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Coupling a branching process to an infinite dimensional epidemic process


Barbour, A D (2009). Coupling a branching process to an infinite dimensional epidemic process. ESAIM: Probability and Statistics, 14:53-64.

Abstract

Branching process approximation to the initial stages of an epidemic process has been used since the 1950's as a technique for providing stochastic counterparts to deterministic epidemic threshold theorems. One way of describing the approximation is to construct both branching and epidemic processes on the same probability space, in such a way that their paths coincide for as long as possible. In this paper, it is shown, in the context of a Markovian model of parasitic infection, that coincidence can be achieved with asymptotically high probability until MN infections have occurred, as long as MN = o(N2/3), where N denotes the total number of hosts.

Branching process approximation to the initial stages of an epidemic process has been used since the 1950's as a technique for providing stochastic counterparts to deterministic epidemic threshold theorems. One way of describing the approximation is to construct both branching and epidemic processes on the same probability space, in such a way that their paths coincide for as long as possible. In this paper, it is shown, in the context of a Markovian model of parasitic infection, that coincidence can be achieved with asymptotically high probability until MN infections have occurred, as long as MN = o(N2/3), where N denotes the total number of hosts.

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1 citation in Web of Science®
2 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
Dewey Decimal Classification:510 Mathematics
Language:English
Date:2009
Deposited On:19 Feb 2010 13:37
Last Modified:05 Apr 2016 13:57
Publisher:EDP Sciences
ISSN:1262-3318
Publisher DOI:https://doi.org/10.1051/ps:2008023
Related URLs:http://arxiv.org/abs/0710.3697
Permanent URL: https://doi.org/10.5167/uzh-31172

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