Response of a deterministic epidemiological system to a stochastically varying environment

Proc Natl Acad Sci U S A. 2003 Jul 22;100(15):9067-72. doi: 10.1073/pnas.1436273100. Epub 2003 Jul 11.

Abstract

Fluctuations in the natural environment introduce variability into the biological systems that exist within them. In this paper, we develop a model for the influence of random fluctuations in the environment on a simple epidemiological system. The model describes the infection of a dynamic host population by an environmentally sensitive pathogen and is based on the infection of sugar beet plants by the endoparasitic slime-mold vector Polymyxa betae. The infection process is switched on only when the temperature is above a critical value. We discuss some of the problems inherent in modeling such a system and analyze the resulting model by using asymptotic techniques to generate closed-form solutions for the mean and variance of the net amount of new inoculum produced within a season. In this way, the variance of temperature profile can be linked with that of the inoculum produced in a season and hence the risk of disease. We also examine the connection between the model developed in this paper and discrete Markov-chain models for weather.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Beta vulgaris / microbiology
  • Beta vulgaris / virology
  • Closterovirus / pathogenicity
  • Disease Outbreaks / statistics & numerical data
  • Environment
  • Epidemiology / statistics & numerical data*
  • Markov Chains
  • Models, Theoretical
  • Myxomycetes / virology
  • Plant Diseases / microbiology
  • Plant Diseases / statistics & numerical data
  • Plant Diseases / virology
  • Seasons
  • Stochastic Processes
  • Temperature