This study investigates the spatio-temporal patterns and determinants of malaria prevalence across Nigeria, with particular attention to transmission dynamics in Sokoto State. Utilizing both statistical and mathematical models, we examined the impact of environmental factors, socioeconomic variables, and interventions such as seasonal malaria chemoprevention (SMC) and vaccination on malaria transmission dynamics. Statistical analysis revealed that malaria prevalence has significantly declined from 2010 to 2021 across Nigeria; however, regional disparities persist, particularly in rural and socioeconomically disadvantaged areas where malaria rates remain comparatively higher. Sokoto State, consistent with patterns observed in parts of northern Nigeria, continues to experience notable malaria burden, suggesting the influence of localized drivers such as proximity to irrigation and limited healthcare access. The mathematical model supports these findings by demonstrating that reducing mosquito breeding sites and improving healthcare access can mitigate transmission, especially in settings with sustained transmission intensity. The combined models underscore the potential effectiveness of sustained, region-specific interventions—such as long-acting vaccines and environmental management—alongside broader control efforts. We additionally conducted a Bayesian prior sensitivity analysis to assess the robustness of the statistical model. Results showed that fixed-effect estimates and predicted malaria prevalence remained stable under multiple alternative prior specifications, confirming that the main findings are driven by the data rather than modeling assumptions. This study highlights the need for adaptive, targeted strategies to address regional malaria transmission variations, informing evidence-based policy recommendations toward malaria elimination in Nigeria.
Ukwajunor et al. (Tue,) studied this question.