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**A Bayesian estimate of the risk of tick-borne diseases.**
*(English)*
Zbl 1099.62541

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.

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.

### MSC:

62P10 | Applications of statistics to biology and medical sciences; meta analysis |

62C12 | Empirical decision procedures; empirical Bayes procedures |

62J12 | Generalized linear models (logistic models) |

### Keywords:

Bayesian estimation; generalized linear model; epidemiological data; statistical properties
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\textit{M. Jiruše} et al., Appl. Math., Praha 49, No. 5, 389--404 (2004; Zbl 1099.62541)

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