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profile--work_container" data-work-id="40711252"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711252/Data_and_text_mining_Comparison_of_statistical_algorithms_for_daily_syndromic_surveillance_aberration_detection"><img alt="Research paper thumbnail of Data and text mining Comparison of statistical algorithms for daily syndromic surveillance aberration detection" class="work-thumbnail" src="https://attachments.academia-assets.com/60996287/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711252/Data_and_text_mining_Comparison_of_statistical_algorithms_for_daily_syndromic_surveillance_aberration_detection">Data and text mining Comparison of statistical algorithms for daily syndromic surveillance aberration detection</a></div><div class="wp-workCard_item"><span>Bioinformatics</span><span>, 2019</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Motivation: Public health authorities can provide more effective and timely interventions to prot...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Motivation: Public health authorities can provide more effective and timely interventions to protect populations during health events if they have effective multi-purpose surveillance systems. These systems rely on aberration detection algorithms to identify potential threats within large datasets. Ensuring the algorithms are sensitive, specific and timely is crucial for protecting public health. Here, we evaluate the performance of three detection algorithms extensively used for syndromic surveillance: the ‘rising activity, multilevel mixed effects, indicator emphasis’ (RAMMIE)  method and the improved quasi-Poisson regression-based method known as ‘Farrington Flexible’ both currently used at Public Health England, and the ‘Early Aberration Reporting System’ (EARS) method used at the US Centre for Disease Control and Prevention. We model the wide range of data structures encountered within the daily syndromic surveillance systems used by PHE. We undertake extensive <br />simulations to identify which algorithms work best across different types of syndromes and different outbreak sizes. We evaluate RAMMIE for the first time since its introduction. Performance metrics were computed and compared in the presence of a range of simulated outbreak types that were added to baseline data. Results: We conclude that amongst the algorithm variants that have a high specificity (i.e. >90%), <br />Farrington Flexible has the highest sensitivity and specificity, whereas RAMMIE has the highest probability of outbreak detection and is the most timely, typically detecting outbreaks 2–3 days earlier.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="512ba96a981d890e7ebf709f91520ea4" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996287,"asset_id":40711252,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996287/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711252"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711252"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711252; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711251"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711251/Twitter_mining_using_semi_supervised_classification_for_relevance_filtering_in_syndromic_surveillance"><img alt="Research paper thumbnail of Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance" class="work-thumbnail" src="https://attachments.academia-assets.com/60996288/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711251/Twitter_mining_using_semi_supervised_classification_for_relevance_filtering_in_syndromic_surveillance">Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance</a></div><div class="wp-workCard_item"><span>Plos One</span><span>, 2019</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We investigate the use of Twitter data to deliver signals for syndromic surveillance in order to ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We investigate the use of Twitter data to deliver signals for syndromic surveillance in order to assess its ability to augment existing syndromic surveillance efforts and give a better understanding of symptomatic people who do not seek healthcare advice directly. We focus on a specific syndrome—asthma/difficulty breathing. We outline data collection using the Twitter streaming API as well as analysis and pre-processing of the collected data. Even with keyword-based data collection, many of the tweets collected are not be relevant because they represent chatter, or talk of awareness instead of an individual suffering a particular condition. In light of this, we set out to identify relevant tweets to collect a strong and reliable signal. For this, we investigate text classification techniques, and in particular we focus on semi-supervised classification techniques since they enable us to use more of the Twitter data collected while only doing very minimal labelling. In this paper, we propose a semi-supervised approach to symptomatic tweet classification and relevance filtering. We also propose alternative techniques to popular deep learning approaches. Additionally, we highlight the use of emojis and other special features capturing the tweet’s tone to improve the classification performance. Our results show that negative emojis and those that denote laughter provide the best classification performance in conjunction with a simple word-level n-gram approach. We obtain good performance in classifying symptomatic tweets with both supervised and semi-supervised algorithms and found that the proposed semi-supervised algorithms preserve more of the relevant tweets and may be advantageous in the context of a weak signal. Finally, we found some correlation (r = 0.414, p = 0.0004) between the Twitter signal generated with the semi-supervised system and data from consultations for related health conditions.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8b244678201872f2eb42829253cc43cc" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996288,"asset_id":40711251,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996288/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711251"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711251"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711251; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711251]").text(description); $(".js-view-count[data-work-id=40711251]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711251; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711251']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "8b244678201872f2eb42829253cc43cc" } } $('.js-work-strip[data-work-id=40711251]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711251,"title":"Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance","internal_url":"https://www.academia.edu/40711251/Twitter_mining_using_semi_supervised_classification_for_relevance_filtering_in_syndromic_surveillance","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996288,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996288/thumbnails/1.jpg","file_name":"PLoS-ONE20191023-22315-1v4bgfv.pdf","download_url":"https://www.academia.edu/attachments/60996288/download_file","bulk_download_file_name":"Twitter_mining_using_semi_supervised_cla.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996288/PLoS-ONE20191023-22315-1v4bgfv-libre.pdf?1571848318=\u0026response-content-disposition=attachment%3B+filename%3DTwitter_mining_using_semi_supervised_cla.pdf\u0026Expires=1740509201\u0026Signature=SseGYrO~OAAsl9sKOEm3ulklhSN7s~j1a520gd3wCaZLVKveTB~1ZAOSDBGaVIhfjqez~8qeoV408ecaTDWknlKxQ1od5KxnE7v~s5JQVrQOZfbQPEuYO1bsCb77FPWhA2se0j5s2DlS7J9godARR7J07TdbZasMxVFS33hgKkXu3x6GaY0jfov62D1cyYRO1uJ37TdwdJQpvYvy6KBG7eNhyntcJitXhpinNsrsmroi098E-ACVzJHp-g8ynH9nRX7MTxhIQln1epMm7GjynwKg6~CLaxiRmfoQMeW99SOCHFZ8NsLtTCNTpol5kFIeUda44dU1AdUub7l-cHemfw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711250"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711250/The_potential_of_recycled_materials_used_in_agriculture_to_contaminate_food_through_uptake_by_livestock"><img alt="Research paper thumbnail of The potential of recycled materials used in agriculture to contaminate food through uptake by livestock" class="work-thumbnail" src="https://attachments.academia-assets.com/60996286/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711250/The_potential_of_recycled_materials_used_in_agriculture_to_contaminate_food_through_uptake_by_livestock">The potential of recycled materials used in agriculture to contaminate food through uptake by livestock</a></div><div class="wp-workCard_item"><span>Science of the Total Environment</span><span>, 2019</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The potential for contaminant uptake from recycled materials used in livestock farming, to animal...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The potential for contaminant uptake from recycled materials used in livestock farming, to animal tissues and organs, was investigated in three practical modular studies involving broiler chickens, laying chickens and pigs. Six types of commercially available recycled materialswere used either as bedding material for chickens or as fertilizer for cropland that later housed outdoor reared pigs. The contaminants studied included regulated contaminants e.g. polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs, dioxins) and polychlorinated biphenyls (PCBs), but related contaminants such as polybrominated diphenylethers (PBDEs), hexabrominated cyclododecane (HBCDD), polychlorinated naphthalenes (PCNs), polybrominated dioxins (PBDD/Fs) and perfluoroalkyl substances (PFAS) were also investigated. Contaminant occurrence in the recycled materials was verified prior to the studies and the relationship to tissue and egg concentrations in market ready animals was investigated using a weights of evidence approach. Contaminant uptake to animal tissues and eggs was observed in all the studies but the extent varied depending on the species and the recycled material. PCBs, PBDEs, PCDD/Fs, PCNs and PFAS showed the highest potential to transfer, with laying chickens showing the most pronounced effects. PBDD/Fs showed lowconcentrations in the recycled materials, making it difficult to evaluate potential transfer. Higher resulting occurrence levels in laying chickens relative to broilers suggests that period of contact with the materials may influence the extent of uptake in chickens. Bio-transfer factors (BTFs) estimated for PCDD/F and PCBs showed a greater magnitude for chicken muscle tissue relative to pigs with the highest values observed for PCBs in laying chickens. There were no significant differences between BTFs for the different chicken tissues which contrasted with the high BTF values for pigs liver relative to muscle. The study raises further questionswhich require investigation such as the effects of repeated or yearly application of recycled materials as fertilizers, and the batch homogeneity/consistency of available recycled materials.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="abecdf286bf48a9633d418e5a21dc7d7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996286,"asset_id":40711250,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996286/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711250"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711250"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711250; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711250]").text(description); $(".js-view-count[data-work-id=40711250]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711250; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711250']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711249"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711249/Syndromic_surveillance_two_decades_experience_of_sustainable_systems_its_people_not_just_data"><img alt="Research paper thumbnail of Syndromic surveillance: two decades experience of sustainable systems -its people not just data" class="work-thumbnail" src="https://attachments.academia-assets.com/60996285/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711249/Syndromic_surveillance_two_decades_experience_of_sustainable_systems_its_people_not_just_data">Syndromic surveillance: two decades experience of sustainable systems -its people not just data</a></div><div class="wp-workCard_item"><span>Epidemiology and Infection </span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Syndromic surveillance is a form of surveillance that generates information for public health act...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Syndromic surveillance is a form of surveillance that generates information for public health action by collecting, analysing and interpreting routine health-related data on symptoms and clinical signs reported by patients and clinicians rather than being based on microbiologically or clinically confirmed cases. In England, a suite of national real-time syndromic surveillance systems (SSS) have been developed over the last 20 years, utilising data from a variety of health care settings (a telehealth triage system, general practice and emergency departments). The real-time systems in England have been used for early detection (e.g. seasonal influenza), for situational awareness (e.g. describing the size and demographics of the impact of a heatwave) and for reassurance of lack of impact on population health of mass gatherings (e.g. the London 2012 Olympic and Paralympic Games).We highlight the lessons learnt from running SSS, for nearly two decades, and propose questions and issues still to be addressed. We feel that syndromic surveillance is an example of the use of ‘big data’, but contend that the focus for sustainable and useful systems should be on the added value of such systems and the importance of people working together to maximise the value for the public health of syndromic surveillance services.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="995ddfa85383c1ea5ec70700425fb360" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996285,"asset_id":40711249,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996285/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711249"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711249"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711249; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711249]").text(description); $(".js-view-count[data-work-id=40711249]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711249; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711249']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "995ddfa85383c1ea5ec70700425fb360" } } $('.js-work-strip[data-work-id=40711249]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711249,"title":"Syndromic surveillance: two decades experience of sustainable systems -its people not just data","internal_url":"https://www.academia.edu/40711249/Syndromic_surveillance_two_decades_experience_of_sustainable_systems_its_people_not_just_data","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996285,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996285/thumbnails/1.jpg","file_name":"Epidemiology-and-Infection_220191023-111482-8g1x9j.pdf","download_url":"https://www.academia.edu/attachments/60996285/download_file","bulk_download_file_name":"Syndromic_surveillance_two_decades_exper.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996285/Epidemiology-and-Infection_220191023-111482-8g1x9j-libre.pdf?1571848295=\u0026response-content-disposition=attachment%3B+filename%3DSyndromic_surveillance_two_decades_exper.pdf\u0026Expires=1740571026\u0026Signature=VaMp5iaoJdAGCWnsUiLYRBMe6Pz~U~hL1qbYxxUFGsHS3jA431JQQzUWQNbNHn4fHiiCU~potpUtkhCc8Zhr5QgDedJF3lubAiGROMWp8c7u2Fxyh2gOZZfXHmEVE7qtKru6kUeQSv6iK1MW~5HKFDgXJfYc0dJDhKPGJbKPucSujtnBZKvaN3Hu8FyjHKFDBOBrl~C-sL-Jo4DWvzJzKMldyur3LLp4qcg1WC9OHLuUO~jh3fZ4d24CjRhS6KIr~4LcsjSwK5W6VQF0qQmKCWEGlmUZ-UAmOyzC5iGHglJbe-RtinIpt12SC9cbTqMzbWKB-j2M9dka1SbOYV8Ryw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711248"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711248/Seasonality_and_the_effects_of_weather_on_Campylobacter_infections"><img alt="Research paper thumbnail of Seasonality and the effects of weather on Campylobacter infections" class="work-thumbnail" src="https://attachments.academia-assets.com/60996278/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711248/Seasonality_and_the_effects_of_weather_on_Campylobacter_infections">Seasonality and the effects of weather on Campylobacter infections</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Campylobacteriosis is a major public health concern. The weather factors that influen...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. Methods: To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. Results: The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas. Conclusions: The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="afc742a2f7fe8af5d907697c4cb4c511" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996278,"asset_id":40711248,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996278/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711248"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711248"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711248; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711247"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711247/Machine_learning_to_refine_decision_making_within_a_syndromic_surveillance_service"><img alt="Research paper thumbnail of Machine learning to refine decision making within a syndromic surveillance service" class="work-thumbnail" src="https://attachments.academia-assets.com/60996269/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711247/Machine_learning_to_refine_decision_making_within_a_syndromic_surveillance_service">Machine learning to refine decision making within a syndromic surveillance service</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situat...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="b5f6e9a63bebcc3c3ef0512c1800eaa9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996269,"asset_id":40711247,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996269/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711247"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711247"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711247; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711247]").text(description); $(".js-view-count[data-work-id=40711247]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711247; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711247']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711246"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711246/Ragweed_pollen_and_allergic_symptoms_in_children_Results_from_a_three_year_longitudinal_study"><img alt="Research paper thumbnail of Ragweed pollen and allergic symptoms in children: Results from a three-year longitudinal study" class="work-thumbnail" src="https://attachments.academia-assets.com/60996273/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711246/Ragweed_pollen_and_allergic_symptoms_in_children_Results_from_a_three_year_longitudinal_study">Ragweed pollen and allergic symptoms in children: Results from a three-year longitudinal study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Common ragweed is a highly allergenic invasive species in Europe, expected to become widespread u...