Over the course of the Corona Virus Disease-19 (COVID-19) pandemic in 2020–2022, monitoring of the severe acute respiratory syndrome coronavirus 2 ribonucleic acid (SARS-CoV-2 RNA) in wastewater has rapidly evolved into a supplementary surveillance instrument for public health. Short term trends (2 weeks) are used as a basis for policy and decision making on measures for dealing with the pandemic. Normalisation is required to account for the dilution rate of the domestic wastewater that can strongly vary due to time- and location-dependent sewer inflow of runoff, industrial discharges and extraneous waters. The standard approach in sewage surveillance is normalisation using flow measurements, although flow based normalisation is not effective in case the wastewater volume sampled does not match the wastewater volume produced. In this paper, two alternative normalisation methods, using electrical conductivity and crAssphage have been studied and compared with the standard approach using flow measurements. For this, a total of 1116 24-h flow-proportional samples have been collected between September 2020 and August 2021 at nine monitoring locations. In addition, 221 stool samples have been analysed to determine the daily crAssphage load per person. Results show that, although crAssphage shedding rates per person vary greatly, on a population-level crAssphage loads per person per day were constant over time and similar for all catchments. Consequently, crAssphage can be used as a quantitative biomarker for populations above 5595 persons. Electrical conductivity is particularly suitable to determine dilution rates relative to dry weather flow concentrations. The overall conclusion is that flow normalisation is necessary to reliably determine short-term trends in virus circulation, and can be enhanced using crAssphage and/or electrical conductivity measurement as a quality check.

Despite high vaccination rates in the Netherlands, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to circulate. Longitudinal sewage surveillance was implemented along with the notification of cases as two parts of the surveillance pyramid to validate the use of sewage for surveillance, as an early warning tool, and to measure the effect of interventions. Sewage samples were collected from nine neighborhoods between September 2020 and November 2021. Comparative analysis and modeling were performed to understand the correlation between wastewater and case trends. Using high resolution sampling, normalization of wastewater SARS-CoV-2 concentrations, and ‘normalization’ of reported positive tests for testing delay and intensity, the incidence of reported positive tests could be modeled based on sewage data, and trends in both surveillance systems coincided. The high collinearity implied that high levels of viral shedding around the onset of disease largely determined SARS-CoV-2 levels in wastewater, and that the observed relationship was independent of variants of concern and vaccination levels. Sewage surveillance alongside a large-scale testing effort where 58 % of a municipality was tested, indicated a five-fold difference in the number of SARS-CoV-2-positive individuals and reported cases through standard testing. Where trends in reported positive cases were biased due to testing delay and testing behavior, wastewater surveillance can objectively display SARS-CoV-2 dynamics for both small and large locations and is sensitive enough to measure small variations in the number of infected individuals within or between neighborhoods. With the transition to a post-acute phase of the pandemic, sewage surveillance can help to keep track of re-emergence, but continued validation studies are needed to assess the predictive value of sewage surveillance with new variants. Our findings and model aid in interpreting SARS-CoV-2 surveillance data for public health decision-making and show its potential as one of the pillars of future surveillance of (re)emerging viruses.

An outbreak of SARS-CoV-2 Alpha variant (Pango lineage B.1.1.7) was detected at a primary school (School X) in Lansingerland, the Netherlands, in December 2020. The outbreak was studied retrospectively, and population-based screening was used to assess the extent of virus circulation and decelerate transmission. Cases were SARS-CoV-2 laboratory confirmed and were residents of Lansingerland (November 16th 2020 until February 22th 2021), or had an epidemiological link with School X or neighbouring schools. The SARS-CoV-2 variant was determined using variant PCR or whole genome sequencing. A questionnaire primarily assessed clinical symptoms. A total of 77 Alpha variant cases were found with an epidemiological link to School X, 16 Alpha variant cases linked to the neighbouring schools, and 146 Alpha variant cases among residents of Lansingerland without a link to the schools. The mean number of self-reported symptoms was not significantly different among Alpha variant infected individuals compared to non-Alpha infected individuals. The secondary attack rate (SAR) among Alpha variant exposed individuals in households was 52% higher compared to non-Alpha variant exposed individuals (p = 0.010), with the mean household age, and mean number of children and adults per household as confounders. Sequence analysis of 60 Alpha variant sequences obtained from cases confirmed virus transmission between School X and neighbouring schools, and showed that multiple introductions of the Alpha variant had already taken place in Lansingerland at the time of the study. The alpha variant caused a large outbreak at both locations of School X, and subsequently spread to neighbouring schools, and households. Population-based screening (together with other public health measures) nearly stopped transmission of the outbreak strain, but did not prevent variant replacement in the Lansingerland municipality.