Modeling prevalence of meningitis control strategies through evaluating with available data on meningitis cases reported in Nigeria

Abstract

Meningitis is a major public health concern, especially in developing nations, due to its devastating consequences for human health. Although modeling studies have examined disease transmission dynamics, little attention has been paid to how control strategies affect the behavior of different population groups, including carriers, symptomatic individuals, hospitalized patients, and those in intensive care. This study proposes a computational framework that compares the effectiveness of vaccination of people at risk of the disease versus treating symptomatic infected persons. The basic reproduction number is used to evaluate the equilibrium points. Assess the precision of the proposed model’s illustration to data. We fit the meningitis model using the information at our disposal on meningitis cases reported in Nigeria from the first week of January to the last week of December 2023; this was obtained from the Nigerian Center for Disease Control (NCDC) database. We also performed a sensitivity analysis using a normalized forward sensitivity index to see which parameters had significant effects on the effective reproduction number. The results of both analytical techniques and numerical simulations reveal that recruitment rate, vaccination, progression from carrier to symptomatic stages, and disease-induced death all significantly reduce the incidence and prevalence of meningitis in the community. The study findings could be used to inform decisions about meningitis control initiatives.