<p>This research presents a detailed mathematical framework designed to explore the transmission patterns of Mpox. It encompasses a variety of transmission pathways, notably human-to-human interactions and potential zoonotic transmissions. Our analysis identifies critical equilibrium points within the model and computes effective reproduction numbers: <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$\mathcal {R}_{0P}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi mathvariant="script">R</mi> <mrow> <mn>0</mn> <mi>P</mi> </mrow> </msub> </math></EquationSource> </InlineEquation> for human-to-human spread and <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$\mathcal {R}_{0R}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi mathvariant="script">R</mi> <mrow> <mn>0</mn> <mi>R</mi> </mrow> </msub> </math></EquationSource> </InlineEquation> for contributions from animal reservoirs. We conduct a detailed stability analysis to uncover the specific conditions that facilitate disease emergence and ongoing transmission. The global stability of the MFE and MEE states is rigorously analyzed and demonstrated using the LaSalle invariance stability theorem. A sensitivity analysis further pinpoints key parameters that impact <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$\mathcal {R}_{0P}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi mathvariant="script">R</mi> <mrow> <mn>0</mn> <mi>P</mi> </mrow> </msub> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq4"> <EquationSource Format="TEX">$\mathcal {R}_{0R}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi mathvariant="script">R</mi> <mrow> <mn>0</mn> <mi>R</mi> </mrow> </msub> </math></EquationSource> </InlineEquation>, utilizing a normalized forward sensitivity index. Additionally, parameter estimation and data-driven validation have been performed using real infected case data from Argentina. To address disease control, we explore optimal intervention strategies, including vaccination, treatment options, and public awareness initiatives aimed at curbing the spread of the virus. Numerical simulations complement our findings, offering deeper insights into the model’s dynamics. This study contributes valuable knowledge for crafting targeted strategies to manage Mpox transmission effectively and avert future outbreaks.</p>

Mathematical modeling and transmission insights into Mpox: dynamics, control measures, and data-driven validation

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发表日期：

2026年2月18日

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G. Swathi,
G. S. Mahapatra,
R. Prem Kumar

摘要

This research presents a detailed mathematical framework designed to explore the transmission patterns of Mpox. It encompasses a variety of transmission pathways, notably human-to-human interactions and potential zoonotic transmissions. Our analysis identifies critical equilibrium points within the model and computes effective reproduction numbers: $\mathcal {R}_{0P}$ $R_{0 P}$ for human-to-human spread and $\mathcal {R}_{0R}$ $R_{0 R}$ for contributions from animal reservoirs. We conduct a detailed stability analysis to uncover the specific conditions that facilitate disease emergence and ongoing transmission. The global stability of the MFE and MEE states is rigorously analyzed and demonstrated using the LaSalle invariance stability theorem. A sensitivity analysis further pinpoints key parameters that impact $\mathcal {R}_{0P}$ $R_{0 P}$ and $\mathcal {R}_{0R}$ $R_{0 R}$ , utilizing a normalized forward sensitivity index. Additionally, parameter estimation and data-driven validation have been performed using real infected case data from Argentina. To address disease control, we explore optimal intervention strategies, including vaccination, treatment options, and public awareness initiatives aimed at curbing the spread of the virus. Numerical simulations complement our findings, offering deeper insights into the model’s dynamics. This study contributes valuable knowledge for crafting targeted strategies to manage Mpox transmission effectively and avert future outbreaks.