Mathematical Modeling and Parameter Estimation of Meningitis Transmission Dynamic using Vaccination Strategies in Indonesia
TL;DR
A six-compartment mathematical model is developed to examine the dynamics of meningitis transmission by dividing the population into susceptible, exposed, infected, recovered without disability, recovered with disability, and vaccinated groups to expedite herd immunity and limit disease spread.
Abstract
Meningitis is a public health threat because it progresses rapidly and has serious clinical impacts, including long-term disability. This research develops a six-compartment mathematical model to examine the dynamics of meningitis transmission by dividing the population into susceptible, exposed, infected, recovered without disability, recovered with disability, and vaccinated groups. The model parameters were fitted using the least squares method based on annual meningitis case data in Indonesia from 1990 to 2023 according to estimates originating from the Institute for Health Metrics and Evaluation (IHME)/Global Burden of Disease, accessed through the archived Our World in Data source. Model validation shows high accuracy performance, with a Mean Absolute Percentage Error value of 3.12%. Local sensitivity analysis indicates that the transmission rate (\beta) and vaccination rate (\xi) are the parameters most influencing changes in R0 resulting from parameter variation. Numerical simulation results show that rapid immunization at the onset of an outbreak is the most effective strategy among the vaccination scenarios examined to expedite herd immunity and limit disease spread.