Modeling the role of public health intervention measures in halting the transmission of monkeypox virus

Monkeypox (mpox), a zoonotic viral disease caused by the monkeypox virus (mpoxv), is endemic in many countries in West Africa and is sometimes exported to other parts of the world. The recent outbreak of mpoxv in humans, in endemic and non-endemic countries, has created substantial public health concern worldwide. This research uses a mechanistic model to study the transmission dynamics of mpoxv epidemics in the USA. Our model describes the interaction between different categories of individuals represent various infection phases and hospitalization processes. The model also takes into account the extent of compliance with non-pharmaceutical intervention strategies (NPIs), such as using condoms during sexual contact, quarantine and avoiding large gatherings. The model's equilibria are analyzed, and results on asymptotic stability are obtained. Moreover, the basic reproductive number and other threshold quantities are used to establish the conditions for a forward or backward bifurcation. Our model accurately captures the incidence curves from mpox surveillance data for the USA, indicating that it can be used to explain mpoxv transmission and suggest some effective ways to enhance control efforts. In addition, numerical simulations are carried out to examine the influence of some parameters on the overall dynamics of the model. A partial rank correlation coefficient is adopted for the sensitivity analysis to determine the model most important parameters, which require close attention for effective mpoxv prevention and control. We conclude that it is especially important to ensure that NPIs are properly followed to mitigate mpoxv outbreaks effectively.

Automated summary

Monkeypox, caused by the monkeypox virus, is a zoonotic viral disease that is endemic in West Africa and can be exported to other parts of the world. This study uses a mechanistic model to analyze the transmission dynamics of monkeypox in the USA. The model considers different categories of individuals and compliance with non-pharmaceutical intervention strategies, and accurately captures the incidence curves.