The number of identified listeriosis outbreaks has increased since the sequence typing of Listeria monocytogenes isolates was established in Germany. Due to the nature of the disease, listeriosis outbreaks are difficult to solve. We present investigational tracing as a simple and rapid method to conduct outbreak investigations. The method was applied in 2019 to stop a prolonged listeriosis outbreak in Germany. The starting point for the investigational tracing was nine health care facilities (HCF). Single cases developed listeriosis while they were staying at the nine facilities. Data were collected from companies that delivered foods to HCF and from ready-to-eat (RTE) foods that were consumed there. Following a step-wise approach, data analysis identified similarities in the food supply of the HCF. Food data were heterogeneous and needed to be standardised. Own brands and changing article numbers were challenging aspects during the identification of manufacturers. The analysis of the delivering companies revealed no similarities. Detailed information about the consumed risk foods for Listeria contamination became available for six HCF. All facilities served a wide variety of cold cut meat products to their in-patients. Investigational tracing revealed that only meat products from one out of 29 food business operators had been consumed in all six HCF. Further activities of the authorities enabled the identification of the outbreak strain on food products and in the processing environment of this company. A product recall and the measures taken stopped the listeriosis outbreak. Thus, investigational tracing can be crucial for the clarification of listeriosis outbreaks.
This report describes the framework of collection, management and transmission of food safety data in the Federal Republic of Germany. To adjust optimally the data governance processes to the requirements defined by the EFSA, measures had been agreed upon in order to improve the specified situation. Subsequent methodological system enhancements related to data quality are given as well as structural adjustments and the development and implementation of supporting processes. Results of the implementations of the measures mentioned above are presented, and conclusions and recommendations which will be important for the further implementation process are listed.
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