Computational Modelling of Measles Transmission Dynamics Among Children Under 5 Years in Borno State, Nigeria: A Compartmental SVEIR Model

Abstract

<title>Abstract</title> <bold>Background</bold>: Measles is a highly contagious viral disease that significantly threatens child health globally. While vaccination programmes have made substantial progress in reducing measles incidence, there is a growing concern about measles infections among children under 5 years. The SVEIR model was used to calculate the prevalence, recruitment rates, and effectiveness of the measles vaccine from the literature and demographics and the parameter estimation of the model estimated better values for effective control of measles outbreaks in Borno State Nigeria. <bold>Methodology</bold>: This study used a retrospective secondary data, and District Health Information System-2 (DHIS-2) was utilized as the source of measles incidences in some selected health facilities in Maiduguri Metropolis LGAs (MMC, Mafa, Konduga, and Jere). The data was used for curve-fitting with the model estimates. This study employed an extended simple SIR Model to capture the vaccinated and exposed populations as SVEIR suitable for this study aimed to estimate the prevalence of measles among children under 5 years of age, match the SVEIR-estimates to the actual incidence data, to understand disease dynamics and estimate the recruitment-rates into the susceptible populations. <bold>Results</bold>: The SVEIR model performance metrics measured were the standard error (SE)and coefficient of determination (R²), which indicated the precision of the parameter estimates and the goodness of fit with the actual data respectively. The R² values range between 0.95-0.99 across different LGAs measles data where a smaller SE (0.015) was found in the model also indicating the higher precision of the parameter estimates for the Transmission rate (β) and vaccination coverage (σ). The SVEIR model revealed that the measles vaccine is very effective, with a theta (θ) value ranging from 90-95%. The Model also revealed a perfect curve fitting between the SVEIR predicted estimates and the actual data. However, the vaccine coverage was relatively low across the study areas (9.3–75%), with Mafa having the lowest (0.093) coverage. The findings suggest that early detection and implementation of effective measles vaccination are essential for controlling measles outbreaks in Borno State. <bold>Conclusion</bold>; The SVEIR model estimated the overall prevalence of measles as (39.70%), recruitment rates (75-540) and effectiveness (90-95%) of MCV-vaccine for the control of measles across the studied LGAs in Borno State.