Spatial patterns in surveillance data during control of Salmonella Dublin in bovine dairy herds in Jutland, Denmark 2003–2009

Annette Kjær Ersbøll, Liza Rosenbaum Nielsen

    7 Citations (Scopus)

    Abstract

    Salmonella Dublin is the most commonly isolated Salmonella serotype in Danish cattle and leads to economic and welfare losses in infected herds. Furthermore, it leads to high mortality in human cases. A national surveillance program for Salmonella Dublin was initiated in Denmark in October 2002. This study aimed at modelling the progress and spatial patterns during the control of Salmonella Dublin in dairy herds in the Jutland peninsula in Denmark, especially differences between regions and years. A total of 6331 dairy herds were included during 2003–2009. Antibody measurements of bulk-tank milk samples were used
    for testing herd-level Salmonella status in these dairy herds. Risk maps were estimated as prevalence intensity maps. Spatial clustering was analysed using scan statistics and SMR was estimated.
    In 2003, the prevalence of Salmonella Dublin test-positive dairy herds was 24%. It decreased to 12% in 2009. Prevalence intensity maps showed large differences in the reduction of Salmonella Dublin test-positive herds. The number of clusters reduced during the study period. However, throughout the study period two clusters remained significant. Differences were seen in the progress of the control between regions over the years. The implementation and effectiveness of the control program was different between regions.
    The progress of control was seen to vary not only between regions, but also over time influencing infection dynamics. Thus, recommendations and regionally targeted efforts during control campaigns are needed.

    Original languageEnglish
    JournalSpatial and Spatio-temporal Epidemiology
    Volume2
    Issue number3
    Pages (from-to)195-204
    Number of pages10
    ISSN1877-5845
    DOIs
    Publication statusPublished - Sept 2011

    Keywords

    • Former LIFE faculty

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