Controlling the Transmission Dynamics of Monkey Pox Infection: A Mathematical Model Approach

The spread of Monkey Pox (Mpox) poses significant public health challenges, requiring effective intervention strategies to mitigate its impact. This study propose a mathematical model to explore the transmission dynamics of Mpox and assess the impact of quarantine as a control measure. The model divides the population into compartments representing Susceptible, Exposed, Infectious, Quarantined, and Recovered individuals. The system of ordinary differential equations describing the dynamics of the infection were derived. The equilibrium states of the model equations: Disease free equilibrium and Disease endemic equilibrium states were obtained. The stability analysis of the disease free equilibrium was analyzed and found it to be stable. The reproduction number ( R 0 ) was obtained and its numerical value was computed. Numerical simulations were performed to investigate how varying quarantine rates affect the progression of the disease across these compartments. The simulations explore the implications of different quarantine intensities on the number of infectious and exposed individuals over time. The results obtained indicate that quarantine can effectively reduce the transmission rate of the infection. Also, it revealed the potential of quarantine to reduce the disease spread and alleviate its overall impact on the population. The findings offered a framework for understanding the dynamics of Mpox transmission and assist public health authorities in designing effective intervention strategies.

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Publication Details

Journal
American Journal of Applied Mathematics
Published
2026-09-18
DOI
https://doi.org/10.11648/j.ajam.20261405.12
Primary Topic
Poxvirus research and outbreaks
Type
article
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article

Controlling the Transmission Dynamics of Monkey Pox Infection: A Mathematical Model Approach

Ayokunle John Tadema, Samuel Jegede, Felix Daodu, Olawale Olatubi et al.
American Journal of Applied Mathematics
Poxvirus research and outbreaks
article

Controlling the Transmission Dynamics of Monkey Pox Infection: A Mathematical Model Approach

Ayokunle John Tadema, Samuel Jegede, Felix Daodu, Olawale Olatubi, Patrick Aye
article en

Abstract

The spread of Monkey Pox (Mpox) poses significant public health challenges, requiring effective intervention strategies to mitigate its impact. This study propose a mathematical model to explore the transmission dynamics of Mpox and assess the impact of quarantine as a control measure. The model divides the population into compartments representing Susceptible, Exposed, Infectious, Quarantined, and Recovered individuals. The system of ordinary differential equations describing the dynamics of the infection were derived. The equilibrium states of the model equations: Disease free equilibrium and Disease endemic equilibrium states were obtained. The stability analysis of the disease free equilibrium was analyzed and found it to be stable. The reproduction number ( R 0 ) was obtained and its numerical value was computed. Numerical simulations were performed to investigate how varying quarantine rates affect the progression of the disease across these compartments. The simulations explore the implications of different quarantine intensities on the number of infectious and exposed individuals over time. The results obtained indicate that quarantine can effectively reduce the transmission rate of the infection. Also, it revealed the potential of quarantine to reduce the disease spread and alleviate its overall impact on the population. The findings offered a framework for understanding the dynamics of Mpox transmission and assist public health authorities in designing effective intervention strategies.

American Journal of Applied MathematicsVol. 14(5)
Federal Government of Nigeria (NG), Adekunle Ajasin University (NG), McPherson University (NG)
Good health and well-being
Openalex Percentile: Top 12%
Poxvirus research and outbreaks
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Controlling the Transmission Dynamics of Monkey Pox Infection: A Mathematical Model Approach — Ayokunle John Tadema, Samuel Jegede, et al. · American Journal of Applied Mathematics (2026) | TGRS Research Map | TGRS