Disease emergence in multi-host epidemic models

Robert K McCormack1, Linda J S Allen

  • 1Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, USA. rmccormack16@hotmail.com

Insights

The emergence of infectious diseases increases with the number of hosts a pathogen can infect. This study develops multi-host epidemic models to understand disease spread and emergence conditions.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Disease Dynamics

Background:

  • Pathogens often infect multiple hosts, creating diverse transmission routes.
  • Understanding multi-host pathogen dynamics is crucial for predicting and controlling disease emergence.

Purpose of the Study:

  • To formulate and analyze multi-host epidemic models (SIS and SIR).
  • To determine conditions for disease emergence in multi-host systems.
  • To investigate the impact of the number of hosts on disease spread.

Main Methods:

  • Formulation of Susceptible-Infected-Susceptible (SIS) and Susceptible-Infected-Recovered (SIR) epidemic models for 'n' hosts.
  • Computation of the basic reproduction number (R0).
  • Analysis of the global stability of endemic equilibria for the two-host SIS model.

Main Results:

  • The basic reproduction number increases with the number of hosts ('n').
  • The likelihood of disease emergence is positively correlated with the number of infected hosts.
  • Conditions for the global stability of endemic states were derived for the two-host model.

Conclusions:

  • Increasing the number of hosts amplifies the potential for infectious disease emergence.
  • The developed models provide insights into zoonotic diseases like hantavirus.
  • Mathematical modeling is essential for understanding complex epidemiological patterns in multi-host systems.

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