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In this study, the spatial distribution of malaria hotspots was investigated and the significant covariates were identified that are potentially influencing its transmission in India.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>District-wise data on malaria, socio-economic variations, meteorological factors and land-use land-cover changes were used to assess the impact of covariates on the transmission using an ensemble of Random Forest and Poisson regression models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Spatial clusters for annual parasite incidence (API) and annual falciparum incidence (AFI) were observed distinctly in the central and northeastern districts, but additional hotspots for non-AFI transmission were present in the northern districts. The ensemble models suggest that in districts with high malaria transmission, socio-economically marginalized communities with water inaccessibility and not having a mobile phone are among the potentially vulnerable sections of the society. The use of unprotected water source for household consumption is also potentially linked to increased transmission. Mother\u2019s education could reduce malaria transmission, but a substantial proportion of the mothers in high-transmission districts reporting API\u2009&gt;\u20091 did not have any formal or informal education.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Socio-economic development that includes concerted efforts to impart both technical and non-technical education and spreading awareness for better lifestyle choices will help reduce the malaria burden in the country. The clusters of high-burden districts instead of individual districts are recommended as strategic points for implementing targeted interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12936-025-05546-9","type":"journal-article","created":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T13:52:14Z","timestamp":1760449934000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Determinants of malaria transmission in Indian districts in 2018: insights from ensemble models"],"prefix":"10.1186","volume":"24","author":[{"given":"Avik Kumar","family":"Sam","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alisha","family":"Khatoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harish C.","family":"Phuleria","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,10,14]]},"reference":[{"key":"5546_CR1","doi-asserted-by":"publisher","first-page":"963","DOI":"10.1016\/S0140-6736(13)60851-X","volume":"382","author":"LS Tusting","year":"2013","unstructured":"Tusting LS, Willey B, Lucas H, Thompson J, Kafy HT, Smith R, et al. 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