Tristan Schadron ^1* Maaike J. Van Den Beld ¹ Lapo Mughini Gras ^1,2 Eelco Franz ¹

• ¹ Centre for Infectious Disease Control, National Institute for Public Health and the Environment (Netherlands), Bilthoven, Netherlands
• ² Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands, Netherlands

Improvements in sequencing quality, availability, speed and costs results in an increased presence of genomics in infectious disease applications. Nevertheless, there are still hurdles in regards to the optimal use of WGS for public health purposes. Here, we discuss the current state ("status quo") and future directions ("quo vadis") based on literature regarding the use of genomics in surveillance, hazard characterization and source attribution of foodborne pathogens. The future directions include the application of new techniques, such as machine learning and network approaches that may overcome the current shortcomings. These include the use of fixed genomic distances in cluster delineation, disentangling similarity or lack thereof in source attribution, and difficulties ascertaining function in hazard characterization. Although, the aforementioned methods can relatively easily be applied technically, an overarching challenge is the inference and biological/epidemiological interpretation of these large amounts of high resolution data. Understanding the context in terms of bacterial isolate and host diversity allows to assess the level of representativeness in regard to sources and isolates in the dataset, which in turn defines the level of certainty associated with defining clusters, sources and risks. This also marks the importance of metadata (clinical, epidemiological and biological) when using genomics for public health purposes.