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Common ragweed is a highly allergenic invasive species in Europe, expected to become widespread under climate change. Allergy to ragweed manifests as eye, nasal and lung symptoms, and children may retain these throughout life. The dose-response relationship between symptoms and pollen concentrations is unclear. We undertook a longitudinal study, assessing the association between ragweed pollen concentration and allergic eye, nasal and lung symptoms in children living under a range of ragweed pollen concentrations in Croatia. Over three years, 85 children completed daily diaries, detailing allergic symptoms alongside daily location, activities and medication, resulting in 10,130 individual daily entries. The daily ragweed pollen concentration for the children's locations was obtained, alongside daily weather and air pollution. Parents completed a home/lifestyle/medical questionnaire. Generalised Additive Mixed Models established the relationship between pollen concentrations and symptoms, alongside other covariates. Eye symptoms were associated with mean daily pollen concentration over four days (day of symptoms plus 3 previous days); 61 grains/m 3 /day (95%CI: 45, 100) was j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / s c i t o t e n v the threshold at which 50% of children reported symptoms. Nasal symptoms were associated with mean daily pollen concentration over 12 days (day of symptoms plus 11 previous days); the threshold for 50% of children reporting symptoms was 40 grains/m 3 /day (95%CI: 24, 87). Lung symptoms showed a relationship with mean daily pollen concentration over 19 days (day of symptoms plus 18 previous days), with a threshold of 71 grains/m 3 /day (95%CI: 59, 88). Taking medication on the day of symptoms showed higher odds, suggesting responsive behaviour. Taking medication on the day prior to symptoms showed lower odds of reporting, indicating preventative behaviour. Different symptoms in children demonstrate varying dose-response relationships with ragweed pollen concentrations. Each symptom type responded to pollen exposure over different time periods. Using medication prior to symptoms can reduce symptom presence. These findings can be used to better manage paediatric ragweed allergy symptoms.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0c6dc85be3adc3dc14074db7b044f1ec" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996273,"asset_id":40711246,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996273/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711246"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711246"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711246; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711246]").text(description); $(".js-view-count[data-work-id=40711246]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711246; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711246']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "0c6dc85be3adc3dc14074db7b044f1ec" } } $('.js-work-strip[data-work-id=40711246]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711246,"title":"Ragweed pollen and allergic symptoms in children: Results from a three-year longitudinal study","internal_url":"https://www.academia.edu/40711246/Ragweed_pollen_and_allergic_symptoms_in_children_Results_from_a_three_year_longitudinal_study","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996273,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996273/thumbnails/1.jpg","file_name":"Science-of-the-Total-Environment20191023-86885-f9ngui.pdf","download_url":"https://www.academia.edu/attachments/60996273/download_file","bulk_download_file_name":"Ragweed_pollen_and_allergic_symptoms_in.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996273/Science-of-the-Total-Environment20191023-86885-f9ngui-libre.pdf?1571848296=\u0026response-content-disposition=attachment%3B+filename%3DRagweed_pollen_and_allergic_symptoms_in.pdf\u0026Expires=1740509201\u0026Signature=XXEtc5nHnxyi9BkO3KZu0vYzBBg4L3FqFcPSGV30~HXfSE~NiS6ZcyMpZCtSAOjuS75jwNfXJ7mz-bEkpycd3pUDC0dxqJXUQMWssOOSLc9Pw1xdskxXjoQa0LF8EH-dFVVvtDzbMBPhcNQcUok0E-g8KWkGt7iM6RI00AvZPbXHqrXIL-uAFBusX1SmxizNOtyFMoBtWKKGC~TTMa2XNlvyyhqn4sMYW9EGHzPUPWHniLw0Ir~tm~Y6SILaePvde-48Bsci5zZUVpdSrBvVBN~zgpVfivq5OekFcTkw18Y6zKKSVmPwOY-Jm7sglLhq5v0jkAZ~7TkBNN7fKjs-OA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711245"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711245/Modifiable_Risk_Factors_for_Common_Ragweed_Ambrosia_artemisiifolia_Allergy_and_Disease_in_Children_A_Case_Control_Study"><img alt="Research paper thumbnail of Modifiable Risk Factors for Common Ragweed (Ambrosia artemisiifolia) Allergy and Disease in Children: A Case-Control Study" class="work-thumbnail" src="https://attachments.academia-assets.com/60996257/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711245/Modifiable_Risk_Factors_for_Common_Ragweed_Ambrosia_artemisiifolia_Allergy_and_Disease_in_Children_A_Case_Control_Study">Modifiable Risk Factors for Common Ragweed (Ambrosia artemisiifolia) Allergy and Disease in Children: A Case-Control Study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Ragweed allergy is a major public health concern. Within Europe, ragweed is an introduced species...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Ragweed allergy is a major public health concern. Within Europe, ragweed is an introduced species and research has indicated that the amounts of ragweed pollen are likely to increase over Europe due to climate change, with corresponding increases in ragweed allergy. To address this threat, improving our understanding of predisposing factors for allergic sensitisation to ragweed and disease is necessary, specifically focusing upon factors that are potentially modifiable (i.e., environmental). In this study, a total of 4013 children aged 2-13 years were recruited across Croatia to undergo skin prick tests to determine sensitisation to ragweed and other aeroallergens. A parental questionnaire collected home environment, lifestyle, family and personal medical history, and socioeconomic information. Environmental variables were obtained using Geographical Information Systems and data from nearby pollen, weather, and air pollution stations. Logistic regression was performed (clustered on school) focusing on risk factors for allergic sensitisation and disease. Ragweed sensitisation was strongly associated with ragweed pollen at levels over 5000 grains m -3 year −1 and, above these levels, the risk of sensitisation was 12-16 times greater than in low pollen areas with about 400 grains m -3 year −1 . Genetic factors were strongly associated with sensitisation but nearly all potentially modifiable factors were insignificant. This included measures of local land use and proximity to potential sources of ragweed pollen. Rural residence was protective (odds ratio (OR) 0.73, 95% confidence interval (CI) 0.55-0.98), but the factors underlying this association were unclear. Being sensitised to ragweed doubled (OR 2.17, 95% CI 1.59-2.96) the risk of rhinoconjunctivitis. No other potentially modifiable risk factors were associated with rhinoconjunctivitis. Ragweed sensitisation was strongly associated with ragweed pollen, and sensitisation was significantly associated with rhinoconjunctivitis. Apart from ragweed pollen levels, few other potentially modifiable factors were significantly associated with ragweed sensitisation. Hence, strategies to lower the risk of sensitisation should focus upon ragweed control.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f83cc3c0d4d672edd9a0c6b3f0ff3ceb" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996257,"asset_id":40711245,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996257/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711245"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711245"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711245; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711244"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711244/Exploring_Campylobacter_seasonality_across_Europe_using_The_European_Surveillance_System_TESSy_2008_to_2016"><img alt="Research paper thumbnail of Exploring Campylobacter seasonality across Europe using The European Surveillance System (TESSy), 2008 to 2016" class="work-thumbnail" src="https://attachments.academia-assets.com/60996254/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711244/Exploring_Campylobacter_seasonality_across_Europe_using_The_European_Surveillance_System_TESSy_2008_to_2016">Exploring Campylobacter seasonality across Europe using The European Surveillance System (TESSy), 2008 to 2016</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Campylobacteriosis is the most commonly reported food-borne infection in the European...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Campylobacteriosis is the most commonly reported food-borne infection in the European Union, with an annual number of cases estimated at around 9 million. In many countries, campylobacteriosis has a striking seasonal peak during early/ mid-summer. In the early 2000s, several publications reported on campylobacteriosis seasonality across Europe and associations with temperature and precipitation. Subsequently, many European countries have introduced new measures against this foodborne disease. Aim: To examine how the seasonality of campylobacteriosis varied across Europe from 2008-16, to explore associations with temperature and precipitation, and to compare these results with previous studies. We also sought to assess the utility of the European Surveillance System TESSy for cross-European seasonal analysis of campylobacteriosis. Methods: Ward's Minimum Variance Clustering was used to group countries with similar seasonal patterns of campylobacteriosis. A two-stage multivariate meta-analysis methodology was used to explore associations with temperature and precipitation. Results: Nordic countries had a pronounced seasonal campylobacteriosis peak in mid-to late summer (weeks 29-32), while most other European countries had a less pronounced peak earlier in the year. The United Kingdom, Ireland, Hungary and Slovakia had a slightly earlier peak (week 24). Campylobacteriosis cases were positively associated with temperature and, to a lesser degree, precipitation. Conclusion: Across Europe, the strength and timing of campylobacteriosis peaks have remained similar to those observed previously. In addition, TESSy is a useful resource for cross-European seasonal analysis of infectious diseases such as campylobacteriosis, but its utility depends upon each country's reporting infrastructure.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="b2d26c6581e8f4202a69548a07ec3173" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996254,"asset_id":40711244,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996254/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711244"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711244"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711244; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711243"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711243/Climate_human_behaviour_or_environment_individual_based_modelling_of_Campylobacter_seasonality_and_strategies_to_reduce_disease_burden"><img alt="Research paper thumbnail of Climate, human behaviour or environment: individual-based modelling of Campylobacter seasonality and strategies to reduce disease burden" class="work-thumbnail" src="https://attachments.academia-assets.com/60996252/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711243/Climate_human_behaviour_or_environment_individual_based_modelling_of_Campylobacter_seasonality_and_strategies_to_reduce_disease_burden">Climate, human behaviour or environment: individual-based modelling of Campylobacter seasonality and strategies to reduce disease burden</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/SandersonRoy">Roy Sanderson</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: With over 800 million cases globally, campylobacteriosis is a major cause of food bor...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: With over 800 million cases globally, campylobacteriosis is a major cause of food borne disease. In temperate climates incidence is highly seasonal but the underlying mechanisms are poorly understood, making human disease control difficult. We hypothesised that observed disease patterns reflect complex interactions between weather, patterns of human risk behaviour, immune status and level of food contamination. Only by understanding these can we find effective interventions. Methods: We analysed trends in human Campylobacter cases in NE England from 2004 to 2009, investigating the associations between different risk factors and disease using time-series models. We then developed an individual-based (IB) model of risk behaviour, human immunological responses to infection and environmental contamination driven by weather and land use. We parameterised the IB model for NE England and compared outputs to observed numbers of reported cases each month in the population in 2004-2009. Finally, we used it to investigate different community level disease reduction strategies. Results: Risk behaviours like countryside visits (t = 3.665, P < 0.001 and t = − 2.187, P = 0.029 for temperature and rainfall respectively), and consumption of barbecued food were strongly associated with weather, (t = 3.219, P = 0.002 and t = 2.015, P = 0.045 for weekly average temperature and average maximum temperature respectively) and also rain (t = 2.254, P = 0.02527). This suggests that the effect of weather was indirect, acting through changes in risk behaviour. The seasonal pattern of cases predicted by the IB model was significantly related to observed patterns (r = 0.72, P < 0.001) indicating that simulating risk behaviour could produce the observed seasonal patterns of cases. A vaccination strategy providing short-term immunity was more effective than educational interventions to modify human risk behaviour. Extending immunity to 1 year from 20 days reduced disease burden by an order of magnitude (from 2412-2414 to 203-309 cases per 50,000 person-years). Conclusions: This is the first interdisciplinary study to integrate environment, risk behaviour, socio-demographics and immunology to model Campylobacter infection, including pathways to mitigation. We conclude that vaccination is likely to be the best route for intervening against campylobacteriosis despite the technical problems associated</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6a9c1a49052f91ec979fa17cb1104cf0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996252,"asset_id":40711243,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996252/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711243"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711243"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711243; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "6a9c1a49052f91ec979fa17cb1104cf0" } } $('.js-work-strip[data-work-id=40711243]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711243,"title":"Climate, human behaviour or environment: individual-based modelling of Campylobacter seasonality and strategies to reduce disease burden","internal_url":"https://www.academia.edu/40711243/Climate_human_behaviour_or_environment_individual_based_modelling_of_Campylobacter_seasonality_and_strategies_to_reduce_disease_burden","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996252,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996252/thumbnails/1.jpg","file_name":"Journal-of-Translational-Medicine20191023-36266-vp7v0o.pdf","download_url":"https://www.academia.edu/attachments/60996252/download_file","bulk_download_file_name":"Climate_human_behaviour_or_environment_i.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996252/Journal-of-Translational-Medicine20191023-36266-vp7v0o-libre.pdf?1571848310=\u0026response-content-disposition=attachment%3B+filename%3DClimate_human_behaviour_or_environment_i.pdf\u0026Expires=1740509202\u0026Signature=NglgqBWVOmhQC4OosbMoNS78XOPy6bKkvgTGSNMV42k0tkQm~WuI4ERJwvjnSa8fqfkfrvyP90OuDmUFR4NYdxRv3SLRbYeoyKhPB2okBnC2mckm7PhQWovJk-yulLFjh1AcvmfZqOjwchFrPgST9bkpRqfrmzekM5VsZdvzhx0y1e1aIv-TbE5Z3LhdaqNvFyghhEFgxBa5D~owDyHO1z7gID399fGhfkCT0FfSaTcYx91P5zMXA9JQN8w3ipqjpEAxsrt4ZjZ3RX5MwLvMc1RTMXoQJHiOHmzSvz~QkpQUdLDbbPmSMbFZx9ceuOjFhN7-0f3-YvzklBUWovDZSA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711242"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711242/Climate_Change_and_Water_Related_Infectious_Diseases"><img alt="Research paper thumbnail of Climate Change and Water-Related Infectious Diseases" class="work-thumbnail" src="https://attachments.academia-assets.com/60996250/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711242/Climate_Change_and_Water_Related_Infectious_Diseases">Climate Change and Water-Related Infectious Diseases</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/CHeaviside">Clare Heaviside</a></span></div><div class="wp-workCard_item"><span>atmosphere </span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Water-related, including waterborne, diseases remain important sources of morbidity a...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Water-related, including waterborne, diseases remain important sources of morbidity and mortality worldwide, but particularly in developing countries. The potential for changes in disease associated with predicted anthropogenic climate changes make water-related diseases a target for prevention. Methods: We provide an overview of evidence on potential future changes in water-related disease associated with climate change. Results: A number of pathogens are likely to present risks to public health, including cholera, typhoid, dysentery, leptospirosis, diarrhoeal diseases and harmful algal blooms (HABS). The risks are greatest where the climate effects drive population movements, conflict and disruption, and where drinking water supply infrastructure is poor. The quality of evidence for water-related disease has been documented. Conclusions: We highlight the need to maintain and develop timely surveillance and rapid epidemiological responses to outbreaks and emergence of new waterborne pathogens in all countries. While the main burden of waterborne diseases is in developing countries, there needs to be both technical and financial mechanisms to ensure adequate quantities of good quality water, sewage disposal and hygiene for all. This will be essential in preventing excess morbidity and mortality in areas that will suffer from substantial changes in climate in the future.