Analyzing the Influence of Weather and Socio-Economic Factors on the Spread of Dengue Fever in Countries in the Americas

Dengue fever is a major global health concern, with around four billion people living in at-risk areas. This study applies a Generalized Linear Model (GLM) with a Poisson distribution to examine the influence of weather and socioeconomic factors on dengue fever cases in the Americas. Using K-Means clustering, three representative countries— Brazil, Mexico, and Saint Kitts and Nevis—were selected. Socioeconomic and weather variables from 1980 to 2022 were reduced using Principal Component Analysis (PCA) to address multicollinearity. The GLM was then used to model dengue cases based on these components. Model outputs were compared with actual data to evaluate accuracy and trend alignment. Results show that both weather and socioeconomic factors significantly influence case numbers, with Brazil and Mexico affected by four components each, and Saint Kitts and Nevis by five. These findings can guide country-specific strategies for dengue prevention and control.