Thijs Veenstra

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The aim of the study is to describe the routine inspections conducted by competent Public Health Authorities (PHAs) on board passenger ships (cruise ships, inland vessels or ferries) sailing in European countries during the EU HEALTHY GATEWAYS joint action and according to the hygiene standards set out in the European Manual for Hygiene Standards and Communicable Disease Surveillance on Passenger Ships (Edition 2nd, April 2016). From 2018 to the end of April 2022, 138 inspection reports were submitted by PHAs in 38 ports in SIS by 76 inspectors, three SHIPSAN experts, 16 inspectors in training and 31 observers, along with 130 Corrective Action Statements by shipping companies or officers of ships.

We analysed all proven cases of SARS-CoV-2 on sea-going vessels entering or present in the Port of Rotterdam to illustrate the burden of the corona pandemic on commercial shipping. We calculated the notification rate (NR) per arrival and attack rate per vessel and correlated outbreak sizes by vessel type over time during the pandemic using routinely gathered data from the port and public health (PH) authorities.

Background: A Q-fever outbreak occurred in an urban area in the south of the Netherlands in May 2008. The distribution and timing of cases suggested a common source. We studied the spatial relationship between the residence locations of human cases and nearby small ruminant farms, of which one dairy goat farm had experienced abortions due to Q-fever since mid April 2008. A generic geographic information system (GIS) was used to develop a method for source detection in the still evolving major epidemic of Q-fever in the Netherlands. Methods: All notified Q-fever cases in the area were interviewed. Postal codes of cases and of small ruminant farms (size >40 animals) located within 5 kilometres of the cluster area were geo-referenced as point locations in a GIS-model. For each farm, attack rates and relative risks were calculated for 5 concentric zones adding 1 kilometre at a time, using the 5-10 kilometres zone as reference. These data were linked to the results of veterinary investigations. Results: Persons living within 2 kilometres of an affected dairy goat farm (>400 animals) had a much higher risk for Q-fever than those living more than 5 kilometres away (Relative risk 31.1 [95% CI 16.4-59.1]). Conclusions: The study supported the hypothesis that a single dairy goat farm was the source of the human outbreak. GIS-based attack rate analysis is a promising tool for source detection in outbreaks of human Q-fever.