A multiple logistic model for predicting the occurrence of Campylobacter jejuni and Campylobacter coli in water

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Abstract
A multiple logistic regression model was established to predict the occurrence of Campylobacter jejuni/coli, related to index bacteria such as faecal coliforms, faecal streptococci, and sulphite-reducing clostridia, in a water source in southern Norway. The fitted model indicated that faecal coliforms were strong predictors for C. jejuni/coli, although the water temperature also had a strong influence on results. Sulphite-reducing clostridia, faecal streptococci, and season of the year had no significant influence on the results, in spite of their apparent predictor value as separate variables. The model employed offers a new approach to the relationship between index bacteria and the occurrence of pathogenic bacteria in water. Similar models can also be established in general food microbiology.