This thesis provides knowledge on factors affecting the representativeness of wastewater-based epidemiology (WBE) for monitoring the SARS-CoV-2 virus. The application of WBE to monitor health parameters has become essential due to the COVID-19 outbreak in March 2020. WBE is a well-known method to track the SARS-CoV-2 virus in wastewater and is used as an early warning system for the spread of the virus. However, the accuracy of monitoring trends through WBE is affected by various methodological challenges. This thesis aims to identify and quantify factors that affect the representativeness of monitoring the SARS-CoV-2 virus through WBE as part of the National Sewage Surveillance (NRS).

Factors that possibly influence the representativeness of WBE for monitoring the SARS-CoV-2 virus from loo to lab are identified. To what extent these factors potentially affect the representativeness is discussed in a literature review. The results are presented in a dendrogram, showing the relationship between different factors. Based on the results of the literature review, the seven most important factors affecting the accuracy of monitoring SARS-CoV-2 through WBE were determined to investigate their effect in more detail. To create an overview of the effect of the various factors and to ensure comparison, the results of the different factors are synthesized based on four criteria.

The effect on the representativeness is quantified and synthesized for the following factors: location of shedding, temporary in-sewer storage, RNA decay, deviant flow values, loss of information by overflow events, automated samplers and flow rate measurements. The effect of each factor is quantified individually. Different methodologies were used for the quantification of the different factors. The results were based on data analysis and expert consultations.

It was observed that the effect on the load of SARS-CoV-2 monitored by temporary in-sewer storage is negligible, as well as the effect by the decay of SARS-CoV-2 RNA by temperature and residence time. For the following factors, the influence on representativeness may be significant: The location of shedding, deviant flow values, loss of information by overflow events, automated samplers and flow rate measurements. Based on the results of the synthesis an advice is given on which factors should be included in the methodology of monitoring the virus through WBE and which samples should be excluded.

In conclusion, WBE is a valuable method to use for pandemic preparedness and monitoring health indicators from wastewater. There are many factors that influence the representativeness of samples for the monitoring of the SARS-CoV-2 virus. This research adds knowledge to the understanding of factors influencing the accuracy of WBE. The results elaborated by this study hope to contribute to the early detection of, not only, the SARS-CoV-2 virus, but also for other epidemic viruses, as well as other health indicators.