title: Contact tracing in stochastic and deterministic epidemic models.
abstract: We consider a simple unstructured individual based stochastic epidemic model with contact tracing. Even in the onset of the epidemic, contact tracing implies that infected individuals do not act independent of each other. Nevertheless, it is possible to analyze the embedded non-stationary Galton-Watson process. Based upon this analysis, threshold theorems and also the probability for major outbreaks can be derived. Furthermore, it is possible to obtain a deterministic model that approximates the stochastic process, and in this way, to determine the prevalence of disease in the quasi-stationary state and to investigate the dynamics of the epidemic.
authors.affiliation: Biomathematik, Universität Tübingen, Auf der Morgenstelle 10, D-72076, Tübingen, Germany. johannes.mueller@uni-tuebingen.de
authors.forename: J
authors.initials: J
authors.lastname: Müller
authors.forename: M
authors.initials: M
authors.lastname: Kretzschmar
authors.forename: K
authors.initials: K
authors.lastname: Dietz
mesh_terms: D003141:Communicable Diseases / Q000453:epidemiology / Q000635:transmission*; D003198:Computer Simulation; D016358:Contact Tracing / Q000191:economics / Q000706:statistics & numerical data*; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D015995:Prevalence; D012749:Sexually Transmitted Diseases / Q000453:epidemiology; D013269:Stochastic Processes; D014376:Tuberculosis / Q000453:epidemiology