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9c636a842ea08f2346b4cee52afc7ca0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996250,"asset_id":40711242,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996250/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711242"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711242"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711242; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711242]").text(description); $(".js-view-count[data-work-id=40711242]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711242; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711242']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711194"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711194/A_spatial_and_temporal_analysis_of_risk_factors_associated_with_sporadic_Shiga_toxin_producing_Escherichia_coli_O157_infection_in_England_between_2009_and_2015"><img alt="Research paper thumbnail of A spatial and temporal analysis of risk factors associated with sporadic Shiga toxin-producing Escherichia coli O157 infection in England between 2009 and 2015" class="work-thumbnail" src="https://attachments.academia-assets.com/60996212/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711194/A_spatial_and_temporal_analysis_of_risk_factors_associated_with_sporadic_Shiga_toxin_producing_Escherichia_coli_O157_infection_in_England_between_2009_and_2015">A spatial and temporal analysis of risk factors associated with sporadic Shiga toxin-producing Escherichia coli O157 infection in England between 2009 and 2015</a></div><div class="wp-workCard_item"><span>Epidemiology and Infection</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Rural residence, presence of private water supplies and proximity to high densities of farmed ani...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Rural residence, presence of private water supplies and proximity to high densities of farmed animals is associated with increased risk of STEC O157 infection in England. Cite this article: Elson R, Grace K, Vivancos R, Jenkins C, Adak GK, O'Brien SJ, Lake IR (2018). A spatial and temporal analysis of risk factors associated with sporadic Shiga toxin-producing Escherichia coli O157 infection in England between Abstract Infection with STEC O157 is relatively rare but has potentially serious sequelae, particularly for children. Large outbreaks have prompted considerable efforts designed to reduce transmission primarily from food and direct animal contact. Despite these interventions, numbers of infections have remained constant for many years and the mechanisms leading to many sporadic infections remain unclear. Here, we show that two-thirds of all cases reported in England between 2009 and 2015 were sporadic. Crude rates of infection differed geographically and were highest in rural areas during the summer months. Living in rural areas with high densities of cattle, sheep or pigs and those served by private water supplies were associated with increased risk. Living in an area of lower deprivation contributed to increased risk but this appeared to be associated with reported travel abroad. Fresh water coverage and residential proximity to the coast were not risk factors. To reduce the overall burden of infection in England, interventions designed to reduce the number of sporadic infections with STEC should focus on the residents of rural areas with high densities of livestock and the effective management of non-municipal water supplies. The role of sheep as a reservoir and potential source of infection in humans should not be overlooked.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="194987b93ff6dc54f8a84f9136b5b1fa" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996212,"asset_id":40711194,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996212/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711194"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711194"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711194; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40679707"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40679707/Limiting_global_mean_temperature_increase_to_1_5_2_C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America"><img alt="Research paper thumbnail of Limiting global-mean temperature increase to 1.5-2 °C could reduce the incidence and spatial spread of dengue fever in Latin America" class="work-thumbnail" src="https://attachments.academia-assets.com/60961561/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40679707/Limiting_global_mean_temperature_increase_to_1_5_2_C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America">Limiting global-mean temperature increase to 1.5-2 °C could reduce the incidence and spatial spread of dengue fever in Latin America</a></div><div class="wp-workCard_item"><span>Proceedings of the National Academy of Sciences</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The Paris Climate Agreement aims to hold global-mean temperature well below 2 °C and to pursue ef...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The Paris Climate Agreement aims to hold global-mean temperature well below 2 °C and to pursue efforts to limit it to 1.5 °C above preindustrial levels. While it is recognized that there are benefits for human health in limiting global warming to 1.5 °C, the magnitude with which those societal benefits will be accrued remains unquantified. Crucial to public health preparedness and response is the understanding and quantification of such impacts at different levels of warming. Using dengue in Latin America as a study case, a climate-driven dengue generalized additive mixed model was developed to predict global warming impacts using five different global circulation models, all scaled to represent multiple global-mean temperature assumptions. We show that policies to limit global warming to 2 °C could reduce dengue cases by about 2.8 (0.8–7.4) million cases per year by the end of the century compared with a no-policy scenario that warms by 3.7 °C. Limiting warming further to 1.5 °C produces an additional drop in cases of about 0.5 (0.2–1.1) million per year. Furthermore, we found that by limiting global warming we can limit the expansion of the disease toward areas where incidence is currently low. We anticipate our study to be a starting point for more comprehensive studies incorporating socioeconomic scenarios and how they may further impact dengue incidence. Our results demonstrate that although future climate change may amplify dengue transmission in the region, impacts may be avoided by constraining the level of warming.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="26d2a0f1bcca7a050d16433ef661ae70" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60961561,"asset_id":40679707,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60961561/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40679707"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40679707"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40679707; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "26d2a0f1bcca7a050d16433ef661ae70" } } $('.js-work-strip[data-work-id=40679707]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40679707,"title":"Limiting global-mean temperature increase to 1.5-2 °C could reduce the incidence and spatial spread of dengue fever in Latin America","internal_url":"https://www.academia.edu/40679707/Limiting_global_mean_temperature_increase_to_1_5_2_C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60961561,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60961561/thumbnails/1.jpg","file_name":"colon_gonzalez_ert_al_2018_pnas20191020-38117-1jpamna.pdf","download_url":"https://www.academia.edu/attachments/60961561/download_file","bulk_download_file_name":"Limiting_global_mean_temperature_increas.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60961561/colon_gonzalez_ert_al_2018_pnas20191020-38117-1jpamna-libre.pdf?1571596301=\u0026response-content-disposition=attachment%3B+filename%3DLimiting_global_mean_temperature_increas.pdf\u0026Expires=1740509202\u0026Signature=XSEwS2hXedDCMYaetGtoizI8FrSGUs5ySrskynR-gL6ZHnmKjXgqqBXYcLmo2PzTDTNyMerTYBz40v7NwWWXh~KrSH12LmvYBGZvFcXtOoDcgGK0Y5IlFx0WVzj3tooNwwikNJffTt3gYaSCsH~3mQNZVZkhQCdMjLW8FJ6vIXtQ8TAL9qhnHLw62c~k5eW5do5dqA1gDTadpgogYinSBV8pGOfJ6XvUlCu39UqujrACE87dI5buBX59sSJdSU9cOh-3oWLjBerX8GSb9t7L1fGoyP6FuwZNW19w66-WDsjCfrO9e2URhYqXlZnP4V7Ve3yLY2baL8I5d1wT3Qlaag__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="38013411"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/38013411/Climate_Change_Foodborne_Pathogens_and_Illness_in_Higher_Income_Countries"><img alt="Research paper thumbnail of Climate Change, Foodborne Pathogens and Illness in Higher-Income Countries" class="work-thumbnail" src="https://attachments.academia-assets.com/58033996/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/38013411/Climate_Change_Foodborne_Pathogens_and_Illness_in_Higher_Income_Countries">Climate Change, Foodborne Pathogens and Illness in Higher-Income Countries</a></div><div class="wp-workCard_item"><span>Current Environmental Health Reports</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Purpose of Review We present a review of the likely consequences of climate change for foodborne ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Purpose of Review We present a review of the likely consequences of climate change for foodborne pathogens and associated human illness in higher-income countries. Recent Findings The relationships between climate and food are complex and hence the impacts of climate change uncertain. This makes it difficult to know which foodborne pathogens will be most affected, what the specific effects will be, and on what timescales changes might occur. Hence, a focus upon current capacity and adaptation potential against foodborne pathogens is essential. We highlight a number of developments that may enhance preparedness for climate change. These include the following:</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="59179cb35bbd18a3a22918ad744c8740" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":58033996,"asset_id":38013411,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/58033996/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="38013411"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="38013411"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 38013411; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=38013411]").text(description); $(".js-view-count[data-work-id=38013411]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 38013411; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='38013411']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="36869340"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/36869340/A_methodological_framework_for_the_evaluation_of_syndromic_surveillance_systems_a_case_study_of_England"><img alt="Research paper thumbnail of A methodological framework for the evaluation of syndromic surveillance systems: a case study of England" class="work-thumbnail" src="https://attachments.academia-assets.com/56823807/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/36869340/A_methodological_framework_for_the_evaluation_of_syndromic_surveillance_systems_a_case_study_of_England">A methodological framework for the evaluation of syndromic surveillance systems: a case study of England</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Syndromic surveillance complements traditional public health surveillance by collecti...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect. Methods: We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of detection to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis. Results: Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different outbreak types with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings. Conclusions: The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d89fc848507498965caf780c50a2dfdc" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":56823807,"asset_id":36869340,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/56823807/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="36869340"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="36869340"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 36869340; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="36869327"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/36869327/The_influence_of_a_major_sporting_event_upon_emergency_department_attendances_A_retrospective_cross_national_European_study"><img alt="Research paper thumbnail of The influence of a major sporting event upon emergency department attendances; A retrospective cross-national European study" class="work-thumbnail" src="https://attachments.academia-assets.com/56823791/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/36869327/The_influence_of_a_major_sporting_event_upon_emergency_department_attendances_A_retrospective_cross_national_European_study">The influence of a major sporting event upon emergency department attendances; A retrospective cross-national European study</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/AlexElliot4">Alex Elliot</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Major sporting events may influence attendance levels at hospital emergency departments (ED). Pre...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Major sporting events may influence attendance levels at hospital emergency departments (ED). Previous research has focussed on the impact of single games, or wins/losses for specific teams/countries, limiting wider generalisations. Here we explore the impact of the Euro 2016 football championships on ED attendances across four participating nations (England, France, Northern Ireland, Wales), using a single methodology. Match days were found to have no significant impact upon daily ED attendances levels. Focussing upon hourly attendances , ED attendances across all countries in the four hour pre-match period were statistically significantly lower than would be expected (OR 0.97, 95% CI 0.94–0.99) and further reduced during matches (OR 0.94, 95% CI 0.91–0.97). In the 4 hour post-match period there was no significant increase in attendances (OR 1.01, 95% CI 0.99–1.04). However, these impacts were highly variable between individual matches: for example in the 4 hour period following the final, involving France, the number of ED attendances in France increased significantly (OR 1.27, 95% CI 1.13–1.42). Overall our results indicate relatively small impacts of major sporting events upon ED attendances. The heterogeneity observed makes it difficult for health providers to predict how major sporting events may affect ED attendances but supports the future development of compatible systems in different countries to support cross-border public health surveillance.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="b3a42907f1e42519e8c30d521532f399" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":56823791,"asset_id":36869327,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/56823791/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="36869327"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="36869327"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 36869327; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=36869327]").text(description); $(".js-view-count[data-work-id=36869327]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 36869327; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='36869327']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "b3a42907f1e42519e8c30d521532f399" } } $('.js-work-strip[data-work-id=36869327]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":36869327,"title":"The influence of a major sporting event upon emergency department attendances; A retrospective cross-national European study","internal_url":"https://www.academia.edu/36869327/The_influence_of_a_major_sporting_event_upon_emergency_department_attendances_A_retrospective_cross_national_European_study","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":56823791,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/56823791/thumbnails/1.jpg","file_name":"Hughes_et_al_2018.pdf","download_url":"https://www.academia.edu/attachments/56823791/download_file","bulk_download_file_name":"The_influence_of_a_major_sporting_event.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/56823791/Hughes_et_al_2018-libre.pdf?1529411065=\u0026response-content-disposition=attachment%3B+filename%3DThe_influence_of_a_major_sporting_event.pdf\u0026Expires=1740571026\u0026Signature=e6N9Fqr8CXR5-NaDINVr9ozOCgpbJ1q0ZjOqjrRmCl1Bnpxp~Eso9~C1tBBQl3JWtp2N34aaG84yFItudN4mkFrQFf0K5fN89fDdWwUFpoHQaKkBEtERZlRsExqfnQnOGEtxmWM1LNX-Rw81E5jiLXao0Dtcwx7Y2NBdqvh2ZGFkJf4wASbgP6QkdTw6TCZJdEknZxCObFg7kEgCFPwPi-Y-HyMoWq4CqgmNhF-LDw2COL9fzr5-ijW-bH~KZAgePt~AlRGpv9iXEb76~brFF3wP4Bb4nVi6uQbgGKpKybu3EquVFCkHP~Nw1Fy6zYrE49ce1q6NDCvFkE7df5ge2A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="36741360"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/36741360/Limiting_global_mean_temperature_increase_to_1_5_2C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America"><img alt="Research paper thumbnail of Limiting global-mean temperature increase to 1.5–2C could reduce the incidence and spatial spread of dengue fever in Latin America" class="work-thumbnail" src="https://attachments.academia-assets.com/56684820/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/36741360/Limiting_global_mean_temperature_increase_to_1_5_2C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America">Limiting global-mean temperature increase to 1.5–2C could reduce the incidence and spatial spread of dengue fever in Latin America</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/CPeres">Carlos A Peres</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The Paris Climate Agreement aims to hold global-mean temperature well below 2 • C and to pursue e...