Combining Case-Control and Source Attribution Data: A Way to Reconstruct Campy's Journey Along the Transmission Chain

Combined case-control and Multilocus Sequence Typing (MLST)-based source attribution analysis allows investigation of risk factors at the point of exposure for human campylobacteriosis attributable to specific reservoirs. Successful applications of this analysis are available for the Netherlands and Luxembourg, where source-specific risk factors for human campylobacteriosis of poultry, ruminant (cattle/sheep), environmental (water/sand/wild birds), pet (dogs/cats) and exotic (travel-related) origin were identified. Nationally representative collections of Campylobacter jejuni and C. coli isolates from these animals and from human cases included in case-control studies were typed using MLST. The asymmetric island model was the used to estimate the probability for the different sequence types (STs) found in human cases to originate from each of the considered reservoirs. Cases were then split according to their attributed reservoirs. Reservoir-specific risk factors were investigated using logistic regression analysis. Both in the Netherlands and in Luxembourg, most cases (>85%) were attributed to chicken and ruminants. Chicken consumption increased the risk of infection with chicken-attributed Campylobacter STs, whereas consuming beef and pork appeared to be protective. Contact with animals, garden soil, barbequing, tripe consumption, and never/seldom chicken consumption were risk factors for ruminant-attributed infections. Game meat consumption and swimming in household pools increased the risk for environment-attributed infections. Dog ownership increased the risk for environment- and pet-attributed infections. Person-to-person contacts around holidays were risk factors for domestic infections with exotic STs, introduced by returning travellers. Based on these studies, it can be concluded that individuals acquiring campylobacteriosis from different reservoirs have different risk factors, the identification and characterization which allow public health messages to be targeted more effectively. While the outcome of classical case-control studies can be enhanced by incorporating source attribution data, identifying source-specific risk factors also allows us to infer the underlying transmission pathways, from the original reservoir to the level of exposure.