Quantifying the Lagged Effects of Climate Variables on Malaria Risk in Eastern Uganda

Climate change is anticipated to significantly affect malaria transmission. Previous research has shown lagged, nonlinear associations between climate variables and malaria risk, with highly context-specific exposure-lag-response relationship. Using weekly malaria case data collected between July 2018 and February 2023 from a health facility within the Iganga-Mayuge Health and Demographic Surveillance System site in Uganda and remotely sensed temperature and rainfall data, we quantified the associations between temperature and rainfall and risk of developing symptomatic malaria using a distributed lag nonlinear model. Furthermore, we investigated whether these associations varied by age group. Our analysis revealed a lag of 2 to 8 weeks between exposure to rainfall exceeding 200 mm/week and a significant increase in the risk of developing symptomatic malaria; no statistically significant lagged association was found with temperature. Additionally, the risk in school-aged children was less sensitive to climate variables compared with the other age groups. Rainfall was found to be associated with an increased risk at a lag of 2 months at the study site. This finding provides valuable guidance for local health authorities in determining the optimal timing for preventive interventions and in preparing for the anticipated rise in demand for malaria case management. The observed variations in the risk of developing symptomatic malaria across different age groups highlight the need for targeted interventions tailored to specific populations. Overall, the significant associations between climate variables and malaria risk underscore the importance of context-specific, adaptive malaria control strategies, complemented by broader efforts to mitigate climate change.