NUMERICAL SIMULATIONS AND CONTROL STRATEGIES FOR COVID-19 AND MONKEYPOX CO-INFECTION DYNAMICS

Abstract

This study is a continuation of [16], which developed a deterministic model for the co-infection dynam ics of COVID-19 and Monkeypox, including model formulation, basic properties, reproduction numbers, and stability analyses of both disease-free and endemic equilibria. In this extension, we further investigate key dynamical aspects of the system that were not previously addressed. Specifically, we establish the existence and uniqueness of solutions using the fixed point theorem, perform sensitivity analysis of the basic reproduc tion numbers for both diseases to identify key epidemiological parameters driving disease transmission, and formulate an optimal control problem to determine effective intervention strategies. Furthermore, numerical simulations are carried out using Python to illustrate the theoretical results and to provide insight into the impact of control measures on disease dynamics. The results obtained provide deeper understanding of the model behavior and offer useful guidance for designing efficient strategies to mitigate the co-infection burden of COVID-19 and Monkeypox.