The digital epidemic shield: Revolutionizing Lassa fever preparedness with predictive analytics

Abstract

Introduction: Lassa fever is a significant threat to the public health of West Africa, as it is endemic in areas with frequent outbreaks that lead to high morbidity and mortality. The greatest burden of the disease in the region is experienced in Nigeria, and this disease is persistent and spreads across several ecological zones. Preparedness and response to outbreaks require quick identification of risky areas and proper prediction of outbreaks. This paper uses the concepts of spatial epidemiology and predictive modelling in order to describe the geographic patterns and dynamic trends of Lassa fever in Nigeria. Methods: The study employs a retrospective observational method utilising the epidemiological surveillance data that is publicly available, environmental covariates (rainfall, land surface temperature, and vegetation index), and administrative boundary datasets. R was used to conduct spatial analyses to determine geographic clusters and hotspots of Lassa fever at the state level. Negative Binomial regression was used to model temporal dynamics that incorporated overdispersion and temporal dependence. The prediction of weekly incidence was performed in a 12-week prediction horizon with the help of past trends of cases and environmental predictors. Results: There was a strong spatial clustering of Lassa fever cases with a high burden consistently recorded in Edo, Ondo, Ebonyi, Bauchi, and Taraba states, which is similar to results reported in earlier studies. The rainfall, land surface temperature, and vegetation density were environmental factors which were significantly correlated with the disease incidence (p < 0.01). The predictive accuracy of the forecasting models revealed the possible persistence of the transmission risk in high-burden states during the project period. Conclusion: Spatial analytics blended with environmental information and predictive modelling offers localised, actionable information on the dynamics of Lassa fever transmission. Enhancing state-level surveillance, environmental surveillance, as well as capacity building in the area of diagnostics to respond and intervene early, specifically to allow a decreased effect of Lassa fever outbreaks in Nigeria.