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These countries are characterized by a heterogeneous malaria landscape and malaria hotspots. Furthermore, the political unrest in Venezuela has led to significant cross-border population movement. Hence, the aim of this study was to describe spatial patterns and identify significant climatic drivers of malaria transmission along the Venezuela-Brazil-Guyana border, focusing on Bolivar state, Venezuela and Roraima state, Brazil. Malaria case data, stratified by species from 2016 to 2018, were obtained from the Brazilian Malaria Epidemiology Surveillance Information System, the Guyana Vector Borne Diseases Program, the Venezuelan Ministry of Health, and civil society organizations. Spatial autocorrelation in malaria incidence was explored using Getis-Ord (Gi*) statistics. A Poisson regression model was developed with a conditional autoregressive prior structure and posterior parameters were estimated using the Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. There were 685,498 malaria cases during the study period.<jats:italic>Plasmodium vivax<\/jats:italic>was the predominant species (71.7%, 490,861). Malaria hotspots were located in eight municipalities along the Venezuela and Guyana international borders with Brazil.<jats:italic>Plasmodium falciparum<\/jats:italic>increased by 2.6% (95% credible interval [CrI] 2.1%, 2.8%) for one meter increase in altitude, decreased by 1.6% (95% CrI 1.5%, 2.3%) and 0.9% (95% CrI 0.7%, 2.4%) per 1\u00a0cm increase in 6-month lagged precipitation and each 1\u00a0\u00b0C increase of minimum temperature without lag. Each 1\u00a0\u00b0C increase of 1-month lagged maximum temperature increased<jats:italic>P. falciparum<\/jats:italic>by 0.6% (95% CrI 0.4%, 1.9%).<jats:italic>P. vivax<\/jats:italic>cases increased by 1.5% (95% CrI 1.3%, 1.6%) for one meter increase in altitude and decreased by \u00a01.1% (95% CrI 1.0%, 1.2%) and 7.3% (95% CrI 6.7%, 9.7%) for each 1\u00a0cm increase of precipitation lagged at 6-months and 1\u00a0\u00b0C increase in minimum temperature lagged at 6-months. Each 1\u00b0C increase of two-month lagged maximum temperature increased<jats:italic>P. vivax<\/jats:italic>by 1.5% (95% CrI 0.6%, 7.1%). There was no significant residual spatial clustering after accounting for climatic covariates. Malaria hotspots were located along the Venezuela and Guyana international border with Roraima state, Brazil. In addition to population movement, climatic variables were important drivers of malaria transmission in these areas.<\/jats:p>","DOI":"10.1038\/s41598-022-14012-4","type":"journal-article","created":{"date-parts":[[2022,6,29]],"date-time":"2022-06-29T17:03:17Z","timestamp":1656522197000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Spatial patterns and climate drivers of malaria in three border areas of Brazil, Venezuela and Guyana, 2016\u20132018"],"prefix":"10.1038","volume":"12","author":[{"given":"Kinley","family":"Wangdi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erica","family":"Wetzler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Horace","family":"Cox","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paola","family":"Marchesini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leopoldo","family":"Villegas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara","family":"Canavati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,6,29]]},"reference":[{"key":"14012_CR1","unstructured":"WHO. 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