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E, Statistical, nonlinear, and soft matter physics" /> <meta name="citation_author" content="Ming Goung Tang" /> <meta name="twitter:card" content="summary" /> <meta name="twitter:url" content="https://www.academia.edu/97408269/Suppressed_epidemics_in_multirelational_networks" /> <meta name="twitter:title" content="Suppressed epidemics in multirelational networks" /> <meta name="twitter:description" content="A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w_{1} and w_{0} occur with probabilities p and 1-p, respectively. The fraction of infected nodes ρ(p) shows" /> <meta name="twitter:image" content="http://a.academia-assets.com/images/twitter-card.jpeg" /> <meta property="fb:app_id" content="2369844204" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://www.academia.edu/97408269/Suppressed_epidemics_in_multirelational_networks" /> <meta property="og:title" content="Suppressed epidemics in multirelational networks" /> <meta property="og:image" content="http://a.academia-assets.com/images/open-graph-icons/fb-paper.gif" /> <meta property="og:description" content="A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w_{1} and w_{0} occur with probabilities p and 1-p, respectively. The fraction of infected nodes ρ(p) shows" /> <meta property="article:author" content="https://independent.academia.edu/MingGoungTang" /> <meta name="description" content="A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w_{1} and w_{0} occur with probabilities p and 1-p, respectively. The fraction of infected nodes ρ(p) shows" /> <title>(PDF) Suppressed epidemics in multirelational networks | Ming Goung Tang - Academia.edu</title> <link rel="canonical" href="https://www.academia.edu/97408269/Suppressed_epidemics_in_multirelational_networks" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "single_work", 'action': "show", 'controller_action': 'single_work#show', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script> var $controller_name = 'single_work'; var $action_name = "show"; var $rails_env = 'production'; var $app_rev = '49879c2402910372f4abc62630a427bbe033d190'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.require = { config: function() { return function() {} } } </script> <script> window.Aedu = window.Aedu || {}; window.Aedu.hit_data = null; window.Aedu.serverRenderTime = new Date(1732474945000); window.Aedu.timeDifference = new Date().getTime() - 1732474945000; </script> <script type="application/ld+json">{"@context":"https://schema.org","@type":"ScholarlyArticle","abstract":"A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w_{1} and w_{0} occur with probabilities p and 1-p, respectively. The fraction of infected nodes ρ(p) shows a nonmonotonic behavior, with ρ drops with p for small p and increases for large p. For small to moderate w_{1}/w_{0} ratios, ρ(p) exhibits a minimum that signifies an optimal suppression. For large w_{1}/w_{0} ratios, the suppression leads to an absorbing phase consisting only of healthy nodes within a range p_{L}≤p≤p_{R}, and an active phase with mixed infected and healthy nodes for p\u0026amp;amp;lt;p_{L} and p\u0026amp;amp;gt;p_{R}. A mean field theory that ignores spatial correlation is shown to give qualitative agreement and capture all the key features. A physical picture that emphasizes the intricate interplay between infections via w_{0} links and within clusters formed by nodes carrying the w_{1} links is presented. The absorbing state at large w_{1}/w...","author":[{"@context":"https://schema.org","@type":"Person","name":"Ming Goung Tang"}],"contributor":[],"dateCreated":"2023-02-23","dateModified":"2023-02-23","datePublished":"2015-01-01","headline":"Suppressed epidemics in multirelational networks","inLanguage":"en","keywords":["Engineering","Mathematics","Physics","Medicine","Probability","Computer Simulation","Mathematical Sciences","Physical sciences","Environment","Epidemics"],"locationCreated":null,"publication":"Physical review. 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window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":97408269,"created_at":"2023-02-23T06:37:00.472-08:00","from_world_paper_id":228256248,"updated_at":"2023-02-23T07:00:02.254-08:00","_data":{"abstract":"A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w_{1} and w_{0} occur with probabilities p and 1-p, respectively. The fraction of infected nodes ρ(p) shows a nonmonotonic behavior, with ρ drops with p for small p and increases for large p. For small to moderate w_{1}/w_{0} ratios, ρ(p) exhibits a minimum that signifies an optimal suppression. For large w_{1}/w_{0} ratios, the suppression leads to an absorbing phase consisting only of healthy nodes within a range p_{L}≤p≤p_{R}, and an active phase with mixed infected and healthy nodes for p\u0026lt;p_{L} and p\u0026gt;p_{R}. A mean field theory that ignores spatial correlation is shown to give qualitative agreement and capture all the key features. A physical picture that emphasizes the intricate interplay between infections via w_{0} links and within clusters formed by nodes carrying the w_{1} links is presented. The absorbing state at large w_{1}/w...","publication_date":"2015,,","publication_name":"Physical review. E, Statistical, nonlinear, and soft matter physics"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Suppressed epidemics in multirelational networks","broadcastable":false,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [252190107]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":99038521,"attachmentType":"pdf"}"><img alt="First page of “Suppressed epidemics in multirelational networks”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/99038521/mini_magick20230223-1-1ey7sdr.png?1677163148" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Suppressed