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Optimal vaccination schemes for epidemics among a population of households, with application to variola minor in Brazil

Ball, Frank G., Lyne, Owen D. (2006) Optimal vaccination schemes for epidemics among a population of households, with application to variola minor in Brazil. Statistical Methods in Medical Research, 15 (5). pp. 481-497. ISSN 0962-2802. (doi:10.1177/0962280206071643) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:7579)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://smm.sagepub.com/cgi/reprint/15/5/481

Abstract

This paper is concerned with stochastic models for the spread of an epidemic among a community of households, in which individuals mix uniformly within households and, in addition, uniformly at a much lower rate within the population at large. This two-level mixing structure has important implications for the threshold behaviour of the epidemic and, consequently, for both the effectiveness of vaccination strategies for controlling an outbreak and the form of optimal vaccination schemes. A brief introduction to optimal vaccination schemes in this setting is provided by presenting a unified treatment of the simplest and most-studied case, viz. the single-type SIR (susceptible infective removed) epidemic.

A reproduction number R *, which determines whether a trace of initial infection can give rise to a major epidemic, is derived and the effect of a vaccination scheme on R * is studied using a general model for vaccine action. In particular, optimal vaccination schemes which reduce R * to its threshold value of one with minimum vaccination coverage are considered. The theory is illustrated by application to data on a variola minor outbreak in São Paulo, which, together with other examples, is used to highlight key issues related to vaccination schemes.

Item Type: Article
DOI/Identification number: 10.1177/0962280206071643
Additional information: Full-text freely available via Official URL Link
Subjects: Q Science > QA Mathematics (inc Computing science) > QA273 Probabilities
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Owen Lyne
Date Deposited: 05 Sep 2008 12:39 UTC
Last Modified: 05 Nov 2024 09:39 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/7579 (The current URI for this page, for reference purposes)

University of Kent Author Information

Lyne, Owen D..

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