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. 2021 Jun 25:775:145790.
doi: 10.1016/j.scitotenv.2021.145790. Epub 2021 Feb 12.

Correlation of SARS-CoV-2 RNA in wastewater with COVID-19 disease burden in sewersheds

Jennifer Weidhaas  1 , Zachary T Aanderud  2 , D Keith Roper  3 , James VanDerslice  4 , Erica Brown Gaddis  5 , Jeff Ostermiller  5 , Ken Hoffman  5 , Rubayat Jamal  6 , Phillip Heck  7 , Yue Zhang  8 , Kevin Torgersen  2 , Jacob Vander Laan  5 , Nathan LaCross  9
Affiliations

Correlation of SARS-CoV-2 RNA in wastewater with COVID-19 disease burden in sewersheds

Jennifer Weidhaas et al. Sci Total Environ. .

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease (COVID-19), is shed in feces and the viral ribonucleic acid (RNA) is detectable in wastewater. A nine-week wastewater epidemiology study of ten wastewater facilities, serving 39% of the state of Utah or 1.26 M individuals was conducted in April and May of 2020. COVID-19 cases were tabulated from within each sewershed boundary. RNA from SARS-CoV-2 was detectable in 61% of 126 wastewater samples. Urban sewersheds serving >100,000 individuals and tourist communities had higher detection frequencies. An outbreak of COVID-19 across two communities positively correlated with an increase in wastewater SARS-CoV-2 RNA, while a decline in COVID-19 cases preceded a decline in RNA. SARS-CoV-2 RNA followed a first order decay rate in wastewater, while 90% of the RNA was present in the liquid phase of the influent. Infiltration and inflow, virus decay and sewershed characteristics should be considered during correlation analysis of SAR-CoV-2 with COVID-19 cases. These results provide evidence of the utility of wastewater epidemiology to assist in public health responses to COVID-19.

Keywords: COVID-19; Disease burden; Interceptor; SARS-CoV-2 RNA; Sewershed; Wastewater epidemiology.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Unlabelled Image
Graphical abstract
Fig. 1
Fig. 1
Location of wastewater treatment plants sampled during this study, representing 1.26 M individuals or 39% of Utah's population.
Fig. 2
Fig. 2
Average and standard deviation of SARS-CoV-2 million viral GC/capita/day in wastewater (grey bars) compared to weekly COVID-19 case rate per 100,000 (red lines). Vertical dashed lines indicate the first week of sampling. Estimated detection limits for SARS-CoV-2 is 3 GC/mL or 1.2 ± 0.5 MVGC/cap/d for all facilities monitored. Note that the cases/100 K do not include data from asymptomatic or pre-symptomatic SARS-CoV-2 shedders. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 3
Fig. 3
Correlations between daily (plot A) or weekly (plots B, C, D) COVID-19 cases or cases/100 K and SARS-CoV-2 million viral gene copies/capita/day in a sewershed. Plot D shows the 1-week lag in COVID-19 cases in ECWRF compared to the prior week SARS-CoV-2 RNA. Spearman correlations and 95% prediction intervals (dashed line) on the linear regressions (solid line) are shown in each figure.
Fig. 4
Fig. 4
Estimated sum of SARS-CoV-2 shedding individuals in sewersheds over the study period compared to the sum of confirmed COVID-19 cases.
Fig. 5
Fig. 5
Observed decay (symbols) of SARS-CoV-2 RNA in wastewater during storage at 4, 10 or 35 °C and predicted first order decay rates (lines). Virus signal was not detectable after 12 h of storage at 35 °C. The grey area indicates the data used to estimate the first order decay rates. Correlation coefficients exceeded 95%.
Fig. 6
Fig. 6
Intra laboratory comparison of replicate filter extractions and triplicate qPCR assays. Bonferroni grouping of least square means (alpha = 0.05). Mean estimated gene copies/mL by filter, with the same letter are not significantly different. OWRF: significant difference in means among filters (GLM, P < 0.001, F = 9.52). CVWRF: No significant difference in means among filters (GLM, P = 0.023, F = 3.1). SLCWRF: No significant difference in means among filters (GLM, P = 0.024, F = 4.51).
Fig. 7
Fig. 7
SARS-CoV-2 RNA in the sewer interceptors feeding CVWRF influenced by flow rates (plot A) and without considering flow rates (plot B), and correlation between SARS-CoV-2 million viral gene copies/capita/day in wastewater as compared to rolling 3-day average COVID-19 case counts in the cities contributing to CVWRF (plot C).
Fig. 8
Fig. 8
Effect of flow rates on relationship between SARS-CoV-2 million viral gene copies/capita/day or gene copies/mL wastewater. Plot A: eight facilities sampled with more than two detections of the virus RNA. Inset B: variation in the ECWRF flows. Plot C: sub-sewersheds feeding CVWRF as compared to the influent into the main plant (bold black line).
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