THE USE OF ALTERNATIVE NORMALIZATION APPROACHES TO UNDERSTAND CHANGES IN SARS-CoV-2 CONCENTRATIONS IN WASTEWATER

Following the detection of SARS-CoV-2 RNA fragments in wastewater in March 2020, the use of wastewater-based epidemiology is rapidly emerging as a non-invasive approach to assessing community wide COVID-19 prevalence. Wastewater-based epidemiology is promoted as a complement to clinical testing in terms of improving public health authorities’ preparedness and supporting them in taking required interventions to protect the public health. To utilize the occurrence of SARS-CoV-2 in wastewater in a public health context and evaluate trends in viral prevalence on a community level, robust data interpretation is required. This master's thesis work examines what is currently known about the factors that influence the concentrations of SARS-CoV-2 in wastewater, as well as the impact of alternative normalization approaches on the relationship between viral wastewater data and clinical case numbers. The work is divided into two parts where this report provides a state-of-the-art review as well as an overview of key findings in the accompanied scientific paper. The study involved collection of wastewater samples from two different sized wastewater treatment plants (WWTPs) in Luleå municipality, between January and March 2021. Concentrations of SARS-CoV-2 RNA were quantified in each sample as well as concentrations of total nitrogen (TN), total phosphorus (TP) and pepper mild mottle virus (PMMoV). Average daily WWTP flow and environmental data (precipitation and temperature) were continuously measured over the sampling period. The population size was estimated based on mass loads of TN and TP and literature values of the domestic contribution of these parameters to the sewer system. The viral wastewater data was normalized using the estimations of population size, census data, WWTP flow and PMMoV. The impact of the alternative normalization approaches was evaluated using statistical analyses to explore the relationship to clinical case numbers. The result showed that the strength of the correlation between the different normalization approaches and clinical case data differed between the WWTPs. However, within each WWTP the differences in correlation between the different normalization approaches and clinical cases were not significant. Moreover, normalization using WWTP flow (i.e., viral loads) showed a stronger correlation to clinical cases compared to population and PMMoV normalized viral loads. However, when comparing wastewater data between the two catchment areas, the normalization approaches utilizing population (either census or TN and TP estimated population) or PMMoV better reflect the number of clinical cases. Additionally, according to time-shifted analysis, wastewater data of SARS-CoV-2 RNA predated an increase in clinical cases by 0-2 and 5-8 days, respectively, for the larger and smaller WWTPs.