Modeling the interplay of seasonality, armed conflict, and intervention strategies on malaria transmission dynamics in Sudan

Malaria incidence has been increasing in Sudan due to the combined effects of climate change, seasonal transmission patterns, and recurring armed conflict that disrupts public health interventions. To understand these interacting influences, we developed and analyzed a non-autonomous compartmental model that captures the effects of seasonality, armed conflict, and malaria control interventions on disease dynamics. The model incorporates seasonal variability in mosquito abundance and disruptions to control measures arising from conflict. We established that all model solutions are positive and bounded, and derive both the basic reproduction number R 0 and the time-averaged reproduction number R 0 i . The analysis shows that malaria dies out when R 0 < 1 and persists when R 0 > 1 . Sensitivity analysis of R 0 i identifies the most influential parameters driving transmission. Numerical simulation illustrates that seasonal fluctuations strongly influence vector dynamics, while increased conflict intensity and reduced intervention markedly elevate malaria prevalence. Our findings demonstrate that both climate variability and conflict exacerbate malaria transmission, but continuous malaria intervention programs and efforts to reduce the impact of armed conflict can mitigate these effects, alongside the control of asymptomatic malaria carriers. This integrated modeling framework provides valuable insights for designing adaptive malaria control strategies in fragile, climate-sensitive settings such as Sudan.