epidemics in multirelational networks</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="252190107" href="https://independent.academia.edu/MingGoungTang"><img alt="Profile image of Ming Goung Tang" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />Ming Goung Tang</a></div><p class="ds-work-card--detail ds2-5-body-sm">2015, Physical review. E, Statistical, nonlinear, and soft matter physics</p><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w_{1} and w_{0} occur with probabilities p and 1-p, respectively. The fraction of infected nodes ρ(p) shows a nonmonotonic behavior, with ρ drops with p for small p and increases for large p. For small to moderate w_{1}/w_{0} ratios, ρ(p) exhibits a minimum that signifies an optimal suppression. For large w_{1}/w_{0} ratios, the suppression leads to an absorbing phase consisting only of healthy nodes within a range p_{L}≤p≤p_{R}, and an active phase with mixed infected and healthy nodes for p&lt;p_{L} and p&gt;p_{R}. A mean field theory that ignores spatial correlation is shown to give qualitative agreement and capture all the key features. A physical picture that emphasizes the intricate interplay between infections via w_{0} links and within clusters formed by nodes carrying the w_{1} links is presented. The absorbing state at large w_{1}/w...</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":99038521,"attachmentType":"pdf","workUrl":"https://www.academia.edu/97408269/Suppressed_epidemics_in_multirelational_networks"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":99038521,"attachmentType":"pdf","workUrl":"https://www.academia.edu/97408269/Suppressed_epidemics_in_multirelational_networks"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="99038521" data-landing_url="https://www.academia.edu/97408269/Suppressed_epidemics_in_multirelational_networks" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="73135534" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/73135534/Epidemics_in_networks_with_nodal_selfinfection_and_the_epidemic_threshold_Phys">Epidemics in networks with nodal selfinfection and the epidemic threshold,” Phys</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="41342035" href="https://radboud.academia.edu/EricCator">Eric Cator</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2012</p><p class="ds-related-work--abstract ds2-5-body-sm">Since the Susceptible-Infected-Susceptible (SIS) epidemic threshold is not precisely defined in spite of its practical importance, the classical SIS epidemic process has been generalized to the ε−SIS model, where a node possesses a self-infection rate ε, in addition to a link infection rate β and a curing rate δ. 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class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="34686395" href="https://independent.academia.edu/PeterSimon21">Peter Simon</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2018</p><p class="ds-related-work--abstract ds2-5-body-sm">Epidemic propagation is controlled conventionally by vaccination or by quarantine. These methods have been widely applied for different compartmental ODE models of epidemic propagation. When epidemic spread is considered on a network, then it is natural to control the propagation process by changing the network structure. Namely, SI links, connecting a susceptible individual to an infected one, can be deleted. This would lead to a disconnected network, which is not realistic, hence new SS links can be created in order to keep the network well connected. Thus it seems to be promising to drive the process to a target with no infection and a prescribed average degree by deleting SI links and creating SS links in an appropriate way. It was shown previously that this can be done for the pairwise ODE approximation of SIS epidemic propagation. In this paper this is extended to the original stochastic process by using the control signals computed from the ODE approximation.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Control of epidemic propagation on networks by using a mean-field model : Dedicated to Professor László Hatvani on the occasion of his 75th birthday","attachmentId":87422634,"attachmentType":"pdf","work_url":"https://www.academia.edu/81348377/Control_of_epidemic_propagation_on_networks_by_using_a_mean_field_model_Dedicated_to_Professor_L%C3%A1szl%C3%B3_Hatvani_on_the_occasion_of_his_75th_birthday","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/81348377/Control_of_epidemic_propagation_on_networks_by_using_a_mean_field_model_Dedicated_to_Professor_L%C3%A1szl%C3%B3_Hatvani_on_the_occasion_of_his_75th_birthday"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="116374505" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/116374505/Epidemics_in_networks_with_nodal_self_infection_and_the_epidemic_threshold">Epidemics in networks with nodal self-infection and the epidemic threshold</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="41342035" href="https://radboud.academia.edu/EricCator">Eric Cator</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Physical Review E, 2012</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Epidemics in networks with nodal self-infection and the epidemic threshold","attachmentId":112522574,"attachmentType":"pdf","work_url":"https://www.academia.edu/116374505/Epidemics_in_networks_with_nodal_self_infection_and_the_epidemic_threshold","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/116374505/Epidemics_in_networks_with_nodal_self_infection_and_the_epidemic_threshold"><span class="ds2-5-text-link__content">View PDF</span><span 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