The importance of pork in the transmission of Salmonella spp. to humans has led to the development of control programmes worldwide. For this, knowledge on the epidemiology of the infection in the production system is fundamental to the efficacy of the regulations. Our objective was to determine the prevalence and spatial distribution of Salmonella-infected farms in the central region of Argentina, and to identify the predominant serotypes and epidemiological factors associated with an increased risk of infection. Salmonella was isolated from 22 of 52 sampled farms, for a farm prevalence of 42·3% (95% confidence interval 28·4–56·1). The most frequent serotypes isolated were S. Typhimurium and S. Derby, which have often been considered of public health concern in the region. Limited evidences of global and local clustering in the region under study were found, and the type of feed and presence of diarrhoeic pigs were significantly associated with having Salmonella shedders in the farm. This highlights the need to evaluate microbiological controls at the farm level, and demonstrates the usefulness of the spatial tools to identify areas of greatest risk when processing pork at slaughterhouse, which could contribute to increasing the food safety of pork products.

In this paper we consider the stationary Poisson Boolean model with spherical grains and propose a family of nonparametric estimators for the radius distribution. These estimators are based on observed distances and radii, weighted in an appropriate way. They are ratio unbiased and asymptotically consistent for a growing observation window. We show that the asymptotic variance exists and is given by a fairly explicit integral expression. Asymptotic normality is established under a suitable integrability assumption on the weight function. We also provide a short discussion of related estimators as well as a simulation study.