Inference for an epidemic when susceptibility varies
Authors:
- Philip D. O’neillPOPhilip D. O’neill
Open Access
- 1 March 2001
- journal article
- research article
- Published by Oxford University Press (OUP) in Biostatistics
- Vol. 2 (1) , 99-108
Abstract
A stochastic epidemic model featuring fixed-length latent periods, gamma-distributed infectious periods and randomly varying heterogeneity among susceptibles is considered. A Markov chain Monte Carlo algorithm is developed for performing Bayesian inference for the parameters governing the infectious-period length and the hyper-parameters governing the heterogeneity of susceptibility. This method of analysis applies to a wider class of diseases than methods proposed previously. An application to smallpox data confirms results about heterogeneity suggested by an earlier analysis that relied on less realistic assumptions.Keywords
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