Background: The Amazon biome exhibits complex arboviral transmission dynamics influenced by accelerating deforestation, climate change, and socioeconomic inequities. Objectives/Methods: This study integrates official epidemiological records with socioeconomic, environmental, and climate variables by applying advanced geostatistical methods (Moran’s I, SaTScan, kernel density estimation) combined with principal component analysis and negative binomial regression to assess the spatiotemporal dynamics of dengue incidence and its association with socio-environmental determinants across municipalities in Pará state (eastern Brazilian Amazon) from 2010 to 2024. Results: Dengue incidence showed an overall decline but with marked epidemic peaks in 2010–2012, 2016, and 2024. The spatial analysis revealed significant clustering (Moran’s I = 0.221, p < 0.01), with persistent high-risk hotspots across most of Pará. Of 144 municipalities, 104 exhibited significant dengue risk, while 58 maintained sustained transmission. Negative binomial regression model identified key determinants: illiteracy, low urbanization, reduced GDP, and climate variables. Conclusions: Dengue transmission in the Amazon is driven by synergistic socio-environmental disruptions, necessitating intersectoral policies that bridge public health surveillance, sustainable land-use governance, and poverty alleviation. Priority actions include targeted vector control in high-risk clusters, coupled with integrated deforestation and climate monitoring to predict outbreak risks. The findings emphasize the urgency of implementing multisectoral interventions tailored to the territorial and socio-environmental complexities of vulnerable Amazonian regions for effective dengue control.
Silva et al. (2025) studied this question.
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