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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Stochastic Modeling

Background:

  • Infectious disease dynamics are complex and influenced by various factors.
  • Understanding disease spread in multi-patch environments is crucial for public health interventions.
  • The impact of the infectious period's distribution on disease dynamics requires further investigation.

Purpose of the Study:

  • To develop a stochastic discrete-time model for infectious disease spread in an n-patch environment.
  • To analyze the influence of the distribution of the infectious period (T) on model outcomes.
  • To compare model results for various infectious period distributions.

Main Methods:

  • Development of a stochastic discrete-time mathematical model.
  • Analytical investigation of basic reproduction numbers (R0) and probability of minor epidemic (P0).
  • Numerical simulations to assess final epidemic size (F) and duration (D) in a two-patch model.

Main Results:

  • The distribution of the infectious period T significantly influences disease spread outcomes.
  • Analytical ordering of reproduction numbers based on the probability generating function of T for n=2.
  • Numerical simulations provide insights into epidemic size and duration for specific scenarios.

Conclusions:

  • The distribution of the infectious period is a critical factor in predicting infectious disease dynamics.
  • The developed model provides a framework for assessing the impact of infectious period variability.
  • Findings can inform targeted public health strategies for disease control in connected populations.