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Area of Science:

  • Epidemiology
  • Evolutionary biology
  • Mathematical modeling

Background:

  • Pathogen emergence poses risks to human and animal health.
  • Previous models often focus on maladapted strains (R0 < 1), overlooking weakly adapted strains (R0 ≈ 1).
  • The impact of susceptible population depletion by an initial strain on subsequent mutated strain emergence is not well quantified.

Purpose of the Study:

  • To model pathogen emergence considering susceptible population dynamics.
  • To quantify the effect of susceptible depletion on the emergence probability of mutated strains.
  • To assess the relevance of these dynamics using Chikungunya virus emergence data.

Main Methods:

  • Development of a mathematical model incorporating changes in susceptible host populations over time.
  • Analysis of pathogen emergence dynamics considering feedback from an initial strain.
  • Application of the model to a real-world case study: Chikungunya virus on La Réunion Island.

Main Results:

  • Susceptible population depletion by an initial strain significantly reduces the emergence probability of a mutated strain.
  • This effect is more pronounced than predicted by simply scaling the reproductive ratio.
  • The model demonstrated an approximately 10-fold reduction in emergence probability for Chikungunya virus, compared to models ignoring susceptible depletion.

Conclusions:

  • Population feedbacks, specifically susceptible depletion, are crucial for accurate prediction of disease emergence.
  • Models must account for dynamic changes in susceptible populations to realistically assess pathogen emergence risks.
  • Understanding these dynamics is vital for public health preparedness and intervention strategies.