Spatial and Temporal Analysis of Dengue Incidence in Manaus, Amazonas, Brazil, 2016-2022

Abstract

ABSTRACT Background: Dengue remains a public health challenge, driven by Aedes aegypti proliferation within complex socio-environmental conditions. Methods: This study investigated the spatiotemporal distribution of dengue in Manaus from 2016 to 2022. Temporal analysis used negative binomial regression adjusted for seasonality. Seasonal and spatial clusters were identified using scan statistics (p < 0.05, 95% CI). A Bayesian spatial model assessed sociodemographic and environmental determinants. Results: Lagged temperature and wind speed showed protective effects. The Bayesian model identified significant associations with population density, vegetation indices (NDVI), sewage infrastructure, and housing types. Conclusions: Integrating climatic and socioeconomic data is essential for intersectoral dengue control strategies.