Within- and between-Day Variability of SARS-CoV-2 RNA in Municipal Wastewater during Periods of Varying COVID-19 Prevalence and Positivity
10 Sep 2021-Vol. 1, Iss: 9, pp 2097-2108
TL;DR: Recovery-corrected SARS-CoV-2 RNA concentrations in primary influent indicate diurnal loading patterns and confirm monitoring dependent on grab samples should target daytime periods with high fecal loading, and large variation both within- and between-days may preclude robust quantitative analyses beyond correlation.
Abstract: Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is being used to monitor Coronavirus Disease 2019 (COVID-19) trends in communities;however, within- and between-day variation of SARS-CoV-2 RNA concentration in primary influent remains largely uncharacterized. In the current study, grab sampling of primary influent was performed every 2 h over two 24-h periods at two wastewater treatment plants (WWTPs) in northern Indiana, USA. The recovery efficiency of endogenous SARS-CoV-2 RNA in wastewater was confirmed to be similar to the recovery efficiency of the process control, bovine respiratory syncytial virus (BRSV). Recovery-corrected SARS-CoV-2 RNA concentrations in primary influent indicate diurnal loading patterns and confirm monitoring dependent on grab samples should target daytime periods with high fecal loading. Importantly, manual compositing performed at the WWTP resulted in concentrations that were consistently lower than grab sample averages indicating potential bias. Uncorrected, recovery-corrected, and pepper mild mottle virus (PMMoV)-normalized SARS-CoV-2 RNA concentrations demonstrated an ordinal agreement with increasing clinical COVID-19 positivity but not COVID-19 cases. In areas where geolocated COVID-19 case data are not available, the COVID-19 positivity rate could provide a useful county-level metric for comparison with wastewater. Nonetheless, large variation both within- and between-days may preclude robust quantitative analyses beyond correlation.
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Commonwealth Scientific and Industrial Research Organisation1, University of Notre Dame2, University of Melbourne3, University of Barcelona4, Instituto Nacional de Saúde Dr. Ricardo Jorge5, Queensland Health6, University of Queensland7, University of North Carolina at Chapel Hill8, University of South Australia9, Michigan State University10, University of Health Sciences Antigua11, Vienna University of Technology12, Southern Nevada Water Authority13, Southern California Coastal Water Research Project14, Drexel University15, Arizona State University16, National Environment Agency17, University of South Florida18, International Centre for Diarrhoeal Disease Research, Bangladesh19, University of New South Wales20, Stellenbosch University21, Hokkaido University22, United States Environmental Protection Agency23, Istituto Superiore di Sanità24, University of Georgia25, University of Wisconsin–Milwaukee26, University College Dublin27, University of Guelph28, University of California, Merced29, Griffith University30, National Institute for Health and Welfare31, University of Helsinki32, National University of Salta33, Spanish National Research Council34, Tulane University35, Chulabhorn Research Institute36, National University of Singapore37, Tohoku University38, Nanyang Technological University39, University of Minnesota40
TL;DR: A technical review of factors that can lead to false-positive and -negative errors in the surveillance of SARS-CoV-2, culminating in recommendations and strategies that can be implemented to identify and mitigate these errors.
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TL;DR: The positivity results indicated that for the analysis of SARS-CoV-2 RNA in wastewater, including the eluate and pellet samples may further increase the detection sensitivity using RT-dPCR.
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Abstract: Let $x$ and $y$ be two random variables with continuous cumulative distribution functions $f$ and $g$. A statistic $U$ depending on the relative ranks of the $x$'s and $y$'s is proposed for testing the hypothesis $f = g$. Wilcoxon proposed an equivalent test in the Biometrics Bulletin, December, 1945, but gave only a few points of the distribution of his statistic. Under the hypothesis $f = g$ the probability of obtaining a given $U$ in a sample of $n x's$ and $m y's$ is the solution of a certain recurrence relation involving $n$ and $m$. Using this recurrence relation tables have been computed giving the probability of $U$ for samples up to $n = m = 8$. At this point the distribution is almost normal. From the recurrence relation explicit expressions for the mean, variance, and fourth moment are obtained. The 2rth moment is shown to have a certain form which enabled us to prove that the limit distribution is normal if $m, n$ go to infinity in any arbitrary manner. The test is shown to be consistent with respect to the class of alternatives $f(x) > g(x)$ for every $x$.