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The Paris Climate Agreement aims to hold global-mean temperature well below 2 • C and to pursue efforts to limit it to 1.5 • C above preindustrial levels. While it is recognized that there are benefits for human health in limiting global warming to 1.5 • C, the magnitude with which those societal benefits will be accrued remains unquantified. Crucial to public health preparedness and response is the understanding and quantification of such impacts at different levels of warming. Using dengue in Latin America as a study case, a climate-driven dengue generalized additive mixed model was developed to predict global warming impacts using five different global circulation models, all scaled to represent multiple global-mean temperature assumptions. We show that policies to limit global warming to 2 • C could reduce dengue cases by about 2.8 (0.8–7.4) million cases per year by the end of the century compared with a no-policy scenario that warms by 3.7 • C. Limiting warming further to 1.5 • C produces an additional drop in cases of about 0.5 (0.2–1.1) million per year. Furthermore, we found that by limiting global warming we can limit the expansion of the disease toward areas where incidence is currently low. We anticipate our study to be a starting point for more comprehensive studies incorporating socioeconomic scenarios and how they may further impact dengue incidence. Our results demonstrate that although future climate change may amplify dengue transmission in the region, impacts may be avoided by constraining the level of warming. climate change impacts | disease modeling | Latin America</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="96c6e254983c2c33476e3f40672f9a87" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":56684820,"asset_id":36741360,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/56684820/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="36741360"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="36741360"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 36741360; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=36741360]").text(description); $(".js-view-count[data-work-id=36741360]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 36741360; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='36741360']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "96c6e254983c2c33476e3f40672f9a87" } } $('.js-work-strip[data-work-id=36741360]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":36741360,"title":"Limiting global-mean temperature increase to 1.5–2C could reduce the incidence and spatial spread of dengue fever in Latin America","translated_title":"","metadata":{"abstract":"The Paris Climate Agreement aims to hold global-mean temperature well below 2 • C and to pursue efforts to limit it to 1.5 • C above preindustrial levels. 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Colon-gonzalez</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Zika is one of the most challenging emergent vector-borne diseases, yet its future public health ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Zika is one of the most challenging emergent vector-borne diseases, yet its future public health impact remains unclear. Zika was of little public health concern until recent reports of its association with congenital syndromes. By 3 August 2017 *217,000 Zika cases and *3,400 cases of associated congenital syndrome were reported in Latin America and the Caribbean. Some modelling exercises suggest that Zika virus infection could become endemic in agreement with recent declarations from the The World Health Organisation.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cebc96ac710b4c64530bb513f4972570" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":54895424,"asset_id":35032899,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/54895424/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35032899"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35032899"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35032899; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35032899]").text(description); $(".js-view-count[data-work-id=35032899]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35032899; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35032899']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "cebc96ac710b4c64530bb513f4972570" } } $('.js-work-strip[data-work-id=35032899]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":35032899,"title":"After the epidemic: Zika virus projections for Latin America and the Caribbean","translated_title":"","metadata":{"abstract":"Zika is one of the most challenging emergent vector-borne diseases, yet its future public health impact remains unclear. Zika was of little public health concern until recent reports of its association with congenital syndromes. By 3 August 2017 *217,000 Zika cases and *3,400 cases of associated congenital syndrome were reported in Latin America and the Caribbean. Some modelling exercises suggest that Zika virus infection could become endemic in agreement with recent declarations from the The World Health Organisation.\n"},"translated_abstract":"Zika is one of the most challenging emergent vector-borne diseases, yet its future public health impact remains unclear. Zika was of little public health concern until recent reports of its association with congenital syndromes. By 3 August 2017 *217,000 Zika cases and *3,400 cases of associated congenital syndrome were reported in Latin America and the Caribbean. Some modelling exercises suggest that Zika virus infection could become endemic in agreement with recent declarations from the The World Health Organisation.\n","internal_url":"https://www.academia.edu/35032899/After_the_epidemic_Zika_virus_projections_for_Latin_America_and_the_Caribbean","translated_internal_url":"","created_at":"2017-11-02T09:27:49.104-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35244294,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":30567007,"work_id":35032899,"tagging_user_id":35244294,"tagged_user_id":6369024,"co_author_invite_id":null,"email":"c***s@gmail.com","affiliation":"University of East Anglia","display_order":1,"name":"Carlos A Peres","title":"After the epidemic: Zika virus projections for Latin America and the Caribbean"},{"id":30567008,"work_id":35032899,"tagging_user_id":35244294,"tagged_user_id":29236961,"co_author_invite_id":null,"email":"p***r@uea.ac.uk","display_order":2,"name":"Paul R Hunter","title":"After the epidemic: Zika virus projections for Latin America and the Caribbean"},{"id":30567009,"work_id":35032899,"tagging_user_id":35244294,"tagged_user_id":47961614,"co_author_invite_id":null,"email":"f***n@uea.ac.uk","display_order":3,"name":"F. Colon-gonzalez","title":"After the epidemic: Zika virus projections for Latin America and the Caribbean"},{"id":30567010,"work_id":35032899,"tagging_user_id":35244294,"tagged_user_id":45173449,"co_author_invite_id":null,"email":"c***r@yahoo.com","display_order":4,"name":"Christine Steiner São Bernardo","title":"After the epidemic: Zika virus projections for Latin America and the Caribbean"}],"downloadable_attachments":[{"id":54895424,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/54895424/thumbnails/1.jpg","file_name":"Colon_gonszalez_et_al_2017.pdf","download_url":"https://www.academia.edu/attachments/54895424/download_file","bulk_download_file_name":"After_the_epidemic_Zika_virus_projection.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/54895424/Colon_gonszalez_et_al_2017-libre.pdf?1509896623=\u0026response-content-disposition=attachment%3B+filename%3DAfter_the_epidemic_Zika_virus_projection.pdf\u0026Expires=1738700426\u0026Signature=PtLyP9isvSitlQkMwjgkTgmnvZgvvx7K63QaayBPYouFVDklyDd1y5LjQ~0slX9tvdX7x7kons5etgcYwOvWAiWKiGu7dRBwFhA5AhaQnYyIqZzQvnOOH6~7G0diPiIJP5e8ymFfc3mmfWR6p3fYmT7x-UdmezuIk7eQVIKFt1p2IZNO2soAI7iBDScimrDpZlzchzCI0JAlTJmBkqO~sE~yvno8F3G0szSR6RujkU0MNkQ3iL5EwEAkWzsfM-yvuMUFLzEmWKEZc7aU4qo~hqq6j58mnxiuTlFU7pZVd9tNex240EYKTYePjOU9GfIrA-tw2974ShzP9TTGlSM4fQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"After_the_epidemic_Zika_virus_projections_for_Latin_America_and_the_Caribbean","translated_slug":"","page_count":19,"language":"en","content_type":"Work","summary":"Zika is one of the most challenging emergent vector-borne diseases, yet its future public health impact remains unclear. Zika was of little public health concern until recent reports of its association with congenital syndromes. By 3 August 2017 *217,000 Zika cases and *3,400 cases of associated congenital syndrome were reported in Latin America and the Caribbean. Some modelling exercises suggest that Zika virus infection could become endemic in agreement with recent declarations from the The World Health Organisation.\n","owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":54895424,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/54895424/thumbnails/1.jpg","file_name":"Colon_gonszalez_et_al_2017.pdf","download_url":"https://www.academia.edu/attachments/54895424/download_file","bulk_download_file_name":"After_the_epidemic_Zika_virus_projection.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/54895424/Colon_gonszalez_et_al_2017-libre.pdf?1509896623=\u0026response-content-disposition=attachment%3B+filename%3DAfter_the_epidemic_Zika_virus_projection.pdf\u0026Expires=1738700426\u0026Signature=PtLyP9isvSitlQkMwjgkTgmnvZgvvx7K63QaayBPYouFVDklyDd1y5LjQ~0slX9tvdX7x7kons5etgcYwOvWAiWKiGu7dRBwFhA5AhaQnYyIqZzQvnOOH6~7G0diPiIJP5e8ymFfc3mmfWR6p3fYmT7x-UdmezuIk7eQVIKFt1p2IZNO2soAI7iBDScimrDpZlzchzCI0JAlTJmBkqO~sE~yvno8F3G0szSR6RujkU0MNkQ3iL5EwEAkWzsfM-yvuMUFLzEmWKEZc7aU4qo~hqq6j58mnxiuTlFU7pZVd9tNex240EYKTYePjOU9GfIrA-tw2974ShzP9TTGlSM4fQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":56989,"name":"Latin America","url":"https://www.academia.edu/Documents/in/Latin_America"},{"id":1276661,"name":"Epedemiology","url":"https://www.academia.edu/Documents/in/Epedemiology"},{"id":2287813,"name":"Zika Virus","url":"https://www.academia.edu/Documents/in/Zika_Virus"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="33023702"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/33023702/A_novel_sampling_method_for_assessing_human_pathogen_interactions_in_the_natural_environment_using_boot_socks_and_citizen_scientists_with_an_application_to_the_seasonality_of_Campylobacter"><img alt="Research paper thumbnail of A novel sampling method for assessing human-pathogen interactions in the natural environment using boot socks and citizen scientists, with an application to the seasonality of Campylobacter" class="work-thumbnail" src="https://attachments.academia-assets.com/53134521/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/33023702/A_novel_sampling_method_for_assessing_human_pathogen_interactions_in_the_natural_environment_using_boot_socks_and_citizen_scientists_with_an_application_to_the_seasonality_of_Campylobacter">A novel sampling method for assessing human-pathogen interactions in the natural environment using boot socks and citizen scientists, with an application to the seasonality of Campylobacter</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper introduces a novel method for sampling pathogens in natural environments. It uses fab...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper introduces a novel method for sampling pathogens in natural environments.  It uses fabric boot socks worn over walkers’ shoes allowing collection of composite samples over large areas.  Wide area sampling is better suited to studies focussing upon human exposure to pathogens (e.g. recreational walking).  This sampling method is implemented using a Citizen Science approach: groups of three walkers wearing boot socks undertook one of six routes, 40 times over 16 months in the North West (NW) and East Anglian (EA) regions of England.  To validate this methodology we report the successful implementation of this Citizen Science approach, the observation that Campylobacter was detected on 47% of boot socks, and the observation that multiple boot socks from individual walks produced consistent results.  Findings indicate elevated Campylobacter<br /> presence in the livestock dominated NW in comparison to EA (55.8% vs 38.6%).  Seasonal variation in Campylobacter presence was found between regions, with indications of winter peaks in both regions, but a spring peak in NW.  Campylobacter presence on boot socks was negatively associated with ambient temperature (p=0.011) and positively associated with precipitation (p<0.001), results which are consistent with our understanding of Campylobacter survival and the probability of material adhering to boot socks. C. jejuni was the predominant species found, with C. coli largely restricted to the livestock dominated NW.  Source attribution analysis indicated that the potential source of C. jejuni was predominantly sheep in NW and wild birds in EA but did not vary between peak and non-peak periods of human incidence.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9f2a95e3231ccf7de33acd53dd9423de" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":53134521,"asset_id":33023702,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/53134521/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="33023702"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="33023702"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 33023702; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=33023702]").text(description); $(".js-view-count[data-work-id=33023702]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 33023702; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='33023702']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "9f2a95e3231ccf7de33acd53dd9423de" } } $('.js-work-strip[data-work-id=33023702]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":33023702,"title":"A novel sampling method for assessing human-pathogen interactions in the natural environment using boot socks and citizen scientists, with an application to the seasonality of Campylobacter","internal_url":"https://www.academia.edu/33023702/A_novel_sampling_method_for_assessing_human_pathogen_interactions_in_the_natural_environment_using_boot_socks_and_citizen_scientists_with_an_application_to_the_seasonality_of_Campylobacter","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":53134521,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/53134521/thumbnails/1.jpg","file_name":"Appl._Environ._Microbiol.-2017-Jones-AEM.00162-17.pdf","download_url":"https://www.academia.edu/attachments/53134521/download_file","bulk_download_file_name":"A_novel_sampling_method_for_assessing_hu.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/53134521/Appl._Environ._Microbiol.-2017-Jones-AEM.00162-17-libre.pdf?1494857939=\u0026response-content-disposition=attachment%3B+filename%3DA_novel_sampling_method_for_assessing_hu.pdf\u0026Expires=1740509202\u0026Signature=Kx0dskRr-dGjBays5dIyANv5ln0WOnHhrXqIAVOBcLGi~oo4bJUaTa-XoickdJkylE1L57a7rZaOHfTj~GwR~uNL1QE1FHVeoYyavgPhTQ49kAWx5T31niXOAoYbAyuPwPpI~ACmuic3lLwr~plHEJGlrMY68oCn8Cn0UYkF2LwT3BYo-JVqVcQVCdZkLiR7fw5D9~ExfwUj474teEExqazLDMvTUHPBKbUmG9Qida-JWfhdgWb-5u6u6Xml11cBVsN3D4E8dfEpkUDZC9MUHR5jCyi~EzwMTKj8I2YWfbph46V~MdHD7aWabmRMxQdSWx~hoOWVTt1kRT8ZOSDUZA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="32510948"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/32510948/Climate_Change_and_Future_Pollen_Allergy_in_Europe"><img alt="Research paper thumbnail of Climate Change and Future Pollen Allergy in Europe" class="work-thumbnail" src="https://attachments.academia-assets.com/52695919/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/32510948/Climate_Change_and_Future_Pollen_Allergy_in_Europe">Climate Change and Future Pollen Allergy in Europe</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background : Globally pollen allergy is a major public health problem, but a f undamental unknow...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background<br />: Globally pollen allergy is a major public health problem, but a f<br />undamental <br />unknown is the likely impact of climate change<br />. To our knowledge, this is the first study to <br />quantify the consequences of climate change upon pollen allergy in humans.<br />Objectives<br />: To produce quantitative estimates of <br />the potential impact of climate change upon <br />pollen allergy in humans, focusing upon common ragweed (<br />Ambrosia artemisiifolia<br />) in Europe. <br />Methods:<br />A process-based <br />model estimated <br />the <br />change in ragweed’s range under climate change. <br />A second model simulated current and future ragweed pollen levels. These <br />were translated into <br />health burdens using a dose-response curve generated from a systematic review and current and <br />future population data. Models considered two different suites of regional climate/pollen models, <br />two greenhouse gas emissions scenarios (RCP4.5 and 8.5), and three different plant invasion <br />scenarios. <br />Results<br />: Our primary estimates indicate that sensitization to ragweed will more than double in <br />Europe, from 33 to 77 million people, by 2041-2060. According to our projections, while <br />sensitization will increase in countries with an existing ragweed problem (e.g. Hungary, the <br />Balkans), the greatest proportional increases will occur where sensitization is uncommon (e.g. <br />Germany, Poland, France). Higher pollen concentrations and a longer pollen season may also <br />increase the severity of symptoms. Our model projections are driven predominantly by chan<br />ges <br />in climate (66%), but also are influenced by current trends in the spread of this invasive plant <br />species.  Assumptions about the rate at which ragweed spreads throughout Europe have a large <br />influence upon the results. <br />Conclusions<br />: Our quantitative estimates indicate that ragweed pollen allergy will<br /> become a <br />common health problem across Europe, expanding into areas where it is currently uncommon. <br />Control of ragweed spread may be an important adaptation strategy in response to climate <br />change.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cfc6b0ec44a4532014b27917ee6072e5" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":52695919,"asset_id":32510948,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/52695919/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="32510948"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="32510948"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 32510948; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=32510948]").text(description); $(".js-view-count[data-work-id=32510948]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 32510948; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='32510948']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "cfc6b0ec44a4532014b27917ee6072e5" } } $('.js-work-strip[data-work-id=32510948]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":32510948,"title":"Climate Change and Future Pollen Allergy in Europe","internal_url":"https://www.academia.edu/32510948/Climate_Change_and_Future_Pollen_Allergy_in_Europe","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":52695919,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/52695919/thumbnails/1.jpg","file_name":"lake_et_al_2017_ehp.pdf","download_url":"https://www.academia.edu/attachments/52695919/download_file","bulk_download_file_name":"Climate_Change_and_Future_Pollen_Allergy.