Mathematical Modeling of Malaria Transmission and Intervention Scale-Up in the Federal Capital Territory, Nigeria

Abstract

Malaria is highly endemic in Nigeria despite the widespread implementation of proven control interventions, including insecticide-treated nets (ITNs), indoor residual spraying (IRS), seasonal malaria chemoprevention (SMC), intermittent preventive treatment in pregnancy (IPTp), and artemisinin-based combination therapies (ACTs). The persistence of transmission suggests that the combined impact of these interventions may be insufficient to reduce transmission below elimination thresholds. Mathematical modelling provides a rigorous framework for understanding transmission dynamics and evaluating intervention effectiveness in complex epidemiological settings. This study aimed to develop and analyse an age-structured SEIR–SEI mathematical model of malaria transmission that incorporates key intervention strategies and to evaluate their impact on the basic and effective reproduction numbers in the Federal Capital Territory (FCT), Nigeria. A deterministic compartmental model was formulated to describe malaria transmission between humans and mosquitoes. The human population was stratified into children, adults, and pregnant women, each divided into susceptible, exposed, infectious, and recovered compartments, with additional protected classes representing intervention coverage (SMC and IPTp). The mosquito population was modelled using susceptible, exposed, and infectious compartments. Model parameters were informed by literature and FCT-specific data. The basic reproduction number (R₀) was derived using the next-generation matrix approach, and sensitivity analysis was conducted to identify key transmission drivers. Intervention scenarios were simulated to assess their impact on transmission dynamics and elimination thresholds. The model demonstrates that malaria transmission remains robust under baseline conditions, with R₀ exceeding unity. Vector control interventions, particularly ITNs and IRS, significantly reduce transmission by decreasing mosquito biting rates and increasing mosquito mortality. However, single interventions were insufficient to reduce the effective reproduction number (Rₜ) below one. Combined intervention strategies incorporating vector control, chemoprevention, and effective treatment were required to achieve substantial reductions in transmission. Sensitivity analysis identified mosquito biting rate, mosquito mortality, and treatment rate as dominant parameters influencing transmission dynamics. Malaria persistence in the FCT is driven by the combined effects of high transmission intensity and suboptimal interaction of interventions. Achieving elimination requires integrated intervention packages that target both vector and human components of transmission. The proposed model provides a robust framework for evaluating intervention strategies and supports evidence-based malaria elimination planning in high-burden settings.