Temporal Analysis and Prediction of Malaria Dynamics Using Meteorological Data in Southeastern of Senegal

Abstract

Malaria continues to be a major public health challenge in Senegal. The intricate links between climate and malaria complicate the development of effective control strategies, despite ongoing efforts by the National Malaria Control Program and international partners. This study investigates the relationship between weekly malaria cases and meteorological factors in four districts of Senegal (Kédougou, Salémata, Saraya, and Dianké Makha) using Generalized Additive Models. Data were sourced from \textit{DHSI2} (malaria cases) and \textit{NASA GIOVANNI} (meteorological data). Principal component analysis identified key explanatory variables, with climate regimes determined via Hierarchical Ascending Classification. Results show that the first component's two-week lag significantly reduces malaria risk at high values. The second component exhibits a nonlinear relationship: moderate levels are protective while very high values increase risk. The third component shows that a 15-week lag, moderate to high precipitation provides a protective effect (50-70\% risk reduction), while excessive precipitation (80-100th percentiles) increases malaria risk by promoting mosquito proliferation.