Mathematical Modeling of Monkeypox Transmission Dynamics: A Review

Abstract

The Monkeypox (Mpox) outbreak continues to pose a significant public health burden worldwide. This situation necessitates a deeper understanding of the disease's transmission and control mechanisms. Mathematical modeling serves as an effective tool for this purpose. The integration of vaccination, quarantine, isolation, and hospitalization strategies within these models highlights their critical role in mitigating the spread of Mpox. This review presents a comprehensive analysis of mathematical models developed to study the transmission dynamics and control of the Mpox virus, covering a broad spectrum from basic frameworks to more advanced models incorporating vaccination, quarantine, isolation, and hospitalization strategies. Key findings from the reviewed studies suggest that models integrating multiple simultaneous intervention strategies better represent the dynamics, but are relatively rare. Furthermore, few models consider bidirectional transmission routes between humans and animals; these are crucial for accurately characterizing Mpox dynamics. The inclusion of complex features such as fractional-order derivatives, risk group stratification, and optimal control analyses has been limited but demonstrates significant potential for more realistic scenario analysis. By synthesizing these findings, this review aims to inform researchers and policymakers in designing more effective intervention strategies to curb the spread of Mpox.