Journal
ACS ES&T WATER
Volume 1, Issue 8, Pages 1955-1965Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acsestwater.1c00160
Keywords
SARS-CoV-2; wastewater; RT-ddPCR; bovine coronavirus; pepper mild mottle virus; HF183; COVID-19 cases
Categories
Funding
- Wisconsin Department of Health Services through the CARES Act
- Milwaukee Metropolitan Sewerage District
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Wastewater surveillance for SARS-CoV-2 can help assess infection burden, but measurement variability and its relationship to case data need to be considered. Research showed that a minimum of two samples collected per week were needed to maintain accuracy in trend analysis.
Wastewater surveillance for SARS-CoV-2 provides an approach for assessing the infection burden across a sewer service area. For these data to be useful for public health, measurement variability and the relationship to case data need to be established. We determined SARS-CoV-2 RNA concentrations in the influent of 12 wastewater treatment plants from August 2020 to January 2021. Technical replicates for N1 gene concentrations showed a relative standard deviation of 24%, suggesting it is possible to track relatively small (similar to 30%) changes in SARS-CoV-2 concentrations over time. COVID-19 cases were correlated significantly (rho >= 0.70) to wastewater SARS-CoV-2 RNA concentrations across large and small service areas, with weaker relationships (rho >= 0.59) in two communities. SARS-CoV-2 concentrations normalized to per capita slightly improved correlations to COVID-19 incidence, but normalizing to a spiked recovery control (BCoV) or a fecal marker (PMMoV or HF183) reduced correlations for a number of plants. Daily sampling demonstrated that a minimum of two samples collected per week were needed to maintain accuracy in trend analysis. The differences in the strength of SARS-CoV-2 relationships to COVID-19 incidence and the effect of normalization on these data among communities demonstrate that rigorous validation should be performed at individual sites where wastewater surveillance programs are implemented.
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