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Coinfection Dynamics of Two Diseases in a Single Host Population

Daozhou Gao1, Travis C Porco2, Shigui Ruan3

  • 1Mathematics and Science College, Shanghai Normal University, Shanghai, China; Francis I. Proctor Foundation, University of California, San Francisco, CA, USA.

Journal of Mathematical Analysis and Applications
|September 27, 2016
PubMed

Insights

This study models coinfection dynamics using a susceptible-infectious-susceptible (SIS) framework. It analyzes disease spread and stability, revealing complex epidemic behaviors like bistability and bifurcations.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Disease Dynamics

Background:

  • Coinfection and cotransmission of diseases pose significant public health challenges.
  • Understanding the interplay of multiple pathogens in a single host population is crucial for effective control strategies.

Purpose of the Study:

  • To develop and analyze a susceptible-infectious-susceptible (SIS) epidemic model for two coinfecting diseases.
  • To investigate the conditions for disease persistence and the stability of the system.

Main Methods:

  • Mathematical modeling using a compartmental SIS framework.
  • Derivation and analysis of basic and invasion reproduction numbers.
  • Numerical simulations to explore complex dynamics.

Main Results:

  • Basic reproduction numbers determine global stability when disease transmission is independent.
  • The invasion reproduction number indicates uniform persistence under specific conditions.
  • Numerical simulations reveal rich dynamics including backward bifurcation, bistability, and Hopf bifurcation.

Conclusions:

  • The SIS model provides insights into the complex dynamics of coinfectious diseases.
  • Reproduction numbers are key indicators for disease spread and stability.
  • The model highlights the potential for intricate epidemic behaviors that warrant further investigation.
Keywords:
Hopf bifurcationbackward bifurcationbistabilitycoinfectioninvasion reproduction numberuniform persistence

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