Mugglin, A.S., Cressie, N. and Gemmell, I. (2002) Hierarchical statistical modelling of influenza epidemic dynamics in space and time. Statistics in Medicine, 21(18), pp. 2703-2721. (doi: 10.1002/sim.1217)
Full text not currently available from Enlighten.
Publisher's URL: http://dx.doi.org/10.1002/sim.1217
Abstract
An infectious disease typically spreads via contact between infected and susceptible individuals. Since the small-scale movements and contacts between people are generally not recorded, available data regarding infectious disease are often aggregations in space and time, yielding small-area counts of the number infected during successive, regular time intervals. In this paper, we develop a spatially descriptive, temporally dynamic hierarchical model to be fitted to such data. Disease counts are viewed as a realization from an underlying multivariate autoregressive process, where the relative risk of infection incorporates the space-time dynamic. We take a Bayesian approach, using Markov chain Monte Carlo to compute posterior estimates of all parameters of interest. We apply the methodology to an influenza epidemic in Scotland during the years 1989-1990.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | UNSPECIFIED |
| Authors: | Mugglin, A.S., Cressie, N., and Gemmell, I. |
| Subjects: | R Medicine > RA Public aspects of medicine |
| College/School: | College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing > Centre for Population and Health Sciences |
| Journal Name: | Statistics in Medicine |
| ISSN: | 0277-6715 |
University Staff: Request a correction | Enlighten Editors: Update this record
Altmetric
Altmetric