Modelling measles transmission dynamics and the impact of control strategies on outbreak Management.

Abstract

Measles is a highly contagious and potentially fatal disease, despite the availability of effective immunizations. This study formulates a deterministic mathematical model to investigate the transmission dynamics of measles, with eight compartments representing different epidemiological states such as susceptible, vaccinated, exposed, infected, early-treated, delayed-treated, hospitalized, and recovered individuals. We use the Next Generation Matrix (NGN) approach to obtain the basic reproduction number ($R_0$) and examine local stability at the disease-free equilibrium (DFE). Sensitivity analysis with Partial Rank Correlation Coefficients (PRCC) identifies significant parameters influencing disease dynamics, such as vaccination rates, transmission rate, treatment timings, and disease-induced mortality rates. Simulation results show that delayed therapy has a limited effect on lowering the infected population, emphasizing the importance of immediate intervention. Early treatment considerably reduces the number of infected individuals, whereas improved recovery rates in hospitalized cases result in fewer hospitalizations. Vaccination is extremely successful, with increased rates significantly lowering the susceptible population while boosting the vaccinated population. Higher disease-related mortality rates reduce the afflicted population, stressing the importance of strong control methods. The transmission rate has a substantial impact on infection rates and hospitalizations, emphasizing the need for effective public health policies and healthcare capacity. The combined effect of immunization and early treatment provides useful information for optimizing control measures. This study emphasizes the need of quick and effective measures in managing measles outbreaks and serves as a platform for future research into improved public health methods.