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/52695919/lake_et_al_2017_ehp-libre.pdf?1492616773=\u0026response-content-disposition=attachment%3B+filename%3DClimate_Change_and_Future_Pollen_Allergy.pdf\u0026Expires=1740509202\u0026Signature=Ppigfhr5K6W956D7CMgmeTSW-kiY3N9NWmR8QTJoQ5YD8d18KE6DAU7M6is-ID0p0wg5ZYemjXqkKRSZ6lY3rLCJTJkxwDFX-iTuiZYPGlZB9UOMWbvlkdExOuqsmeAo16J68iPZ2ueOY266iWcQVRGmZ33sD8en54fobC8AwdE6GzAsFjesR3T9uNZPKnQJkoO1WSFblg~PY1KsbRWEdbQe9NvoMx5digMbwbE5Jqr9bAMcDwZ4ICcoDwCoxiKTiVEVXVNcyV2JfxPFxUywIdteE1kMjpqV5r-V0-BH9u9-vma~e4u43OTe0usIFsLnwPhKQvRvGHO74P8iyhTfbQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="3611676" id="papers"><div class="js-work-strip profile--work_container" data-work-id="40711252"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711252/Data_and_text_mining_Comparison_of_statistical_algorithms_for_daily_syndromic_surveillance_aberration_detection"><img alt="Research paper thumbnail of Data and text mining Comparison of statistical algorithms for daily syndromic surveillance aberration detection" class="work-thumbnail" src="https://attachments.academia-assets.com/60996287/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711252/Data_and_text_mining_Comparison_of_statistical_algorithms_for_daily_syndromic_surveillance_aberration_detection">Data and text mining Comparison of statistical algorithms for daily syndromic surveillance aberration detection</a></div><div class="wp-workCard_item"><span>Bioinformatics</span><span>, 2019</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Motivation: Public health authorities can provide more effective and timely interventions to prot...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Motivation: Public health authorities can provide more effective and timely interventions to protect populations during health events if they have effective multi-purpose surveillance systems. These systems rely on aberration detection algorithms to identify potential threats within large datasets. Ensuring the algorithms are sensitive, specific and timely is crucial for protecting public health. Here, we evaluate the performance of three detection algorithms extensively used for syndromic surveillance: the ‘rising activity, multilevel mixed effects, indicator emphasis’ (RAMMIE)  method and the improved quasi-Poisson regression-based method known as ‘Farrington Flexible’ both currently used at Public Health England, and the ‘Early Aberration Reporting System’ (EARS) method used at the US Centre for Disease Control and Prevention. We model the wide range of data structures encountered within the daily syndromic surveillance systems used by PHE. We undertake extensive <br />simulations to identify which algorithms work best across different types of syndromes and different outbreak sizes. We evaluate RAMMIE for the first time since its introduction. Performance metrics were computed and compared in the presence of a range of simulated outbreak types that were added to baseline data. Results: We conclude that amongst the algorithm variants that have a high specificity (i.e. >90%), <br />Farrington Flexible has the highest sensitivity and specificity, whereas RAMMIE has the highest probability of outbreak detection and is the most timely, typically detecting outbreaks 2–3 days earlier.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="512ba96a981d890e7ebf709f91520ea4" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996287,"asset_id":40711252,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996287/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711252"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711252"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711252; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711251"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711251/Twitter_mining_using_semi_supervised_classification_for_relevance_filtering_in_syndromic_surveillance"><img alt="Research paper thumbnail of Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance" class="work-thumbnail" src="https://attachments.academia-assets.com/60996288/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711251/Twitter_mining_using_semi_supervised_classification_for_relevance_filtering_in_syndromic_surveillance">Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance</a></div><div class="wp-workCard_item"><span>Plos One</span><span>, 2019</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We investigate the use of Twitter data to deliver signals for syndromic surveillance in order to ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We investigate the use of Twitter data to deliver signals for syndromic surveillance in order to assess its ability to augment existing syndromic surveillance efforts and give a better understanding of symptomatic people who do not seek healthcare advice directly. We focus on a specific syndrome—asthma/difficulty breathing. We outline data collection using the Twitter streaming API as well as analysis and pre-processing of the collected data. Even with keyword-based data collection, many of the tweets collected are not be relevant because they represent chatter, or talk of awareness instead of an individual suffering a particular condition. In light of this, we set out to identify relevant tweets to collect a strong and reliable signal. For this, we investigate text classification techniques, and in particular we focus on semi-supervised classification techniques since they enable us to use more of the Twitter data collected while only doing very minimal labelling. In this paper, we propose a semi-supervised approach to symptomatic tweet classification and relevance filtering. We also propose alternative techniques to popular deep learning approaches. Additionally, we highlight the use of emojis and other special features capturing the tweet’s tone to improve the classification performance. Our results show that negative emojis and those that denote laughter provide the best classification performance in conjunction with a simple word-level n-gram approach. We obtain good performance in classifying symptomatic tweets with both supervised and semi-supervised algorithms and found that the proposed semi-supervised algorithms preserve more of the relevant tweets and may be advantageous in the context of a weak signal. Finally, we found some correlation (r = 0.414, p = 0.0004) between the Twitter signal generated with the semi-supervised system and data from consultations for related health conditions.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8b244678201872f2eb42829253cc43cc" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996288,"asset_id":40711251,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996288/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711251"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711251"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711251; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711251]").text(description); $(".js-view-count[data-work-id=40711251]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711251; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711251']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "8b244678201872f2eb42829253cc43cc" } } $('.js-work-strip[data-work-id=40711251]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711251,"title":"Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance","internal_url":"https://www.academia.edu/40711251/Twitter_mining_using_semi_supervised_classification_for_relevance_filtering_in_syndromic_surveillance","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996288,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996288/thumbnails/1.jpg","file_name":"PLoS-ONE20191023-22315-1v4bgfv.pdf","download_url":"https://www.academia.edu/attachments/60996288/download_file","bulk_download_file_name":"Twitter_mining_using_semi_supervised_cla.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996288/PLoS-ONE20191023-22315-1v4bgfv-libre.pdf?1571848318=\u0026response-content-disposition=attachment%3B+filename%3DTwitter_mining_using_semi_supervised_cla.pdf\u0026Expires=1740509201\u0026Signature=SseGYrO~OAAsl9sKOEm3ulklhSN7s~j1a520gd3wCaZLVKveTB~1ZAOSDBGaVIhfjqez~8qeoV408ecaTDWknlKxQ1od5KxnE7v~s5JQVrQOZfbQPEuYO1bsCb77FPWhA2se0j5s2DlS7J9godARR7J07TdbZasMxVFS33hgKkXu3x6GaY0jfov62D1cyYRO1uJ37TdwdJQpvYvy6KBG7eNhyntcJitXhpinNsrsmroi098E-ACVzJHp-g8ynH9nRX7MTxhIQln1epMm7GjynwKg6~CLaxiRmfoQMeW99SOCHFZ8NsLtTCNTpol5kFIeUda44dU1AdUub7l-cHemfw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711250"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711250/The_potential_of_recycled_materials_used_in_agriculture_to_contaminate_food_through_uptake_by_livestock"><img alt="Research paper thumbnail of The potential of recycled materials used in agriculture to contaminate food through uptake by livestock" class="work-thumbnail" src="https://attachments.academia-assets.com/60996286/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711250/The_potential_of_recycled_materials_used_in_agriculture_to_contaminate_food_through_uptake_by_livestock">The potential of recycled materials used in agriculture to contaminate food through uptake by livestock</a></div><div class="wp-workCard_item"><span>Science of the Total Environment</span><span>, 2019</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The potential for contaminant uptake from recycled materials used in livestock farming, to animal...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The potential for contaminant uptake from recycled materials used in livestock farming, to animal tissues and organs, was investigated in three practical modular studies involving broiler chickens, laying chickens and pigs. Six types of commercially available recycled materialswere used either as bedding material for chickens or as fertilizer for cropland that later housed outdoor reared pigs. The contaminants studied included regulated contaminants e.g. polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs, dioxins) and polychlorinated biphenyls (PCBs), but related contaminants such as polybrominated diphenylethers (PBDEs), hexabrominated cyclododecane (HBCDD), polychlorinated naphthalenes (PCNs), polybrominated dioxins (PBDD/Fs) and perfluoroalkyl substances (PFAS) were also investigated. Contaminant occurrence in the recycled materials was verified prior to the studies and the relationship to tissue and egg concentrations in market ready animals was investigated using a weights of evidence approach. Contaminant uptake to animal tissues and eggs was observed in all the studies but the extent varied depending on the species and the recycled material. PCBs, PBDEs, PCDD/Fs, PCNs and PFAS showed the highest potential to transfer, with laying chickens showing the most pronounced effects. PBDD/Fs showed lowconcentrations in the recycled materials, making it difficult to evaluate potential transfer. Higher resulting occurrence levels in laying chickens relative to broilers suggests that period of contact with the materials may influence the extent of uptake in chickens. Bio-transfer factors (BTFs) estimated for PCDD/F and PCBs showed a greater magnitude for chicken muscle tissue relative to pigs with the highest values observed for PCBs in laying chickens. There were no significant differences between BTFs for the different chicken tissues which contrasted with the high BTF values for pigs liver relative to muscle. The study raises further questionswhich require investigation such as the effects of repeated or yearly application of recycled materials as fertilizers, and the batch homogeneity/consistency of available recycled materials.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="abecdf286bf48a9633d418e5a21dc7d7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996286,"asset_id":40711250,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996286/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711250"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711250"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711250; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "abecdf286bf48a9633d418e5a21dc7d7" } } $('.js-work-strip[data-work-id=40711250]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711250,"title":"The potential of recycled materials used in agriculture to contaminate food through uptake by livestock","internal_url":"https://www.academia.edu/40711250/The_potential_of_recycled_materials_used_in_agriculture_to_contaminate_food_through_uptake_by_livestock","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996286,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996286/thumbnails/1.jpg","file_name":"Science-of-the-Total-Environment_220191023-26105-1s5d0kr.pdf","download_url":"https://www.academia.edu/attachments/60996286/download_file","bulk_download_file_name":"The_potential_of_recycled_materials_used.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996286/Science-of-the-Total-Environment_220191023-26105-1s5d0kr-libre.pdf?1571848300=\u0026response-content-disposition=attachment%3B+filename%3DThe_potential_of_recycled_materials_used.pdf\u0026Expires=1740509201\u0026Signature=C54j~2bvPRUT6J1sNdN0xfP8JrDhpuPuC4CL~EVVXZk4qYNPnHfeRgFu4YHq6dnHgRA15YSPYCHIT0UDbSn8kkpdvoZgtBWv6Gs3uayE~~IRJDJa-sIRdQAxsShB~B1RbpWy1pTDy5ww2~2lgeQMQ6f1dR6qKMVOaXf~wLMAazHCm6V~ONY0-u~VEbOyxFSDftmAxhOXo2Pvn-Rh2Ja~awv0BpwKsiFg1iM6OlUl2PjL4KzCVxN~zaDI3HXAcjlxDdlCjV2~l1RTz9Qr9RsQ9qfYIeiL9v9pMcOkJZIkjvfFKtsqjAs5BUPOwy0pRY-K6S3r8DYZPiL9k7J8QV9YFQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711249"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711249/Syndromic_surveillance_two_decades_experience_of_sustainable_systems_its_people_not_just_data"><img alt="Research paper thumbnail of Syndromic surveillance: two decades experience of sustainable systems -its people not just data" class="work-thumbnail" src="https://attachments.academia-assets.com/60996285/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711249/Syndromic_surveillance_two_decades_experience_of_sustainable_systems_its_people_not_just_data">Syndromic surveillance: two decades experience of sustainable systems -its people not just data</a></div><div class="wp-workCard_item"><span>Epidemiology and Infection </span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Syndromic surveillance is a form of surveillance that generates information for public health act...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Syndromic surveillance is a form of surveillance that generates information for public health action by collecting, analysing and interpreting routine health-related data on symptoms and clinical signs reported by patients and clinicians rather than being based on microbiologically or clinically confirmed cases. In England, a suite of national real-time syndromic surveillance systems (SSS) have been developed over the last 20 years, utilising data from a variety of health care settings (a telehealth triage system, general practice and emergency departments). The real-time systems in England have been used for early detection (e.g. seasonal influenza), for situational awareness (e.g. describing the size and demographics of the impact of a heatwave) and for reassurance of lack of impact on population health of mass gatherings (e.g. the London 2012 Olympic and Paralympic Games).We highlight the lessons learnt from running SSS, for nearly two decades, and propose questions and issues still to be addressed. We feel that syndromic surveillance is an example of the use of ‘big data’, but contend that the focus for sustainable and useful systems should be on the added value of such systems and the importance of people working together to maximise the value for the public health of syndromic surveillance services.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="995ddfa85383c1ea5ec70700425fb360" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996285,"asset_id":40711249,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996285/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711249"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711249"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711249; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711249]").text(description); $(".js-view-count[data-work-id=40711249]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711249; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711249']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711248"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711248/Seasonality_and_the_effects_of_weather_on_Campylobacter_infections"><img alt="Research paper thumbnail of Seasonality and the effects of weather on Campylobacter infections" class="work-thumbnail" src="https://attachments.academia-assets.com/60996278/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711248/Seasonality_and_the_effects_of_weather_on_Campylobacter_infections">Seasonality and the effects of weather on Campylobacter infections</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Campylobacteriosis is a major public health concern. The weather factors that influen...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. Methods: To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. Results: The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas. Conclusions: The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="afc742a2f7fe8af5d907697c4cb4c511" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996278,"asset_id":40711248,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996278/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711248"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711248"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711248; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711248]").text(description); $(".js-view-count[data-work-id=40711248]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711248; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711248']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "afc742a2f7fe8af5d907697c4cb4c511" } } $('.js-work-strip[data-work-id=40711248]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711248,"title":"Seasonality and the effects of weather on Campylobacter infections","internal_url":"https://www.academia.edu/40711248/Seasonality_and_the_effects_of_weather_on_Campylobacter_infections","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996278,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996278/thumbnails/1.jpg","file_name":"BMC-Infectious-Diseases20191023-36179-1v31bew.pdf","download_url":"https://www.academia.edu/attachments/60996278/download_file","bulk_download_file_name":"Seasonality_and_the_effects_of_weather_o.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996278/BMC-Infectious-Diseases20191023-36179-1v31bew-libre.pdf?1571848309=\u0026response-content-disposition=attachment%3B+filename%3DSeasonality_and_the_effects_of_weather_o.pdf\u0026Expires=1740571026\u0026Signature=AavB26FnWBzvjf7iL-8Gn~6sLZ1ovZ9qHqme4NUdVMpuai12YFRvgZAClinWGQfYZpimqrhZw82V3-BnlKxrY2g-hlM63PSacmGl6iJhMcxZX9g8S4ZmVuh7D4b5XX5r3rx2ojIJ9-N6~fOIz4586xCDAmRe0XvT6w46z9o~6F4m8Q8~FIRFVtxD1uJaMpI5Um7WSiYpwUXnIb14elM0PvU3g08ni3fVRvVYbFwx3qr6Bh9pQ~48SDjUsnyw1hAZy0GAFsnIE4JFAKq9vhborAPPBwJ83fONlo~DkzlRLmh4BANASpZzfkbJmfQ4kvRhdwtchM0VTnkLHQ0gIiG~ag__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711247"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711247/Machine_learning_to_refine_decision_making_within_a_syndromic_surveillance_service"><img alt="Research paper thumbnail of Machine learning to refine decision making within a syndromic surveillance service" class="work-thumbnail" src="https://attachments.academia-assets.com/60996269/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711247/Machine_learning_to_refine_decision_making_within_a_syndromic_surveillance_service">Machine learning to refine decision making within a syndromic surveillance service</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situat...