Modelling characteristics to predict Legionella contamination risk - Surveillance of drinking water plumbing systems and identification of risk areas

We discovered high variability (up to 4 log10 steps) in the presence of Legionella spp. (CFU/100 mL) within all buildings over a half year period as well as over the course of a day. Occurrences were significantly correlated with temperature, pipe length measures, and stagnation. Logistic regression modelling revealed three parameters (temperature after flushing until no significant changes in temperatures can be obtained, stagnation (low withdrawal, qualitatively assessed), pipe length proportion) to be the best predictors of Legionella contamination (>100 CFU/100 mL) at single outlets (precision = 66.7%; accuracy = 72.1%; F0.5 score = 0.59).