{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T18:24:29Z","timestamp":1787595869422,"version":"build-2736575974"},"reference-count":53,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background and aims<\/jats:title>\n                    <jats:p>Malaria remains a public health concern in Bangladesh, despite a notable decline in reported cases since 2012 and a brief resurgence in 2014. Aligned with the United Nations Sustainable Development Goal (SDG) 3.3, which targets the elimination of malaria by 2030, Bangladesh has implemented multiple control and prevention strategies. This study assesses the significance of the decline in malaria cases and applies Bayesian hierarchical models to capture spatial dynamics of malaria-related vulnerability, map district-level risk, and inform targeted interventions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A nationwide spatial analysis was conducted using district-level malaria data from the Bangladesh Disaster-related Statistics (BDRS) 2021, which report cumulative counts of \u201cpopulation suffering from malaria due to disaster\u201d for 2015\u20132020. These data were used as a proxy indicator of relative malaria vulnerability. National malaria time-series data were obtained from Bangladesh\u2019s National Strategic Plan for Malaria Elimination (2021\u20132025) published by the Asia Pacific Malaria Elimination Network (APMEN), together with malaria surveillance summaries from the World Malaria Reports (2024,2025) published by the World Health Organization (WHO). District-level rainfall data were obtained from the Bangladesh Water Development Board. Bayesian hierarchical disease mapping models were used to assess spatial dependence and district-level malaria risk. Spatial visualization and autocorrelation analyses (Global Moran\u2019s I, Geary\u2019s C, and Local Moran\u2019s I) were performed using R (version 4.4.0), and Bayesian model estimation was carried out using WinBUGS via Markov Chain Monte Carlo methods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The analysis showed evidence of a trend in decreasing malaria cases by a value of \u22120.691 in the Mann-Kendall trend test. However, spatial analysis revealed significant clustering and geographic heterogeneity. Persistent high-risk clusters were identified in the southeastern hilly regions. Additionally the presence of excess zeros in the data justified the use of zero-inflated models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The findings show significant national decline and offer valuable insights into the geographical variability in malaria-related vulnerability in Bangladesh. Rather than being direct indicators of malaria transmission, the results should be understood as representing relative risk patterns based on data related to disasters. Under current data limitations, these results provide evidence to boost spatially informed malaria control methods and assist geographically focused interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0353483","type":"journal-article","created":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T17:32:27Z","timestamp":1787592747000},"page":"e0353483","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatial Analysis of Malaria in Bangladesh: Insights from Bayesian Disease Mapping Models"],"prefix":"10.1371","volume":"21","author":[{"given":"Ummehani","family":"Mimi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8453-1604","authenticated-orcid":true,"given":"Md. Rezaul","family":"Karim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sultana","family":"Begum","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8615-3484","authenticated-orcid":true,"given":"Khadiza Akter","family":"Eme","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"pone.0353483.ref001","unstructured":"G of B. National