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="b5f6e9a63bebcc3c3ef0512c1800eaa9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996269,"asset_id":40711247,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996269/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711247"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711247"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711247; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "b5f6e9a63bebcc3c3ef0512c1800eaa9" } } $('.js-work-strip[data-work-id=40711247]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711247,"title":"Machine learning to refine decision making within a syndromic surveillance service","internal_url":"https://www.academia.edu/40711247/Machine_learning_to_refine_decision_making_within_a_syndromic_surveillance_service","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996269,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996269/thumbnails/1.jpg","file_name":"BMC-Public-Health20191023-80324-15p48f.pdf","download_url":"https://www.academia.edu/attachments/60996269/download_file","bulk_download_file_name":"Machine_learning_to_refine_decision_maki.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996269/BMC-Public-Health20191023-80324-15p48f-libre.pdf?1571848295=\u0026response-content-disposition=attachment%3B+filename%3DMachine_learning_to_refine_decision_maki.pdf\u0026Expires=1740571026\u0026Signature=Q6uC7~eqRZTBQdvRCx3aaiIG6~-CKrek3TPalfZtaO~g4JhuShzPvZSzLSNKm2HQxdhbzlDortG6pqpGMuWjOU8qwsUpO0JC603Nys1I9juUhcwS-~AfPClwypzp9oPH82DQ3-TMwWCfjQtLJjAu219fxcb3VJqPgQ0iyfxJw6QhpoO1gpCB9iNRgetCvRTCF70gcm4bQtaoJzskM4oTsF9fd7v8HNnx76vfmF8FDSbWe7ylVqTtWTqYzaVV~lQZQaqKjlaCvf87Pk8zFkl9NpgoMbUcttFtr5QQhxD3~AP27QgiPwrmUHIz~3dfVBX86PFeooTXkZBlrjXh21iykA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711246"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711246/Ragweed_pollen_and_allergic_symptoms_in_children_Results_from_a_three_year_longitudinal_study"><img alt="Research paper thumbnail of Ragweed pollen and allergic symptoms in children: Results from a three-year longitudinal study" class="work-thumbnail" src="https://attachments.academia-assets.com/60996273/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711246/Ragweed_pollen_and_allergic_symptoms_in_children_Results_from_a_three_year_longitudinal_study">Ragweed pollen and allergic symptoms in children: Results from a three-year longitudinal study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Common ragweed is a highly allergenic invasive species in Europe, expected to become widespread u...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Common ragweed is a highly allergenic invasive species in Europe, expected to become widespread under climate change. Allergy to ragweed manifests as eye, nasal and lung symptoms, and children may retain these throughout life. The dose-response relationship between symptoms and pollen concentrations is unclear. We undertook a longitudinal study, assessing the association between ragweed pollen concentration and allergic eye, nasal and lung symptoms in children living under a range of ragweed pollen concentrations in Croatia. Over three years, 85 children completed daily diaries, detailing allergic symptoms alongside daily location, activities and medication, resulting in 10,130 individual daily entries. The daily ragweed pollen concentration for the children's locations was obtained, alongside daily weather and air pollution. Parents completed a home/lifestyle/medical questionnaire. Generalised Additive Mixed Models established the relationship between pollen concentrations and symptoms, alongside other covariates. Eye symptoms were associated with mean daily pollen concentration over four days (day of symptoms plus 3 previous days); 61 grains/m 3 /day (95%CI: 45, 100) was j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / s c i t o t e n v the threshold at which 50% of children reported symptoms. Nasal symptoms were associated with mean daily pollen concentration over 12 days (day of symptoms plus 11 previous days); the threshold for 50% of children reporting symptoms was 40 grains/m 3 /day (95%CI: 24, 87). Lung symptoms showed a relationship with mean daily pollen concentration over 19 days (day of symptoms plus 18 previous days), with a threshold of 71 grains/m 3 /day (95%CI: 59, 88). Taking medication on the day of symptoms showed higher odds, suggesting responsive behaviour. Taking medication on the day prior to symptoms showed lower odds of reporting, indicating preventative behaviour. Different symptoms in children demonstrate varying dose-response relationships with ragweed pollen concentrations. Each symptom type responded to pollen exposure over different time periods. Using medication prior to symptoms can reduce symptom presence. These findings can be used to better manage paediatric ragweed allergy symptoms.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0c6dc85be3adc3dc14074db7b044f1ec" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996273,"asset_id":40711246,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996273/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711246"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711246"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711246; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711245"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711245/Modifiable_Risk_Factors_for_Common_Ragweed_Ambrosia_artemisiifolia_Allergy_and_Disease_in_Children_A_Case_Control_Study"><img alt="Research paper thumbnail of Modifiable Risk Factors for Common Ragweed (Ambrosia artemisiifolia) Allergy and Disease in Children: A Case-Control Study" class="work-thumbnail" src="https://attachments.academia-assets.com/60996257/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711245/Modifiable_Risk_Factors_for_Common_Ragweed_Ambrosia_artemisiifolia_Allergy_and_Disease_in_Children_A_Case_Control_Study">Modifiable Risk Factors for Common Ragweed (Ambrosia artemisiifolia) Allergy and Disease in Children: A Case-Control Study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Ragweed allergy is a major public health concern. Within Europe, ragweed is an introduced species...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Ragweed allergy is a major public health concern. Within Europe, ragweed is an introduced species and research has indicated that the amounts of ragweed pollen are likely to increase over Europe due to climate change, with corresponding increases in ragweed allergy. To address this threat, improving our understanding of predisposing factors for allergic sensitisation to ragweed and disease is necessary, specifically focusing upon factors that are potentially modifiable (i.e., environmental). In this study, a total of 4013 children aged 2-13 years were recruited across Croatia to undergo skin prick tests to determine sensitisation to ragweed and other aeroallergens. A parental questionnaire collected home environment, lifestyle, family and personal medical history, and socioeconomic information. Environmental variables were obtained using Geographical Information Systems and data from nearby pollen, weather, and air pollution stations. Logistic regression was performed (clustered on school) focusing on risk factors for allergic sensitisation and disease. Ragweed sensitisation was strongly associated with ragweed pollen at levels over 5000 grains m -3 year −1 and, above these levels, the risk of sensitisation was 12-16 times greater than in low pollen areas with about 400 grains m -3 year −1 . Genetic factors were strongly associated with sensitisation but nearly all potentially modifiable factors were insignificant. This included measures of local land use and proximity to potential sources of ragweed pollen. Rural residence was protective (odds ratio (OR) 0.73, 95% confidence interval (CI) 0.55-0.98), but the factors underlying this association were unclear. Being sensitised to ragweed doubled (OR 2.17, 95% CI 1.59-2.96) the risk of rhinoconjunctivitis. No other potentially modifiable risk factors were associated with rhinoconjunctivitis. Ragweed sensitisation was strongly associated with ragweed pollen, and sensitisation was significantly associated with rhinoconjunctivitis. Apart from ragweed pollen levels, few other potentially modifiable factors were significantly associated with ragweed sensitisation. Hence, strategies to lower the risk of sensitisation should focus upon ragweed control.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f83cc3c0d4d672edd9a0c6b3f0ff3ceb" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996257,"asset_id":40711245,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996257/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711245"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711245"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711245; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711245]").text(description); $(".js-view-count[data-work-id=40711245]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711245; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711245']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "f83cc3c0d4d672edd9a0c6b3f0ff3ceb" } } $('.js-work-strip[data-work-id=40711245]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711245,"title":"Modifiable Risk Factors for Common Ragweed (Ambrosia artemisiifolia) Allergy and Disease in Children: A Case-Control Study","internal_url":"https://www.academia.edu/40711245/Modifiable_Risk_Factors_for_Common_Ragweed_Ambrosia_artemisiifolia_Allergy_and_Disease_in_Children_A_Case_Control_Study","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996257,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996257/thumbnails/1.jpg","file_name":"International-journal-of-environmental-research-and-public-health20191023-10684-5vhno7.pdf","download_url":"https://www.academia.edu/attachments/60996257/download_file","bulk_download_file_name":"Modifiable_Risk_Factors_for_Common_Ragwe.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996257/International-journal-of-environmental-research-and-public-health20191023-10684-5vhno7-libre.pdf?1571848301=\u0026response-content-disposition=attachment%3B+filename%3DModifiable_Risk_Factors_for_Common_Ragwe.pdf\u0026Expires=1740509202\u0026Signature=FH3917sjZfsIhUhoxsDwzypJuS7f5MtnAIT~ziGjNv~ZJrnk2gRe0LJJE28Moy3RK822Iy~wH4Gda4t358o5d2aYaFJveU9ouo9lbEONc4nwDx-WIBr3JbhAH2MJJGxZq~QlOCGZfkIzJx8MwQdVFJTwKVin6AIA9r2PXS1nFw2RDZ-qMtqvQtE2r2vFN6-4bCGfUiGLC6~va8qg35C8Yz9Wp4GlgDJpVekeQWegRT2sm44k4L8ktNyxxtUpHtHJxyi-zH-rnpGwcpKqkQsawRWxMD4tBiSM7ybi54vTQL77oLJ4dGNyZtBa0oM4rHnVTJsuvdp2Q1h52GSIRRPJ~w__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711244"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711244/Exploring_Campylobacter_seasonality_across_Europe_using_The_European_Surveillance_System_TESSy_2008_to_2016"><img alt="Research paper thumbnail of Exploring Campylobacter seasonality across Europe using The European Surveillance System (TESSy), 2008 to 2016" class="work-thumbnail" src="https://attachments.academia-assets.com/60996254/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711244/Exploring_Campylobacter_seasonality_across_Europe_using_The_European_Surveillance_System_TESSy_2008_to_2016">Exploring Campylobacter seasonality across Europe using The European Surveillance System (TESSy), 2008 to 2016</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Campylobacteriosis is the most commonly reported food-borne infection in the European...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Campylobacteriosis is the most commonly reported food-borne infection in the European Union, with an annual number of cases estimated at around 9 million. In many countries, campylobacteriosis has a striking seasonal peak during early/ mid-summer. In the early 2000s, several publications reported on campylobacteriosis seasonality across Europe and associations with temperature and precipitation. Subsequently, many European countries have introduced new measures against this foodborne disease. Aim: To examine how the seasonality of campylobacteriosis varied across Europe from 2008-16, to explore associations with temperature and precipitation, and to compare these results with previous studies. We also sought to assess the utility of the European Surveillance System TESSy for cross-European seasonal analysis of campylobacteriosis. Methods: Ward's Minimum Variance Clustering was used to group countries with similar seasonal patterns of campylobacteriosis. A two-stage multivariate meta-analysis methodology was used to explore associations with temperature and precipitation. Results: Nordic countries had a pronounced seasonal campylobacteriosis peak in mid-to late summer (weeks 29-32), while most other European countries had a less pronounced peak earlier in the year. The United Kingdom, Ireland, Hungary and Slovakia had a slightly earlier peak (week 24). Campylobacteriosis cases were positively associated with temperature and, to a lesser degree, precipitation. Conclusion: Across Europe, the strength and timing of campylobacteriosis peaks have remained similar to those observed previously. In addition, TESSy is a useful resource for cross-European seasonal analysis of infectious diseases such as campylobacteriosis, but its utility depends upon each country's reporting infrastructure.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="b2d26c6581e8f4202a69548a07ec3173" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996254,"asset_id":40711244,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996254/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711244"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711244"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711244; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711244]").text(description); $(".js-view-count[data-work-id=40711244]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711244; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711244']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "b2d26c6581e8f4202a69548a07ec3173" } } $('.js-work-strip[data-work-id=40711244]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711244,"title":"Exploring Campylobacter seasonality across Europe using The European Surveillance System (TESSy), 2008 to 2016","internal_url":"https://www.academia.edu/40711244/Exploring_Campylobacter_seasonality_across_Europe_using_The_European_Surveillance_System_TESSy_2008_to_2016","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996254,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996254/thumbnails/1.jpg","file_name":"Eurosurveillance20191023-86485-126f7u7.pdf","download_url":"https://www.academia.edu/attachments/60996254/download_file","bulk_download_file_name":"Exploring_Campylobacter_seasonality_acro.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996254/Eurosurveillance20191023-86485-126f7u7-libre.pdf?1571848298=\u0026response-content-disposition=attachment%3B+filename%3DExploring_Campylobacter_seasonality_acro.pdf\u0026Expires=1740571026\u0026Signature=Y6bXEbV0TGFj3k3iwO0sA-mAZv2~cGy5BZsDVvcv27KSPtY-WfAlxVIF-4WIvdE-kQcA~-3wpH3q3Lj~co3j1QIDf6JBi4ySnKUKB-1RayMd-V2lIhiu3hQx7wjqGvXlH0qVBGA75pIKJ7yKneKx-A8smmUM37dEkiPzJ0hkvomDMi-NbGYx8Hwsedknttag1W71Vq8dA9vNrMmbJUWm207pRU~8~32H7xkgaWs9zUjCkeqTVoepfzT2KuvlX-IUBL6sI2C4lg8sycVhmGGEC5QhJeTyIr-p18xY7GaU1gqyOy8RtKo~UajphVnidAPOQFySSNe2N9i34cJtt2TFiQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711243"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711243/Climate_human_behaviour_or_environment_individual_based_modelling_of_Campylobacter_seasonality_and_strategies_to_reduce_disease_burden"><img alt="Research paper thumbnail of Climate, human behaviour or environment: individual-based modelling of Campylobacter seasonality and strategies to reduce disease burden" class="work-thumbnail" src="https://attachments.academia-assets.com/60996252/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711243/Climate_human_behaviour_or_environment_individual_based_modelling_of_Campylobacter_seasonality_and_strategies_to_reduce_disease_burden">Climate, human behaviour or environment: individual-based modelling of Campylobacter seasonality and strategies to reduce disease burden</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/SandersonRoy">Roy Sanderson</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: With over 800 million cases globally, campylobacteriosis is a major cause of food bor...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: With over 800 million cases globally, campylobacteriosis is a major cause of food borne disease. In temperate climates incidence is highly seasonal but the underlying mechanisms are poorly understood, making human disease control difficult. We hypothesised that observed disease patterns reflect complex interactions between weather, patterns of human risk behaviour, immune status and level of food contamination. Only by understanding these can we find effective interventions. Methods: We analysed trends in human Campylobacter cases in NE England from 2004 to 2009, investigating the associations between different risk factors and disease using time-series models. We then developed an individual-based (IB) model of risk behaviour, human immunological responses to infection and environmental contamination driven by weather and land use. We parameterised the IB model for NE England and compared outputs to observed numbers of reported cases each month in the population in 2004-2009. Finally, we used it to investigate different community level disease reduction strategies. Results: Risk behaviours like countryside visits (t = 3.665, P < 0.001 and t = − 2.187, P = 0.029 for temperature and rainfall respectively), and consumption of barbecued food were strongly associated with weather, (t = 3.219, P = 0.002 and t = 2.015, P = 0.045 for weekly average temperature and average maximum temperature respectively) and also rain (t = 2.254, P = 0.02527). This suggests that the effect of weather was indirect, acting through changes in risk behaviour. The seasonal pattern of cases predicted by the IB model was significantly related to observed patterns (r = 0.72, P < 0.001) indicating that simulating risk behaviour could produce the observed seasonal patterns of cases. A vaccination strategy providing short-term immunity was more effective than educational interventions to modify human risk behaviour. Extending immunity to 1 year from 20 days reduced disease burden by an order of magnitude (from 2412-2414 to 203-309 cases per 50,000 person-years). Conclusions: This is the first interdisciplinary study to integrate environment, risk behaviour, socio-demographics and immunology to model Campylobacter infection, including pathways to mitigation. We conclude that vaccination is likely to be the best route for intervening against campylobacteriosis despite the technical problems associated</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6a9c1a49052f91ec979fa17cb1104cf0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996252,"asset_id":40711243,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996252/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711243"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711243"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711243; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711242"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711242/Climate_Change_and_Water_Related_Infectious_Diseases"><img alt="Research paper thumbnail of Climate Change and Water-Related Infectious Diseases" class="work-thumbnail" src="https://attachments.academia-assets.com/60996250/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711242/Climate_Change_and_Water_Related_Infectious_Diseases">Climate Change and Water-Related Infectious Diseases</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/CHeaviside">Clare Heaviside</a></span></div><div class="wp-workCard_item"><span>atmosphere </span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Water-related, including waterborne, diseases remain important sources of morbidity a...