Quantifying the climatic influence on Lassa fever incidences in six high-risk Nigerian states using multilinear regression and generalized additive models

Lassa fever, a viral hemorrhagic disease endemic to West Africa, presents significant public health challenges due to its environmental sensitivity and high mortality rate. This study investigates the influence of meteorological and environmental variables on the incidence of Lassa fever, a viral hemorrhagic disease endemic to West Africa, across six high-risk Nigerian states: Ondo, Edo, Ebonyi, Benue, Plateau, and Bauchi. Using weekly Lassa fever case data from 2018–2022 and ERA5 reanalysis datasets, we applied multilinear regression and generalized additive models (GAMs) to quantify the relationships between Lassa fever outbreaks and climatic variables, including precipitation, air and soil temperatures, dew point, vegetation indices, and soil moisture. The analysis revealed a strong seasonality in Lassa fever occurrence. Results showed significant inverse correlations between precipitation, vegetation cover, and case numbers. Dew point temperature (d2m) and soil temperature (st1) emerged as significant predictors, with lower d2m associated with increased cases. The GAM analysis indicated that most climatic variables exhibit nonlinear relationships with disease incidence, and a temperature rise between 17–20 °C was found to significantly increase infection rates. These findings underscore the crucial role of environmental conditions in shaping Lassa fever dynamics and highlight the importance of integrating meteorological data into early warning and mitigation strategies for endemic regions. Furthermore, this study provides a framework for attaining Sustainable Development Goal 3 (Good Health and Well-being) through a climate-informed early warning system for epidemic-prone diseases in vulnerable regions.