strategic plan for malaria elimination and prevention of re-establishment of malaria transmission in Bangladesh 2024-2030 national malarial elimination programme directorate general of health services ministry of health and family welfare government of Bangladesh. Ministry of Health and Family Welfare. https:\/\/share.google\/VEVeeyaVnRidJL3RB"},{"key":"pone.0353483.ref002","unstructured":"International Centre for Diarrhoeal Disease Research. Malaria in Bangladesh - Bangladesh. Accessed 2026 March 7. https:\/\/reliefweb.int\/report\/bangladesh\/malaria-bangladesh"},{"key":"pone.0353483.ref003","unstructured":"Centers for Disease Control and Prevention. Malaria\u2019s impact worldwide. Accessed 2026 March 7. https:\/\/www.cdc.gov\/malaria\/php\/impact\/index.html"},{"issue":"8","key":"pone.0353483.ref004","doi-asserted-by":"crossref","first-page":"2039","DOI":"10.3934\/mbe.2025075","article-title":"Vaccination and combined optimal control measures for malaria prevention and spread mitigation","volume":"22","author":"KA Eme","year":"2025","journal-title":"Math Biosci Eng"},{"key":"pone.0353483.ref005","volume-title":"Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review","author":"A Aswi","year":"2019"},{"issue":"2","key":"pone.0353483.ref006","doi-asserted-by":"crossref","first-page":"123","DOI":"10.24171\/j.phrp.2021.0304","article-title":"Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India","volume":"13","author":"S Chaudhary","year":"2022","journal-title":"Osong Public Health Res Perspect"},{"key":"pone.0353483.ref007","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1186\/1475-2875-13-457","article-title":"Spatio-temporal distribution of malaria and its association with climatic factors and vector-control interventions in two high-risk districts of Nepal","volume":"13","author":"M Dhimal","year":"2014","journal-title":"Malar J"},{"issue":"1","key":"pone.0353483.ref008","article-title":"Spatio-temporal variation of malaria incidence in Sub-Saharan Africa from 2011 to 2020","volume":"3","author":"CJ Chol","year":"2025","journal-title":"Research in Statistics"},{"key":"pone.0353483.ref009","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1186\/1475-2875-8-185","article-title":"Spatial malaria epidemiology in Bangladeshi highlands","volume":"8","author":"U Haque","year":"2009","journal-title":"Malar J"},{"issue":"1","key":"pone.0353483.ref010","doi-asserted-by":"crossref","DOI":"10.1186\/s12936-019-2849-0","article-title":"Knowledge, attitudes, and practices regarding malaria control among the slash and burn cultivators in Rangamati Hill tracts of Bangladesh","volume":"18","author":"A Saha","year":"2019","journal-title":"Malar J"},{"issue":"4","key":"pone.0353483.ref011","doi-asserted-by":"crossref","first-page":"861","DOI":"10.4269\/ajtmh.2010.10-0154","article-title":"Mapping malaria risk in Bangladesh using Bayesian geostatistical models","volume":"83","author":"H Reid","year":"2010","journal-title":"Am J Trop Med Hyg"},{"issue":"1","key":"pone.0353483.ref012","article-title":"Mapping the stability of malaria hotspots in Bangladesh from 2013 to 2016","volume":"17","author":"A No\u00e9","year":"2018","journal-title":"Malar J"},{"key":"pone.0353483.ref013","first-page":"49","article-title":"Climatic determinants and spatial hotspots of malaria incidence in Lama Upazila, Bangladesh (2020-2024)","volume":"10","author":"HA Pulok","year":"2025","journal-title":"Jahangirnagar University Environmental Bulletin"},{"key":"pone.0353483.ref014","unstructured":"Bangladesh Bureau of Statistics. Bangladesh disaster related statistics 2021- climate change and natural disaster perspectives. 2022."},{"key":"pone.0353483.ref015","unstructured":"Bangladesh Water Development Board. Rainfall in Bangladesh; Year-2017 & 2018. 2019."