Descriptive spatial epidemiology of subclinical Salmonella infection in finisher pig herds: application of a novel method of spatially adaptive smoothing.

We describe the spatial epidemiological features of the 6.8 million meat-juice serological tests that were conducted between 1995 and 2004 as part of the Danish swine Salmonella control programme. We investigated pig and farm density using edge-corrected kernel estimations. Pigs were aggregated at the county level to assess county-level risk, and then we investigated farm-level risk by giving farms a case or non-case label using a cut-off of 40% of pigs positive. Conditional probability surfaces, correcting for the underlying population at risk, were produced for each year of the study period using a novel kernel estimator with a spatially adaptive smoothing bandwidth. This approach improves on previous methods by allowing focussed estimation of risk in areas of high population density while maintaining stable estimates in regions where the data are sparse. Two spatial trends in the conditional probability of a farm being a case were evident: (1) over the whole country, with the highest risk in the west compared to the east; and (2) on the Jutland peninsula with the highest risk in the north and south. At the farm-level a consistent area of risk was the south-west of Jutland. Case farms tended to aggregate indicating spatial dependency in the data. We found no association between pig or farm density and Salmonella risk. We generated hypotheses for this spatial pattern of risk and we conclude that this spatial pattern should be considered in the development of surveillance strategies and as a basis for further, more detailed analyses of the data.