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Water-related, including waterborne, diseases remain important sources of morbidity and mortality worldwide, but particularly in developing countries. The potential for changes in disease associated with predicted anthropogenic climate changes make water-related diseases a target for prevention. Methods: We provide an overview of evidence on potential future changes in water-related disease associated with climate change. Results: A number of pathogens are likely to present risks to public health, including cholera, typhoid, dysentery, leptospirosis, diarrhoeal diseases and harmful algal blooms (HABS). The risks are greatest where the climate effects drive population movements, conflict and disruption, and where drinking water supply infrastructure is poor. The quality of evidence for water-related disease has been documented. Conclusions: We highlight the need to maintain and develop timely surveillance and rapid epidemiological responses to outbreaks and emergence of new waterborne pathogens in all countries. While the main burden of waterborne diseases is in developing countries, there needs to be both technical and financial mechanisms to ensure adequate quantities of good quality water, sewage disposal and hygiene for all. This will be essential in preventing excess morbidity and mortality in areas that will suffer from substantial changes in climate in the future.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9c636a842ea08f2346b4cee52afc7ca0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996250,"asset_id":40711242,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996250/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711242"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711242"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711242; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40711242]").text(description); $(".js-view-count[data-work-id=40711242]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40711242; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40711242']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40711194"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40711194/A_spatial_and_temporal_analysis_of_risk_factors_associated_with_sporadic_Shiga_toxin_producing_Escherichia_coli_O157_infection_in_England_between_2009_and_2015"><img alt="Research paper thumbnail of A spatial and temporal analysis of risk factors associated with sporadic Shiga toxin-producing Escherichia coli O157 infection in England between 2009 and 2015" class="work-thumbnail" src="https://attachments.academia-assets.com/60996212/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40711194/A_spatial_and_temporal_analysis_of_risk_factors_associated_with_sporadic_Shiga_toxin_producing_Escherichia_coli_O157_infection_in_England_between_2009_and_2015">A spatial and temporal analysis of risk factors associated with sporadic Shiga toxin-producing Escherichia coli O157 infection in England between 2009 and 2015</a></div><div class="wp-workCard_item"><span>Epidemiology and Infection</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Rural residence, presence of private water supplies and proximity to high densities of farmed ani...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Rural residence, presence of private water supplies and proximity to high densities of farmed animals is associated with increased risk of STEC O157 infection in England. Cite this article: Elson R, Grace K, Vivancos R, Jenkins C, Adak GK, O'Brien SJ, Lake IR (2018). A spatial and temporal analysis of risk factors associated with sporadic Shiga toxin-producing Escherichia coli O157 infection in England between Abstract Infection with STEC O157 is relatively rare but has potentially serious sequelae, particularly for children. Large outbreaks have prompted considerable efforts designed to reduce transmission primarily from food and direct animal contact. Despite these interventions, numbers of infections have remained constant for many years and the mechanisms leading to many sporadic infections remain unclear. Here, we show that two-thirds of all cases reported in England between 2009 and 2015 were sporadic. Crude rates of infection differed geographically and were highest in rural areas during the summer months. Living in rural areas with high densities of cattle, sheep or pigs and those served by private water supplies were associated with increased risk. Living in an area of lower deprivation contributed to increased risk but this appeared to be associated with reported travel abroad. Fresh water coverage and residential proximity to the coast were not risk factors. To reduce the overall burden of infection in England, interventions designed to reduce the number of sporadic infections with STEC should focus on the residents of rural areas with high densities of livestock and the effective management of non-municipal water supplies. The role of sheep as a reservoir and potential source of infection in humans should not be overlooked.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="194987b93ff6dc54f8a84f9136b5b1fa" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60996212,"asset_id":40711194,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60996212/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40711194"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40711194"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40711194; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "194987b93ff6dc54f8a84f9136b5b1fa" } } $('.js-work-strip[data-work-id=40711194]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":40711194,"title":"A spatial and temporal analysis of risk factors associated with sporadic Shiga toxin-producing Escherichia coli O157 infection in England between 2009 and 2015","internal_url":"https://www.academia.edu/40711194/A_spatial_and_temporal_analysis_of_risk_factors_associated_with_sporadic_Shiga_toxin_producing_Escherichia_coli_O157_infection_in_England_between_2009_and_2015","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":60996212,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/60996212/thumbnails/1.jpg","file_name":"Epidemiology-and-Infection20191023-111636-1nhthv6.pdf","download_url":"https://www.academia.edu/attachments/60996212/download_file","bulk_download_file_name":"A_spatial_and_temporal_analysis_of_risk.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/60996212/Epidemiology-and-Infection20191023-111636-1nhthv6-libre.pdf?1571847885=\u0026response-content-disposition=attachment%3B+filename%3DA_spatial_and_temporal_analysis_of_risk.pdf\u0026Expires=1740571026\u0026Signature=QR6bqZriQFM9ghmegHuRFmaFy~u-PIpdLKFmWsOzJ3SX4ekO7UOkOa4aYxsUTbR8zyfaIyiggiapEdYxsgvc2jRGKZzlezGs4MkbHCAHTFPR6ytgax~~RWwyUIdq1c3e5E2U5seihKlQ6IZtZzogfbAPJPV0OWtVgHxGWFmb-F0e08hMCK~ijvXsWUv9PnWuMdxIj6bXdvDAIITCVoOzFiL8SgDnZKWycQ8Vb32gggnebzJHU0EDtuxnoaKxTEbh8De4BBgMR8qrHL51v-I9B6iBe4SPqEn-jmbz4-nTefBu9wHfFVt6RaIEVZL~M4zRxElZELwBorGOgZE9z8i6Og__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="40679707"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/40679707/Limiting_global_mean_temperature_increase_to_1_5_2_C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America"><img alt="Research paper thumbnail of Limiting global-mean temperature increase to 1.5-2 °C could reduce the incidence and spatial spread of dengue fever in Latin America" class="work-thumbnail" src="https://attachments.academia-assets.com/60961561/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/40679707/Limiting_global_mean_temperature_increase_to_1_5_2_C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America">Limiting global-mean temperature increase to 1.5-2 °C could reduce the incidence and spatial spread of dengue fever in Latin America</a></div><div class="wp-workCard_item"><span>Proceedings of the National Academy of Sciences</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The Paris Climate Agreement aims to hold global-mean temperature well below 2 °C and to pursue ef...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The Paris Climate Agreement aims to hold global-mean temperature well below 2 °C and to pursue efforts to limit it to 1.5 °C above preindustrial levels. While it is recognized that there are benefits for human health in limiting global warming to 1.5 °C, the magnitude with which those societal benefits will be accrued remains unquantified. Crucial to public health preparedness and response is the understanding and quantification of such impacts at different levels of warming. Using dengue in Latin America as a study case, a climate-driven dengue generalized additive mixed model was developed to predict global warming impacts using five different global circulation models, all scaled to represent multiple global-mean temperature assumptions. We show that policies to limit global warming to 2 °C could reduce dengue cases by about 2.8 (0.8–7.4) million cases per year by the end of the century compared with a no-policy scenario that warms by 3.7 °C. Limiting warming further to 1.5 °C produces an additional drop in cases of about 0.5 (0.2–1.1) million per year. Furthermore, we found that by limiting global warming we can limit the expansion of the disease toward areas where incidence is currently low. We anticipate our study to be a starting point for more comprehensive studies incorporating socioeconomic scenarios and how they may further impact dengue incidence. Our results demonstrate that although future climate change may amplify dengue transmission in the region, impacts may be avoided by constraining the level of warming.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="26d2a0f1bcca7a050d16433ef661ae70" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":60961561,"asset_id":40679707,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/60961561/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="40679707"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="40679707"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 40679707; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=40679707]").text(description); $(".js-view-count[data-work-id=40679707]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 40679707; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='40679707']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="38013411"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/38013411/Climate_Change_Foodborne_Pathogens_and_Illness_in_Higher_Income_Countries"><img alt="Research paper thumbnail of Climate Change, Foodborne Pathogens and Illness in Higher-Income Countries" class="work-thumbnail" src="https://attachments.academia-assets.com/58033996/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/38013411/Climate_Change_Foodborne_Pathogens_and_Illness_in_Higher_Income_Countries">Climate Change, Foodborne Pathogens and Illness in Higher-Income Countries</a></div><div class="wp-workCard_item"><span>Current Environmental Health Reports</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Purpose of Review We present a review of the likely consequences of climate change for foodborne ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Purpose of Review We present a review of the likely consequences of climate change for foodborne pathogens and associated human illness in higher-income countries. Recent Findings The relationships between climate and food are complex and hence the impacts of climate change uncertain. This makes it difficult to know which foodborne pathogens will be most affected, what the specific effects will be, and on what timescales changes might occur. Hence, a focus upon current capacity and adaptation potential against foodborne pathogens is essential. We highlight a number of developments that may enhance preparedness for climate change. These include the following:</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="59179cb35bbd18a3a22918ad744c8740" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":58033996,"asset_id":38013411,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/58033996/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="38013411"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="38013411"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 38013411; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=38013411]").text(description); $(".js-view-count[data-work-id=38013411]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 38013411; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='38013411']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "59179cb35bbd18a3a22918ad744c8740" } } $('.js-work-strip[data-work-id=38013411]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":38013411,"title":"Climate Change, Foodborne Pathogens and Illness in Higher-Income Countries","internal_url":"https://www.academia.edu/38013411/Climate_Change_Foodborne_Pathogens_and_Illness_in_Higher_Income_Countries","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":58033996,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/58033996/thumbnails/1.jpg","file_name":"lake_et_al_2018_current_env_health_reports.pdf","download_url":"https://www.academia.edu/attachments/58033996/download_file","bulk_download_file_name":"Climate_Change_Foodborne_Pathogens_and_I.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/58033996/lake_et_al_2018_current_env_health_reports-libre.pdf?1545295965=\u0026response-content-disposition=attachment%3B+filename%3DClimate_Change_Foodborne_Pathogens_and_I.pdf\u0026Expires=1740571026\u0026Signature=eJ00JeIZkQQHGyojsHeQCmHIoAyewSynFnUza1ZVitqHXYpgMmGDDheBwKAPGV8NMPtTebWztznRE4Ob96MaprnlXAe-7dOdE-bFmZXhAPXxyI8A16YOspxkElKntMvHpJU15Lw1L4HKA77h2IwPYBr34xphGH02o42QmId6L0STpAEdanLpV9hLK2U7LGjhlIazyizT2beXMBquR09Gnkdbp2fCyizEEz2h4cBsPtN4RAcVZ5yzc9O05kB~o3SHrbOmBZfHCzxuFrMPvaUSBhmxA6TDiPAql0vdGXM8duL1yxB~yL2P5rx9U~L~ojReExTQN6ueDiBcZqQ~IRE-Hg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="36869340"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/36869340/A_methodological_framework_for_the_evaluation_of_syndromic_surveillance_systems_a_case_study_of_England"><img alt="Research paper thumbnail of A methodological framework for the evaluation of syndromic surveillance systems: a case study of England" class="work-thumbnail" src="https://attachments.academia-assets.com/56823807/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/36869340/A_methodological_framework_for_the_evaluation_of_syndromic_surveillance_systems_a_case_study_of_England">A methodological framework for the evaluation of syndromic surveillance systems: a case study of England</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Syndromic surveillance complements traditional public health surveillance by collecti...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect. Methods: We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of detection to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis. Results: Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different outbreak types with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings. Conclusions: The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d89fc848507498965caf780c50a2dfdc" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":56823807,"asset_id":36869340,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/56823807/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="36869340"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="36869340"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 36869340; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=36869340]").text(description); $(".js-view-count[data-work-id=36869340]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 36869340; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='36869340']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "d89fc848507498965caf780c50a2dfdc" } } $('.js-work-strip[data-work-id=36869340]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":36869340,"title":"A methodological framework for the evaluation of syndromic surveillance systems: a case study of England","internal_url":"https://www.academia.edu/36869340/A_methodological_framework_for_the_evaluation_of_syndromic_surveillance_systems_a_case_study_of_England","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":56823807,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/56823807/thumbnails/1.jpg","file_name":"colon-gonzalez_et_al_2018_bmc_public_health.pdf","download_url":"https://www.academia.edu/attachments/56823807/download_file","bulk_download_file_name":"A_methodological_framework_for_the_evalu.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/56823807/colon-gonzalez_et_al_2018_bmc_public_health-libre.pdf?1529411065=\u0026response-content-disposition=attachment%3B+filename%3DA_methodological_framework_for_the_evalu.pdf\u0026Expires=1740509202\u0026Signature=PXUoCgS4rWh-T2lt9HH7eKfoNSnuWVUOePZcjKQqXeUFmsSIJRWAcGnoHbxgqyl1YbZqKSUY18f-UDs8DsxoK8w-Jy4ZdJwvsF1NOXYsvIpUrSAqGMrw-cZq98cqbq2YtdKtWOvcZE-mpFWRs7JQXLQTX8CrS2ZJ~TxvaL2ggZyhVUoS3QMuSpRFsD0W0DPEmXY4ggKjISuicLKd6ZTcGvtDvi~Qaiyva639etXKFt8SZKWOPXhLRNFcbmSBZgd~tr3nd-wzBGSGsMzk1GxF7UEZj6ywD4tRtfms7BvJzBHM1gN3WEnt~yn25ofoVcREQrLXRTvP4U7~~4~LQEJbtw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="36869327"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/36869327/The_influence_of_a_major_sporting_event_upon_emergency_department_attendances_A_retrospective_cross_national_European_study"><img alt="Research paper thumbnail of The influence of a major sporting event upon emergency department attendances; A retrospective cross-national European study" class="work-thumbnail" src="https://attachments.academia-assets.com/56823791/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/36869327/The_influence_of_a_major_sporting_event_upon_emergency_department_attendances_A_retrospective_cross_national_European_study">The influence of a major sporting event upon emergency department attendances; A retrospective cross-national European study</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/AlexElliot4">Alex Elliot</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Major sporting events may influence attendance levels at hospital emergency departments (ED). Pre...