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Title: A Bayesian estimate of the risk of tick-borne diseases (English)
Author: Jiruše, Marek
Author: Machek, Josef
Author: Beneš, Viktor
Author: Zeman, Petr
Language: English
Journal: Applications of Mathematics
ISSN: 0862-7940 (print)
ISSN: 1572-9109 (online)
Volume: 49
Issue: 5
Year: 2004
Pages: 389-404
Summary lang: English
Category: math
Summary: The paper considers the problem of estimating the risk of a tick-borne disease in a given region. A large set of epidemiological data is evaluated, including the point pattern of collected cases, the population map and covariates, i.e. explanatory variables of geographical nature, obtained from GIS. The methodology covers the choice of those covariates which influence the risk of infection most. Generalized linear models are used and AIC criterion yields the decision. Further, an empirical Bayesian approach is used to estimate the parameters of the risk model. Statistical properties of the estimators are investigated. Finally, a comparison with earlier results is discussed from the point of view of statistical disease mapping. (English)
Keyword: Bayesian estimation
Keyword: generalized linear model
Keyword: epidemiological data
Keyword: statistical properties
MSC: 62C12
MSC: 62G05
MSC: 62J12
MSC: 62P10
idZBL: Zbl 1099.62541
idMR: MR2086085
DOI: 10.1023/B:APOM.0000048119.55855.65
Date available: 2009-09-22T18:18:56Z
Last updated: 2020-07-02
Stable URL:
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Reference: [8] W. N.  Venables, B. D. Ripley: Modern Applied Statistics with  S-PLUS.Springer, New York, 1997, pp. 242–243. MR 1337030
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