title: Response of a deterministic epidemiological system to a stochastically varying environment.
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.
authors.affiliation: Epidemiology and Modelling Group, Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EA, United Kingdom. j.truscott@ic.ac.uk
authors.forename: J E
authors.initials: JE
authors.lastname: Truscott
authors.forename: C A
authors.initials: CA
authors.lastname: Gilligan
mesh_terms: D027461:Beta vulgaris / Q000382:microbiology / Q000821:virology; D017790:Closterovirus / Q000472:pathogenicity; D004196:Disease Outbreaks / Q000706:statistics & numerical data; D004777:Environment; D004813:Epidemiology / Q000706:statistics & numerical data*; D008390:Markov Chains; D008962:Models, Theoretical; D009235:Myxomycetes / Q000821:virology; D010935:Plant Diseases / Q000382:microbiology / Q000706:statistics & numerical data / Q000821:virology; D012621:Seasons; D013269:Stochastic Processes; D013696:Temperature