Mathematical modelling to assess the impact of vaccine delivery on measles transmission dynamics in Ondo state, Nigeria

Abstract

Introduction: measles, a highly contagious disease, poses significant risks, particularly to unvaccinated children and pregnant women. Vaccination remains the most effective control measure. In Nigeria, outbreaks are more prevalent in areas with low vaccination coverage, including Ondo State, which recently experienced an outbreak. This study employs a deterministic model to evaluate the impact of vaccination and other factors influencing measles transmission in the region. Methods: a mathematical model susceptible, vaccinated, infected and recovered (SVIR) was set up and analyzed. Using parameters within the study population, R-studio (Version 4.4.1) was used to simulate data and run optimization using a deSolve library to find a solution to a set of four ordinary differential equations (ODE). A Sympy library in Python package was used for differentiation and parameter evaluation. Results: we found that measles outbreaks are likely to occur when effective immunization is very low. Essentially, if the vaccine efficiency is less than 75%, it may trigger an outbreak (R0 > 1) while an increase in the vaccinated population results in a corresponding decrease in the susceptible population. Overall, vaccine efficiency, vaccination rate, and disease transmission rate are key to the control of the disease. Conclusion: we set up an SVIR model. Using a scenario analysis, we found that Measles disease outbreaks are eminent in communities with zero percent dose vaccination. Vaccine efficiency is also key to eliminating the disease.