Modelling the Spread of Malaria in Ogun State Using Compartmental Epidemiological Models

Malaria remains the leading cause of hospital attendance in Ogun State, South West Nigeria, accounting for an estimated 38 percent of outpatient consultations recorded at state government facilities in 2022. This study formulates a deterministic Susceptible-Exposed-Infected-Recovered-Susceptible compartmental model incorporating a mosquito population sub-model to capture vector-host transmission dynamics in three Local Government Areas: Sagamu, Ijebu-Ode, and Abeokuta North. Epidemiological parameters including transmission probability, biting rate, incubation period, and recovery rate are estimated from state health facility data and published entomological surveys. The basic reproduction number is derived using the next-generation matrix approach and computed as 2.84 for the baseline parameter set. Stability analysis confirms that the endemic equilibrium is asymptotically stable when reproduction number exceeds one, implying persistence of malaria without sustained intervention. Numerical simulations conducted using the Runge-Kutta method explore the effect of insecticide-treated net coverage and indoor residual spraying on infection prevalence. Results demonstrate that achieving 80 percent ITN coverage reduces prevalence by 54 percent within two years, while combining ITN and IRS reduces it by 71 percent. The study recommends prioritising integrated vector control programmes in high-density urban peri-urban transition zones of the state. Keywords: malaria modelling, SEIRS model, Ogun State, basic reproduction number, vector control.