Whole genome sequencing data used for surveillance of Campylobacter infections: detection of a large continuous outbreak, Denmark, 2019

Background: Campylobacter  is one of the most frequent causes of bacterial gastroenteritis. Campylobacter  outbreaks are rarely reported, which could be a reflection of a surveillance without routine molecular typing. We have previously shown that numerous small outbreak-like clusters can be detected when whole genome sequencing (WGS) data of clinical Campylobacter  isolates was applied. Aim: Typing based surveillance of  Campylobacter  infections was initiated in 2019 to enable detection of large clusters of clinical isolates and to match them to concurrent retail chicken isolates in order to react on ongoing outbreaks. Methods: We performed WGS continuously on isolates from cases (n=701) and chicken meat (n=164) throughout 2019. Core genome multilocus sequence typing was used to detect clusters of clinical isolates and match them to isolates from chicken meat. Results: Seventy-two clusters were detected, 58 small clusters (2–4 cases) and 14 large clusters (5–91 cases). One third of the clinical isolates matched isolates from chicken meat. One large cluster persisted throughout the whole year and represented 12% of all studied  Campylobacter  cases. This cluster type was detected in several chicken samples and was traced back to one slaughterhouse, where interventions were implemented to control the outbreak. Conclusion: Our WGS-based surveillance has contributed to an improved understanding of the dynamics of the occurrence of  Campylobacter  strains in chicken meat and the correlation to clusters of human cases.