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A pair formation model with recovery: Application to mpox.

Matthew I Betti1, Lauren Farrell2, Jane Heffernan3

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Mpox outbreaks spread through close contact and confer immunity, necessitating new mathematical models. Our research introduces a novel framework combining pair formation and recovery to understand mpox transmission dynamics.

Keywords:
Mathematical modelMpoxPair formation

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Disease Modeling

Background:

  • Current mpox outbreaks exhibit unique transmission patterns, primarily within men who have sex with men (MSM) communities through close, prolonged contact.
  • Mpox infection confers long-lasting immunity, distinguishing it from other infections with limited or no post-infection immunity.

Purpose of the Study:

  • To develop a novel mathematical model that incorporates both pair formation and recovery dynamics for mpox.
  • To analyze the emergent epidemiological behaviors arising from the interplay of pair formation and recovery in disease transmission.

Main Methods:

  • Development of a new compartmental model integrating sexual pair formation and disease-induced immunity.
  • Derivation and analysis of the basic reproduction number (R0) for the proposed model.
  • Estimation of R0 for human mpox using global and Canadian epidemiological data.

Main Results:

  • The combined dynamics of pair formation and recovery generate distinct infection waves not observed in standard SIR or pair-formation-only models.
  • An estimated basic reproduction number (R0) of approximately 2.3 for human mpox was derived.
  • The model provides a framework for estimating key transmission parameters and comparing interventions.

Conclusions:

  • The unique transmission characteristics of mpox, including pair formation and recovery, necessitate specialized modeling approaches.
  • Public health strategies for mpox may require tailored interventions that account for these specific epidemiological dynamics.
  • The derived R0 offers valuable insights for disease control and comparative analysis with other models.