},{"key":"pone.0353483.ref016","unstructured":"Bangladesh Water Development Board. Rainfall in Bangladesh; Year-2019 & 2020. 2021."},{"key":"pone.0353483.ref017","unstructured":"Bangladesh: districts and urban places - population statistics, maps, charts, weather and web information. Accessed 2026 March 7. https:\/\/www.citypopulation.de\/en\/bangladesh\/cities\/"},{"key":"pone.0353483.ref018","unstructured":"World Bank. Population growth (annual %) - Bangladesh. Accessed 2026 March 7. https:\/\/data.worldbank.org\/indicator\/SP.POP.GROW?locations=BD"},{"key":"pone.0353483.ref019","doi-asserted-by":"crossref","unstructured":"Zhao J, Zhang F, Zhao C, Wu G, Wang H, Cao X. The properties and application of poisson distribution. In: Journal of Physics: Conference Series, 2020. https:\/\/doi.org\/10.1088\/1742-6596\/1550\/3\/032109","DOI":"10.1088\/1742-6596\/1550\/3\/032109"},{"key":"pone.0353483.ref020","unstructured":"St. Francis Xavier University. Introduction to probability theory and mathematical statistics. Accessed 2026 March 7. https:\/\/share.google\/XEOcAU7qCsj7b0jAF"},{"issue":"29","key":"pone.0353483.ref021","doi-asserted-by":"crossref","first-page":"5151","DOI":"10.1002\/sim.6293","article-title":"A marginalized zero-inflated Poisson regression model with overall exposure effects","volume":"33","author":"DL Long","year":"2014","journal-title":"Stat Med"},{"key":"pone.0353483.ref022","unstructured":"UCLA-Advanced Research Computing. Zero-inflated poisson regression | R data analysis examples. Accessed 2026 March 7. https:\/\/stats.oarc.ucla.edu\/r\/dae\/zip\/"},{"issue":"1","key":"pone.0353483.ref023","article-title":"Mann-Kendall test - a novel approach for statistical trend analysis","volume":"63","author":"N Kamal","year":"2018","journal-title":"International J Comp Trends Tech"},{"key":"pone.0353483.ref024","unstructured":"Pacific Northwest National Laboratory. Design trend Mann-Kendall. Accessed 2026 March 7. https:\/\/vsp.pnnl.gov\/help\/vsample\/design_trend_mann_kendall.htm"},{"issue":"3","key":"pone.0353483.ref025","doi-asserted-by":"crossref","first-page":"977","DOI":"10.2166\/wcc.2023.508","article-title":"Application of MK trend and test of Sen\u2019s slope estimator to measure impact of climate change on the adoption of conservation agriculture in Ethiopia","volume":"14","author":"H Jiqin","year":"2023","journal-title":"J Water Climate Change"},{"key":"pone.0353483.ref026","unstructured":"Aswad FK, Yousif AA, Ibrahim SA. Trend analysis using Mann-Kendall and Sen\u2019s slope estimator test for annual and monthly rainfall for Sinjar district, Iraq. 2023."},{"key":"pone.0353483.ref027","unstructured":"Awati R, Zola A, Fontecchio M. What is spatial data and how does it work?. Accessed 2026 March 8. https:\/\/www.techtarget.com\/searchdatamanagement\/definition\/spatial-data"},{"key":"pone.0353483.ref028","unstructured":"Loonis V, d Bellefon M-P. Handbook of spatial analysis theory and practical application with R. Insee \u2013 Eurostat. 2018."},{"key":"pone.0353483.ref029","unstructured":"University of Kassel. 3. spatial autocorrelation. Accessed 2026 March 8. https:\/\/share.google\/rrHDWg36l83UcdoJ9"},{"key":"pone.0353483.ref030","doi-asserted-by":"crossref","DOI":"10.1201\/9780429318443","volume-title":"Bayesian modeling of spatio-temporal data with R","author":"SK Sahu","year":"2021"},{"issue":"6","key":"pone.0353483.ref031","doi-asserted-by":"crossref","DOI":"10.1002\/hsr2.2154","article-title":"Dengue fever mapping in Bangladesh: A spatial modeling approach","volume":"7","author":"I Sarker","year":"2024","journal-title":"Health Sci Rep"},{"key":"pone.0353483.ref032","unstructured":"Esri. How High\/Low Clustering (Getis-Ord General G) Works. Accessed 2026 March 8. https:\/\/pro.arcgis.com\/en\/pro-app\/3.4\/tool-reference\/spatial-statistics\/h-how-high-low-clustering-getis-ord-general-g-spat.htm"},{"issue":"2","key":"pone.0353483.ref033","doi-asserted-by":"crossref","first-page":"208","DOI":"10.4236\/ojce.2017.72013","article-title":"A