The probability of severe disease in zoonotic and commensal infections

S A Frank1, J S Jeffrey

  • 1Department of Ecology and Evolutionary Biology, University of California, Irvine 92697-2525, USA. safrank@uci.edu

Insights

Understanding pathogen transmission is key to preventing severe diseases. This study models how inoculum size, infection route, and asymptomatic immunity influence disease severity in zoonotic and commensal infections.

Area of Science:

  • Infectious Diseases
  • Mathematical Modeling
  • Pathogen Dynamics

Background:

  • Zoonotic and commensal infections can cause mild or severe diseases, with few intermediate outcomes.
  • Pathogen transmission dynamics are influenced by host-pathogen interactions and infection routes.
  • Asymptomatic infections can induce protective immunity, acting as natural vaccinations.

Purpose of the Study:

  • To develop a mathematical model analyzing factors influencing severe disease probability.
  • To investigate the impact of inoculum size, inoculation route, and asymptomatic immunity on disease outcomes.
  • To explore how multiple infection routes affect the balance between disease and protective immunity.

Main Methods:

  • Development of a mathematical model to simulate infection dynamics.
  • Analysis of three key factors: inoculum size, inoculation route, and frequency of asymptomatic infections.
  • Examination of single and dual inoculation routes to assess disease probability.

Main Results:

  • Increased pathogen density favors disease over asymptomatic, immunity-inducing infections in single-route scenarios.
  • Dual inoculation routes can lead to a higher frequency of severe disease at lower pathogen densities.
  • A reversal in disease-inducing versus vaccinating inoculation frequency can occur with multiple routes.

Conclusions:

  • Inoculum characteristics and infection routes significantly modulate disease severity.
  • Multiple infection routes introduce complex dynamics that can increase the risk of severe disease.
  • Mathematical modeling provides insights into preventing and managing infectious diseases.

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