header

Understanding the Impact of HIV on Mpox Transmission in an Msm Population: A Mathematical Modeling Study

24 Pages Posted: 22 Apr 2024 Publication Status: Accepted

See all articles by Andrew Omame

Andrew Omame

Federal University of Technology Owerri - School of Physical Sciences

Qing Han

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics (LIAM), York University

Sarafa Iyaniwura

Government of the United States of America - Los Alamos National Laboratory

Ebenezer Adeniyi

University of Ibadan

Nicola Luigi BRAGAZZI

York University

Xiaoying Wang

Trent University

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium

Woldegebriel Assefa Woldegerima

York University; Africa-Canada Artificial Intelligence and Data Innovation Consortium

Abstract

The recent mpox outbreak (in 2022-2023) has different clinical and epidemiological features compared with previous outbreaks of the disease. During this outbreak, sexual contact was believed to be the primary transmission route of the disease. In addition, the community of men having sex with men (MSM) was disproportionately affected by the outbreak. This population is also disproportionately affected by HIV infection. Given that both diseases can be transmitted sexually, the endemicity of HIV, and the high sexual behavior associated with the MSM community, it is essential to understand the effect of the two diseases spreading simultaneously in an MSM population. Particularly, we aim to understand the potential effects of HIV on an mpox outbreak in the MSM population. We develop a mechanistic mathematical model of HIV and mpox co-infection. Our model incorporates the dynamics of both diseases and consider HIV treatment with anti-retroviral therapy (ART). In addition, we consider a potential scenario where HIV infection increases susceptibility to mpox, and investigated the potential impact of this mechanism on mpox dynamics. Our analysis shows that HIV can facilitate the spread of mpox in an MSM population, and that HIV treatment with ART may not be sufficient to control the spread of mpox in the population. However, we showed that a moderate use of condom or reduction in sexual contact in the population combined with ART is beneficial in controlling mpox transmission. Based on our analysis, it is evident that an effective control of HIV, specifically through substantial ART use, moderate condom compliance, and reduction in sexual contact, is imperative for curtailing the transmission of mpox in an MSM population and mitigating the compounding impact of these intertwined epidemics.

Note:

Funding Information: This research is funded by the Canadian Institute for Health Research (CIHR) under the Mpox and other zoonotic threats Team Grant (FRN. 187246). W.A.W., J.D.K, and N.L.B. acknowledge financial support from the CIHR. W.A.W acknowledges financial support from the NSERC Discovery Grant (Appl No.: RGPIN-2023-05100). JDK acknowledges support from IDRC (Grant No. 109981). JDK equally acknowledges support from NSERC Discovery Grant (Grant No. RGPIN-2022-04559), NSERC Discovery Launch Supplement (Grant No: DGECR-2022-00454) and New Frontier in Research Fund- Exploratory (Grant No. NFRFE-2021-00879).

Conflict of Interests: The authors declare that there is no competing interest.

Keywords: HIV-mpox co-infection, infectious disease modeling, invasion reproduction number, control reproduction number, Sensitivity analysis, MSM

Suggested Citation

Omame, Andrew and Han, Qing and Iyaniwura, Sarafa and Adeniyi, Ebenezer and BRAGAZZI, Nicola Luigi and Wang, Xiaoying and Kong, Jude Dzevela and Woldegerima, Woldegebriel Assefa, Understanding the Impact of HIV on Mpox Transmission in an Msm Population: A Mathematical Modeling Study. Available at SSRN: https://ssrn.com/abstract=4793888 or http://dx.doi.org/10.2139/ssrn.4793888

Andrew Omame

Federal University of Technology Owerri - School of Physical Sciences

Owerri
1526
Owerri, Ihiagwa 234
Nigeria

Qing Han

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics (LIAM), York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Sarafa Iyaniwura

Government of the United States of America - Los Alamos National Laboratory ( email )

Ebenezer Adeniyi

University of Ibadan ( email )

Nicola Luigi BRAGAZZI

York University ( email )

Xiaoying Wang

Trent University ( email )

1600 West Bank Drive
Peterborough, K9J 7B8
Canada

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

Woldegebriel Assefa Woldegerima (Contact Author)

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
24
Abstract Views
74
PlumX Metrics