novel hybrid method for measuring the spatial autocorrelation of vehicular crashes: combining Moran\u2019s index and Getis-Ord Gi statistic","volume":"7","author":"A Abdulhafedh","year":"2017","journal-title":"Open J Civil Engineering"},{"issue":"3","key":"pone.0353483.ref034","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1111\/j.1538-4632.1992.tb00261.x","article-title":"The analysis of spatial association by use of distance statistics","volume":"24","author":"A Getis","year":"1992","journal-title":"Geographical Analysis"},{"key":"pone.0353483.ref035","volume-title":"Applied Spatial Data Analysis with R","author":"RS Bivand","year":"2008"},{"key":"pone.0353483.ref036","unstructured":"Muse AH. Module VIII Hotspot Analysis. Accessed 2026 March 8."},{"issue":"16","key":"pone.0353483.ref037","doi-asserted-by":"crossref","first-page":"2943","DOI":"10.3390\/rs16162943","article-title":"Application of Getis-Ord Correlation Index (Gi) for burned area detection improvement in Mediterranean Ecosystems (Southern Italy and Sardinia) using Sentinel-2 Data","volume":"16","author":"A Lanorte","year":"2024","journal-title":"Remote Sensing"},{"key":"pone.0353483.ref038","unstructured":"Esr. How Hot Spot Analysis (Getis-Ord Gi*) Works. Accessed 2026 March 8. https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/spatial-statistics\/h-how-hot-spot-analysis-getis-ord-gi-spatial-stati.htm"},{"key":"pone.0353483.ref039","unstructured":"Vidanapathirana ND. A Comparison of spatial clustering assessment methods. Accessed 2026 March 8. https:\/\/scholarcommons.sc.edu\/etd\/6411\/"},{"issue":"2","key":"pone.0353483.ref040","article-title":"Spatial Autocorrelation analysis of CO and NO2 related to forest fire dynamics","volume":"14","author":"H Atalay","year":"2025","journal-title":"ISPRS Int J Geoinf"},{"key":"pone.0353483.ref041","doi-asserted-by":"crossref","unstructured":"Melo C, Melo O, Melo S. bisdep: statistical tools for bivariate spatial dependence analysis. 2025. Accessed 2026 March 8. https:\/\/CRAN.R-project.org\/package=bispdep","DOI":"10.32614\/CRAN.package.bispdep"},{"issue":"1","key":"pone.0353483.ref042","article-title":"A study on spatial association of poor child health outcomes and multidimensional poverty in India","volume":"25","author":"P Das","year":"2025","journal-title":"BMC Public Health"},{"key":"pone.0353483.ref043","volume-title":"Developing a cancer atlas using Bayesian methods: a practical guide for application and interpretation","author":"E Duncan","year":"2024","edition":"2"},{"issue":"3","key":"pone.0353483.ref044","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.sste.2011.10.004","article-title":"A generalized Poisson-gamma model for spatially overdispersed data","volume":"3","author":"T Neyens","year":"2012","journal-title":"Spat Spatiotemporal Epidemiol"},{"key":"pone.0353483.ref045","volume-title":"Spatial statistics for data science: theory and practice with R","author":"a Moraga P a u l","year":"2024"},{"key":"pone.0353483.ref046","article-title":"Discussion of Bayesian models for spatially correlated disease and exposure data","volume-title":"Bayesian Statistics 6","author":"JE Kelsall","year":"1999"},{"key":"pone.0353483.ref047","volume-title":"Bayesian data analysis","author":"A Gelman","year":"2014","edition":"3"},{"issue":"4","key":"pone.0353483.ref048","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1111\/1467-9868.00353","article-title":"Bayesian measures of model complexity and fit","volume":"64","author":"DJ Spiegelhalter","year":"2002","journal-title":"J R Stat Soc Series B Stat Methodol"},{"key":"pone.0353483.ref049","unstructured":"Start Fund Bangladesh. 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