Mathematical Modelling of Diphtheria Transmission Dynamics for Effective Strategies of Prevention and Control with Emphasis on Vaccination and Vaccine-Induced Immunity

Abstract

Diphtheria is a bacterial infection that can cause severe respiratory illnesses leading to death if left untreated. Despite the availability of effective vaccines, diphtheria still poses a significant public health challenge in many parts of the world. Mathematical modelling is a powerful tool that enables researchers to understand the dynamics of diphtheria transmission and evaluate the effectiveness of different control measures. In this study, investigation into transmission dynamics to inform effective strategies for controlling and preventing outbreaks of diphtheria is considered. By developing a mathematical model that accurately represents the dynamics of diphtheria transmission in a population, we can predict how diphtheria will spread under different scenarios and evaluate the effectiveness of different control measures. Effective strategies of controlling and prevention was modelled resulting into blocks of dynamics compartments. Basic properties of the model were also investigated, analyzed and reported. The numerical simulation was carried out to study the effect of the factors responsible for causes, spread as well as control and prevention of the disease. The analysis highlights the importance of vaccination coverage, waning immunity, and susceptibility to the disease in diphtheria transmission. The models also suggest that a combination of vaccination, treatment, and contact tracing can be effective in controlling diphtheria outbreaks. This information can then be used to inform public health policies and strategies for preventing outbreaks and reducing the burden of diphtheria on public health. This research also identifies some gaps in our understanding regarding the role of asymptomatic carriers in diphtheria transmission dynamics. Further research is needed to address these gaps using mathematical modelling approaches.