A Hybrid SEIR-SEI and ARIMA Modeling Framework to Evaluate Malaria Intervention Packages and Elimination Prospects in the Federal Capital Territory, Nigeria

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Background: Despite substantial investments in malaria control, transmission remains persistent in Nigeria, including the Federal Capital Territory (FCT). Traditional mathematical models capture transmission dynamics, while time-series approaches provide short-term forecasts; however, these methods are often applied independently, limiting their ability to jointly inform intervention planning and elimination strategies. Objective: This study developed a hybrid SEIR-SEI and autoregressive integrated moving average (ARIMA) modelling framework to evaluate the effectiveness of malaria intervention packages and assess elimination prospects in the FCT, Nigeria. Methods: An age-structured SEIR-SEI compartmental model describing human–vector malaria transmission was integrated with an ARIMA time-series model fitted to reported malaria incidence data. The SEIR-SEI component captured mechanistic transmission dynamics and intervention effects, while the ARIMA model provided data-driven forecasts. Intervention scenarios, including insecticide-treated nets (ITNs), indoor residual spraying (IRS), seasonal malaria chemoprevention (SMC), intermittent preventive treatment in pregnancy (IPTp), artemisinin-based combination therapy (ACT), and combined strategies, were simulated. Model outputs were evaluated using infection prevalence, reproduction number (R0), and projected incidence trends. Results: The ARIMA model demonstrated a good fit to observed malaria incidence data and provided reliable short-term forecasts. The SEIR–SEI simulations showed that baseline conditions sustain endemic transmission, with (R0 > 1). Single intervention strategies produced moderate reductions in infection levels but failed to achieve elimination. In contrast, combined intervention packages significantly reduced transmission and, under optimal coverage conditions, drove (R0) below unity. The hybrid framework revealed that elimination prospects depend not only on intervention efficacy but also on coverage, timing, and sustained implementation. Conclusion: The hybrid SEIR–SEI–ARIMA framework provides a robust approach for integrating mechanistic understanding with empirical forecasting to evaluate malaria control strategies. The findings indicate that malaria persistence in the FCT is driven by suboptimal integration of interventions rather than lack of effective tools. Achieving elimination will require coordinated, high-coverage intervention packages supported by data-driven planning and continuous monitoring.

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