Informing surveillance programmes by investigating spatial dependency of subclinical Salmonella infection

• Published in: Epidemiology and infection 2009-09, Vol.137 (9), p.1348-1359
• Main Authors: BENSCHOP, J., STEVENSON, M. A., DAHL, J., MORRIS, R. S., FRENCH, N. P.
• Format: Article
• Language: English
• Subjects: Aggregation; Animals; Bacteria; Bacterial diseases; Bacterial diseases of the digestive system and abdomen; Biological and medical sciences; Cluster Analysis; Denmark - epidemiology; Farms; Fundamental and applied biological sciences. Psychology; Herds; Human bacterial diseases; Infectious diseases; K function; Medical sciences; Microbiology; Pig farms; Population Surveillance - methods; Salmonella; Salmonella infections; Salmonella Infections, Animal - epidemiology; Seroepidemiologic Studies; spatial; Spatial dependencies; Surveillance; Sus scrofa; Swine; Swine Diseases - epidemiology; variogram; Veterinary medicine
• ISSN: 0950-2688; 1469-4409
• DOI: 10.1017/S0950268809002106

The aim of this paper is to investigate local spatial dependency with regard to Salmonella seropositivity in data from the Danish swine salmonellosis control programme and its application in informing surveillance strategies. We applied inhomogeneous and observed-difference K-function estimation, and geo-statistical modelling to data from the Danish swine salmonellosis control programme. Slaughter-pig farm density showed large variation at both the country-wide and local level in Denmark (median 0·23, range 0·02–0·47 farms/km2). The spatial distribution of pig farms followed a random inhomogeneous Poisson process but was not aggregated. We found evidence for aggregation of Salmonella case farms over that of all farms at distances of up to 6 km and semivariogram analyses of Salmonella seropositivity revealed spatial dependency between pairs of farms up to 4 km apart. The strength of the spatial dependency was positively associated with slaughter-pig farm density. We proposed sampling more intensively those farms within a 4 km radius of farms that were identified with a high Salmonella status, and reduced sampling of farms that are within this radius of ‘Salmonella-free’ farms. Our approach has the potential to optimize sampling strategies while maintaining consumer confidence in food safety and also has potential to be used for other zoonotic disease surveillance systems.