<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/10013044" mdate="2023-04-04 00:00:00"> <author>Meghna Maiti and Utpal Roy</author> <title>Malaria Prone Zones of West Bengal A SpatioTemporal Scenario</title> <pages>71 - 77</pages> <year>2023</year> <volume>17</volume> <number>4</number> <journal>International Journal of Health and Medical Engineering</journal> <ee>https://publications.waset.org/pdf/10013044</ee> <url>https://publications.waset.org/vol/196</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>In India, till today, malaria is considered to be one of the significant infectious diseases. Most of the cases regional geographical factors are the principal elements to let the places a unique identity. The incidence and intensity of infectious diseases are quite common and affect different places differently across the nation. The present study aims to identify spatial clusters of hot spots and cold spots of malaria incidence and their seasonal variation during the three periods of 20122014, 20152017 and 201820 in the state of West Bengal in India. As malaria is a vectorborne disease, numbers of positive test results are to be reported by the laboratories to the Department of Health, West Bengal (through the National Vector Borne Disease Control Programme). Data on blockwise monthly malaria positive cases are collected from Health Management Information System (HMIS), Ministry of Health and Family Welfare, Government of India. Moran&amp;rsquo;s I statistic is performed to assess the spatial autocorrelation of malaria incidence. The spatial statistical analysis mainly Local Indicators of Spatial Autocorrelation (LISA) cluster and Local Geary Cluster are applied to find the spatial clusters of hot spots and cold spots and seasonal variability of malaria incidence over the three periods. The result indicates that the spatial distribution of malaria is clustered during each of the three periods of 20122014, 20152017 and 201820. The analysis shows that in all the cases, highhigh clusters are primarily concentrated in the western (Purulia, Paschim Medinipur districts), central (Maldah, Murshidabad districts) and the northern parts (Jalpaiguri, Kochbihar districts) and lowlow clusters are found in the lower Gangetic plain (centralsouth) mainly and northern parts of West Bengal during the stipulated period. Apart from this seasonal variability interyear variation is also visible. The results from different methods of this study indicate significant variation in the spatial distribution of malaria incidence in West Bengal and high incidence clusters are primarily persistently concentrated over the western part during 20122020 along with a strong seasonal pattern with a peak in rainy and autumn. By applying the different techniques in identifying the different degrees of incidence zones of malaria across West Bengal, some specific pockets or malaria hotspots are marked and identified where the incidence rates are quite harmonious over the different periods. From this analysis, it is clear that malaria is not a disease that is distributed uniformly across the state; some specific pockets are more prone to be affected in particular seasons of each year. Disease ecology and spatial patterns must be the factors in explaining the real factors for the higher incidence of this issue within those affected districts. The further study mainly by applying empirical approach is needed for discerning the strong relationship between communicable disease and other associated affecting factors. </abstract> <index>Open Science Index 196, 2023</index> </article>