Statistical approaches to the monitoring and surveillance of infectious diseases for veterinary public health.
This paper covers the aspect of using statistical methodology for the monitoring and surveillance of routinely collected data in veterinary public health. An account of the Farrington algorithm and Poisson cumulative sum schemes for the prospective detection of aberrations is given with special attention devoted to the occurrence of seasonality and spatial aggregation of the time series. Modelling approaches for retrospective analysis of surveillance counts are also described. To illustrate the applicability of the methodology in veterinary public health, data from the monitoring of rabies among fox in Hesse, Germany, are analysed.
Höhle
Michael
M
Department of Statistics, University of Munich, Munich, Germany. hoehle@stat.uni-muenchen.de
Paul
Michaela
M
Held
Leonhard
L
D000818:Animals; D003141:Communicable Diseases / Q000453:epidemiology / Q000662:veterinary*; D004196:Disease Outbreaks / Q000662:veterinary*; D004812:Epidemiologic Methods / Q000662:veterinary*; D015233:Models, Statistical; D011446:Prospective Studies; D012189:Retrospective Studies; D013223:Statistics as Topic / Q000379:methods*; D014730:Veterinary Medicine / Q000379:methods*