11,055 citations
TL;DR: In this article, a test of the hypothesis that the samples are from the same population may be made by ranking the observations from from 1 to Σn i (giving each observation in a group of ties the mean of the ranks tied for), finding the C sums of ranks, and computing a statistic H. Under the stated hypothesis, H is distributed approximately as χ2(C − 1), unless the samples were too small, in which case special approximations or exact tables are provided.
Abstract: Given C samples, with n i observations in the ith sample, a test of the hypothesis that the samples are from the same population may be made by ranking the observations from from 1 to Σn i (giving each observation in a group of ties the mean of the ranks tied for), finding the C sums of ranks, and computing a statistic H. Under the stated hypothesis, H is distributed approximately as χ2(C – 1), unless the samples are too small, in which case special approximations or exact tables are provided. One of the most important applications of the test is in detecting differences among the population means.* * Based in part on research supported by the Office of Naval Research at the Statistical Research Center, University of Chicago.
9,365 citations
TL;DR: Detailed virological analysis of nine cases of coronavirus disease 2019 (COVID-19) provides proof of active replication of the SARS-CoV-2 virus in tissues of the upper respiratory tract.
Abstract: Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in late 20191,2. Initial outbreaks in China involved 13.8% of cases with severe courses, and 6.1% of cases with critical courses3. This severe presentation may result from the virus using a virus receptor that is expressed predominantly in the lung2,4; the same receptor tropism is thought to have determined the pathogenicity—but also aided in the control—of severe acute respiratory syndrome (SARS) in 20035. However, there are reports of cases of COVID-19 in which the patient shows mild upper respiratory tract symptoms, which suggests the potential for pre- or oligosymptomatic transmission6–8. There is an urgent need for information on virus replication, immunity and infectivity in specific sites of the body. Here we report a detailed virological analysis of nine cases of COVID-19 that provides proof of active virus replication in tissues of the upper respiratory tract. Pharyngeal virus shedding was very high during the first week of symptoms, with a peak at 7.11 × 108 RNA copies per throat swab on day 4. Infectious virus was readily isolated from samples derived from the throat or lung, but not from stool samples—in spite of high concentrations of virus RNA. Blood and urine samples never yielded virus. Active replication in the throat was confirmed by the presence of viral replicative RNA intermediates in the throat samples. We consistently detected sequence-distinct virus populations in throat and lung samples from one patient, proving independent replication. The shedding of viral RNA from sputum outlasted the end of symptoms. Seroconversion occurred after 7 days in 50% of patients (and by day 14 in all patients), but was not followed by a rapid decline in viral load. COVID-19 can present as a mild illness of the upper respiratory tract. The confirmation of active virus replication in the upper respiratory tract has implications for the containment of COVID-19. Detailed virological analysis of nine cases of coronavirus disease 2019 (COVID-19) provides proof of active replication of the SARS-CoV-2 virus in tissues of the upper respiratory tract.
5,840 citations
TL;DR: It is estimated that 44% (95% confidence interval, 25–69%) of secondary cases were infected during the index cases’ presymptomatic stage, in settings with substantial household clustering, active case finding and quarantine outside the home.
Abstract: We report temporal patterns of viral shedding in 94 patients with laboratory-confirmed COVID-19 and modeled COVID-19 infectiousness profiles from a separate sample of 77 infector–infectee transmission pairs. We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% (95% confidence interval, 30–57%) of secondary cases were infected during the index cases’ presymptomatic stage, in settings with substantial household clustering, active case finding and quarantine outside the home. Disease control measures should be adjusted to account for probable substantial presymptomatic transmission. Presymptomatic transmission of SARS-CoV-2 is estimated to account for a substantial proportion of COVID-19 cases.
3,943 citations
TL;DR: In this paper, the use of rank sums from a combined ranking of k independent samples in order to decide which populations differ is suggested as a convenient alternative to making separate rankings for each pair of samples and the two methods are compared.
Abstract: This paper considers the use of rank sums from a combined ranking of k independent samples in order to decide which populations differ. Such a procedure is suggested as a convenient alternative to making separate rankings for each pair of samples, and the two methods are compared. Asymptotic use of the normal tables is given and the treatment of ties is discussed. A numerical example is given.
3,305 citations