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Major sporting events may influence attendance levels at hospital emergency departments (ED). Previous research has focussed on the impact of single games, or wins/losses for specific teams/countries, limiting wider generalisations. Here we explore the impact of the Euro 2016 football championships on ED attendances across four participating nations (England, France, Northern Ireland, Wales), using a single methodology. Match days were found to have no significant impact upon daily ED attendances levels. Focussing upon hourly attendances , ED attendances across all countries in the four hour pre-match period were statistically significantly lower than would be expected (OR 0.97, 95% CI 0.94–0.99) and further reduced during matches (OR 0.94, 95% CI 0.91–0.97). In the 4 hour post-match period there was no significant increase in attendances (OR 1.01, 95% CI 0.99–1.04). However, these impacts were highly variable between individual matches: for example in the 4 hour period following the final, involving France, the number of ED attendances in France increased significantly (OR 1.27, 95% CI 1.13–1.42). Overall our results indicate relatively small impacts of major sporting events upon ED attendances. The heterogeneity observed makes it difficult for health providers to predict how major sporting events may affect ED attendances but supports the future development of compatible systems in different countries to support cross-border public health surveillance.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="b3a42907f1e42519e8c30d521532f399" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":56823791,"asset_id":36869327,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/56823791/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="36869327"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="36869327"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 36869327; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="36741360"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/36741360/Limiting_global_mean_temperature_increase_to_1_5_2C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America"><img alt="Research paper thumbnail of Limiting global-mean temperature increase to 1.5–2C could reduce the incidence and spatial spread of dengue fever in Latin America" class="work-thumbnail" src="https://attachments.academia-assets.com/56684820/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/36741360/Limiting_global_mean_temperature_increase_to_1_5_2C_could_reduce_the_incidence_and_spatial_spread_of_dengue_fever_in_Latin_America">Limiting global-mean temperature increase to 1.5–2C could reduce the incidence and spatial spread of dengue fever in Latin America</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/CPeres">Carlos A Peres</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The Paris Climate Agreement aims to hold global-mean temperature well below 2 • C and to pursue e...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The Paris Climate Agreement aims to hold global-mean temperature well below 2 • C and to pursue efforts to limit it to 1.5 • C above preindustrial levels. While it is recognized that there are benefits for human health in limiting global warming to 1.5 • C, the magnitude with which those societal benefits will be accrued remains unquantified. Crucial to public health preparedness and response is the understanding and quantification of such impacts at different levels of warming. Using dengue in Latin America as a study case, a climate-driven dengue generalized additive mixed model was developed to predict global warming impacts using five different global circulation models, all scaled to represent multiple global-mean temperature assumptions. We show that policies to limit global warming to 2 • C could reduce dengue cases by about 2.8 (0.8–7.4) million cases per year by the end of the century compared with a no-policy scenario that warms by 3.7 • C. Limiting warming further to 1.5 • C produces an additional drop in cases of about 0.5 (0.2–1.1) million per year. Furthermore, we found that by limiting global warming we can limit the expansion of the disease toward areas where incidence is currently low. We anticipate our study to be a starting point for more comprehensive studies incorporating socioeconomic scenarios and how they may further impact dengue incidence. Our results demonstrate that although future climate change may amplify dengue transmission in the region, impacts may be avoided by constraining the level of warming. climate change impacts | disease modeling | Latin America</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="96c6e254983c2c33476e3f40672f9a87" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":56684820,"asset_id":36741360,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/56684820/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="36741360"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="36741360"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 36741360; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=36741360]").text(description); $(".js-view-count[data-work-id=36741360]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 36741360; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='36741360']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "96c6e254983c2c33476e3f40672f9a87" } } $('.js-work-strip[data-work-id=36741360]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":36741360,"title":"Limiting global-mean temperature increase to 1.5–2C could reduce the incidence and spatial spread of dengue fever in Latin America","translated_title":"","metadata":{"abstract":"The Paris Climate Agreement aims to hold global-mean temperature well below 2 • C and to pursue efforts to limit it to 1.5 • C above preindustrial levels. While it is recognized that there are benefits for human health in limiting global warming to 1.5 • C, the magnitude with which those societal benefits will be accrued remains unquantified. Crucial to public health preparedness and response is the understanding and quantification of such impacts at different levels of warming. Using dengue in Latin America as a study case, a climate-driven dengue generalized additive mixed model was developed to predict global warming impacts using five different global circulation models, all scaled to represent multiple global-mean temperature assumptions. We show that policies to limit global warming to 2 • C could reduce dengue cases by about 2.8 (0.8–7.4) million cases per year by the end of the century compared with a no-policy scenario that warms by 3.7 • C. Limiting warming further to 1.5 • C produces an additional drop in cases of about 0.5 (0.2–1.1) million per year. 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We anticipate our study to be a starting point for more comprehensive studies incorporating socioeconomic scenarios and how they may further impact dengue incidence. 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Our results demonstrate that although future climate change may amplify dengue transmission in the region, impacts may be avoided by constraining the level of warming. climate change impacts | disease modeling | Latin America","owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":56684820,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/56684820/thumbnails/1.jpg","file_name":"1718945115.full.pdf","download_url":"https://www.academia.edu/attachments/56684820/download_file","bulk_download_file_name":"Limiting_global_mean_temperature_increas.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/56684820/1718945115.full-libre.pdf?1527616032=\u0026response-content-disposition=attachment%3B+filename%3DLimiting_global_mean_temperature_increas.pdf\u0026Expires=1738700426\u0026Signature=J-QbAIMg~4gXMKwLkaveUwmtq2LPH~G8~3vXcxy-2jI2tFN942puMw9U5ZO6zVn9I7ABOEy0Ga3Eapq-YDPXSOloRAHs6KRirUjaTKIotEaNoSHevSKDFf-1LCsWtJp7kyIHXwZbA1E71a9zP5KL6SLwS~bxaLVYxws4sXdkYsR8Gi9sm7-ezOlMGcT6jxZA0yGxSVPob97gNEt4hCRVk6pYjvdX9RX0mhC2loXiSwxbVDDfcNkRDfz6tz8wWiEe63pRl-nIiSSIz2UnVwUh9-veaHbcZ6PcXTCEzNkFCYaZPeG4ZFArkegJiFEl0-sNCtJ~ji92bq~roI30NV9vpg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35032899"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35032899/After_the_epidemic_Zika_virus_projections_for_Latin_America_and_the_Caribbean"><img alt="Research paper thumbnail of After the epidemic: Zika virus projections for Latin America and the Caribbean" class="work-thumbnail" src="https://attachments.academia-assets.com/54895424/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35032899/After_the_epidemic_Zika_virus_projections_for_Latin_America_and_the_Caribbean">After the epidemic: Zika virus projections for Latin America and the Caribbean</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/IainLake">Iain Lake</a>, <a class="" data-click-track="profile-work-strip-authors" href="https://eastanglia.academia.edu/CPeres">Carlos A Peres</a>, and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/FColongonzalez">F. Colon-gonzalez</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Zika is one of the most challenging emergent vector-borne diseases, yet its future public health ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Zika is one of the most challenging emergent vector-borne diseases, yet its future public health impact remains unclear. Zika was of little public health concern until recent reports of its association with congenital syndromes. By 3 August 2017 *217,000 Zika cases and *3,400 cases of associated congenital syndrome were reported in Latin America and the Caribbean. Some modelling exercises suggest that Zika virus infection could become endemic in agreement with recent declarations from the The World Health Organisation.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cebc96ac710b4c64530bb513f4972570" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":54895424,"asset_id":35032899,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/54895424/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35032899"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35032899"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35032899; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35032899]").text(description); $(".js-view-count[data-work-id=35032899]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35032899; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35032899']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "cebc96ac710b4c64530bb513f4972570" } } $('.js-work-strip[data-work-id=35032899]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":35032899,"title":"After the epidemic: Zika virus projections for Latin America and the Caribbean","translated_title":"","metadata":{"abstract":"Zika is one of the most challenging emergent vector-borne diseases, yet its future public health impact remains unclear. 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It uses fab...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper introduces a novel method for sampling pathogens in natural environments.  It uses fabric boot socks worn over walkers’ shoes allowing collection of composite samples over large areas.  Wide area sampling is better suited to studies focussing upon human exposure to pathogens (e.g. recreational walking).  This sampling method is implemented using a Citizen Science approach: groups of three walkers wearing boot socks undertook one of six routes, 40 times over 16 months in the North West (NW) and East Anglian (EA) regions of England.  To validate this methodology we report the successful implementation of this Citizen Science approach, the observation that Campylobacter was detected on 47% of boot socks, and the observation that multiple boot socks from individual walks produced consistent results.  Findings indicate elevated Campylobacter<br /> presence in the livestock dominated NW in comparison to EA (55.8% vs 38.6%).  Seasonal variation in Campylobacter presence was found between regions, with indications of winter peaks in both regions, but a spring peak in NW.  Campylobacter presence on boot socks was negatively associated with ambient temperature (p=0.011) and positively associated with precipitation (p<0.001), results which are consistent with our understanding of Campylobacter survival and the probability of material adhering to boot socks. C. jejuni was the predominant species found, with C. coli largely restricted to the livestock dominated NW.  Source attribution analysis indicated that the potential source of C. jejuni was predominantly sheep in NW and wild birds in EA but did not vary between peak and non-peak periods of human incidence.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9f2a95e3231ccf7de33acd53dd9423de" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":53134521,"asset_id":33023702,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/53134521/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="33023702"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="33023702"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 33023702; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=33023702]").text(description); $(".js-view-count[data-work-id=33023702]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 33023702; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='33023702']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "9f2a95e3231ccf7de33acd53dd9423de" } } $('.js-work-strip[data-work-id=33023702]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":33023702,"title":"A novel sampling method for assessing human-pathogen interactions in the natural environment using boot socks and citizen scientists, with an application to the seasonality of Campylobacter","internal_url":"https://www.academia.edu/33023702/A_novel_sampling_method_for_assessing_human_pathogen_interactions_in_the_natural_environment_using_boot_socks_and_citizen_scientists_with_an_application_to_the_seasonality_of_Campylobacter","owner_id":35244294,"coauthors_can_edit":true,"owner":{"id":35244294,"first_name":"Iain","middle_initials":null,"last_name":"Lake","page_name":"IainLake","domain_name":"eastanglia","created_at":"2015-09-24T08:08:03.917-07:00","display_name":"Iain Lake","url":"https://eastanglia.academia.edu/IainLake"},"attachments":[{"id":53134521,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/53134521/thumbnails/1.jpg","file_name":"Appl._Environ._Microbiol.-2017-Jones-AEM.00162-17.pdf","download_url":"https://www.academia.edu/attachments/53134521/download_file","bulk_download_file_name":"A_novel_sampling_method_for_assessing_hu.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/53134521/Appl._Environ._Microbiol.-2017-Jones-AEM.00162-17-libre.pdf?1494857939=\u0026response-content-disposition=attachment%3B+filename%3DA_novel_sampling_method_for_assessing_hu.pdf\u0026Expires=1740509202\u0026Signature=Kx0dskRr-dGjBays5dIyANv5ln0WOnHhrXqIAVOBcLGi~oo4bJUaTa-XoickdJkylE1L57a7rZaOHfTj~GwR~uNL1QE1FHVeoYyavgPhTQ49kAWx5T31niXOAoYbAyuPwPpI~ACmuic3lLwr~plHEJGlrMY68oCn8Cn0UYkF2LwT3BYo-JVqVcQVCdZkLiR7fw5D9~ExfwUj474teEExqazLDMvTUHPBKbUmG9Qida-JWfhdgWb-5u6u6Xml11cBVsN3D4E8dfEpkUDZC9MUHR5jCyi~EzwMTKj8I2YWfbph46V~MdHD7aWabmRMxQdSWx~hoOWVTt1kRT8ZOSDUZA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="32510948"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/32510948/Climate_Change_and_Future_Pollen_Allergy_in_Europe"><img alt="Research paper thumbnail of Climate Change and Future Pollen Allergy in Europe" class="work-thumbnail" src="https://attachments.academia-assets.com/52695919/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/32510948/Climate_Change_and_Future_Pollen_Allergy_in_Europe">Climate Change and Future Pollen Allergy in Europe</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background : Globally pollen allergy is a major public health problem, but a f undamental unknow...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background<br />: Globally pollen allergy is a major public health problem, but a f<br />undamental <br />unknown is the likely impact of climate change<br />. To our knowledge, this is the first study to <br />quantify the consequences of climate change upon pollen allergy in humans.<br />Objectives<br />: To produce quantitative estimates of <br />the potential impact of climate change upon <br />pollen allergy in humans, focusing upon common ragweed (<br />Ambrosia artemisiifolia<br />) in Europe. <br />Methods:<br />A process-based <br />model estimated <br />the <br />change in ragweed’s range under climate change. <br />A second model simulated current and future ragweed pollen levels. These <br />were translated into <br />health burdens using a dose-response curve generated from a systematic review and current and <br />future population data. Models considered two different suites of regional climate/pollen models, <br />two greenhouse gas emissions scenarios (RCP4.5 and 8.5), and three different plant invasion <br />scenarios. <br />Results<br />: Our primary estimates indicate that sensitization to ragweed will more than double in <br />Europe, from 33 to 77 million people, by 2041-2060. According to our projections, while <br />sensitization will increase in countries with an existing ragweed problem (e.g. Hungary, the <br />Balkans), the greatest proportional increases will occur where sensitization is uncommon (e.g. <br />Germany, Poland, France). Higher pollen concentrations and a longer pollen season may also <br />increase the severity of symptoms. Our model projections are driven predominantly by chan<br />ges <br />in climate (66%), but also are influenced by current trends in the spread of this invasive plant <br />species.  Assumptions about the rate at which ragweed spreads throughout Europe have a large <br />influence upon the results. <br />Conclusions<br />: Our quantitative estimates indicate that ragweed pollen allergy will<br /> become a <br />common health problem across Europe, expanding into areas where it is currently uncommon. <br />Control of ragweed spread may be an important adaptation strategy in response to climate <br />change.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cfc6b0ec44a4532014b27917ee6072e5" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":52695919,"asset_id":32510948,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/52695919/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="32510948"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="32510948"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 32510948; 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