SARS-CoV-2 concentrations in a wastewater collection system indicated potential COVID-19 hotspots at the zip code level.
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ABSTRACT:
SUBMITTER: Barrios RE
PROVIDER: S-EPMC8330136 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Monitoring the progression of SARS-CoV-2 outbreaks requires accurate estimation of the unobservable fraction of the population infected over time in addition to the observed numbers of COVID-19 cases, as the latter present a distorted view of the pandemic due to changes in test frequency and coverage over time. The objective of this report is to describe and illustrate an approach that produces representative estimates of the unobservable cumulative incidence of infection by scaling the daily concentrations of SARS-CoV-2 RNA in wastewater from the consistent population contribution of fecal material to the sewage collection system.
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Project description:There are only a few established methods to determine the concentration of encapsulated viruses, such as SARS-CoV-2, in water matrices, limiting the application of wastewater-based epidemiology (WBE)—an important tool for public health research. The present study compared four methods that are commonly used to concentrate non-encapsulated enteric viruses for determining SARS-CoV-2 concentration in wastewater and wastewater-enriched river water samples. The four methods tested were electronegative membrane with Mg+2 addition, aluminum hydroxide-based precipitation, polyethylene glycol (PEG) 8000 precipitation, and ultrafiltration (with porosity of 10 and 50 kDa). Prior to the concentration step, filtration or centrifugation was performed to remove suspended particles from the samples (pretreatment). To evaluate the recovery efficiency (%), samples of SARS-CoV-2 from nasopharyngeal swabs obtained from RT-qPCR-positive patients were used as spiked samples. The second part of the analysis involved the quantification of the SARS-CoV-2 copy number in analytes without SARS-CoV-2-spiked samples. Among the tested methods, pretreatment via centrifugation followed by ultrafiltration with a 50-kDa cut-off was found the most efficient method for wastewater samples with spiked samples (54.3 or 113.01% efficiency). For the wastewater-enriched river samples with spiked samples, pretreatment via centrifugation followed by filtration using an electronegative membrane was the most efficient method (110.8% and 95.9% for N1 and N2 markers, respectively). However, ultrafiltration of the raw river water samples using 10 or 50 kDa cut-off filters and PEG 8000 precipitation showed the best concentration efficiency based on copy number, regardless of the pretreatment approach or sample type (values ranging from 3 × 105 to 6.7 × 103). The effectiveness of the concentration method can vary depending on the type of sample and concentration method. We consider that this study will contribute to more widespread use of WBE for the environmental surveillance of SARS-CoV-2. Graphical abstract Image 1
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for causing the COVID-19 pandemic, can be detected in untreated wastewater. Wastewater surveillance of SARS-CoV-2 complements clinical data by offering earlier community-level detection, removing underlying factors such as access to healthcare, sampling asymptomatic patients, and reaching a greater population. Here, we compare 24-hour composite samples from the influents of two different wastewater treatment plants (WWTPs) in South Carolina, USA: Columbia and Rock Hill. The sampling intervals span the months of July 2020 and January 2021, which cover the first and second waves of elevated SARS-CoV-2 transmission and COVID-19 clinical cases in these regions. We identify four signature mutations in the surface glycoprotein (spike) gene that are associated with the following variants of interest or concern, VOI or VOC (listed in parenthesis): S477N (B.1.526, Iota), T478K (B.1.617.2, Delta), D614G (present in all VOC as of May 2021), and H655Y (P.1, Gamma). The N501Y mutation, which is associated with three variants of concern, was identified in samples from July 2020, but not detected in January 2021 samples. Comparison of mutations identified in viral sequence databases such as NCBI Virus and GISAID indicated that wastewater sampling detected mutations that were present in South Carolina, but not reflected in the clinical data deposited into databases.
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Project description:We assessed the added value and limitations of generating directly estimated ZIP Code-level estimates by aggregating 5 years of data from an annual cross-sectional survey, the New York City Community Health Survey (n = 44,886) from 2009 to 2013, that were designed to provide reliable estimates only of larger geographies. Survey weights generated directly-observed ZIP Code (n = 128) level estimates. We assessed the heterogeneity of ZIP Code-level estimates within coarser United Hospital Fund (UHF) neighborhood areas (n = 34) by using the Rao-Scott Chi-Square test and one-way ANOVA. Orthogonal linear contrasts assessed whether there were linear trends at the UHF level from 2009 to 2013. 22 of 37 health indicators were reliable in over 50% of ZIP Codes. 14 of the 22 variables showed heterogeneity in ≥4 UHFs. Variables for drinking, nutrition, and HIV testing showed heterogeneity in the most UHFs (9-24 UHFs). In half of the 32 UHFs, >20% variables had within-UHF heterogeneity. Flu vaccination and sugary beverage consumption showed significant time trends in the largest number of UHFs (12 or more UHFs). Overall, heterogeneity of ZIP Code-level estimates suggests that there is value in aggregating 5 years of data to make direct small area estimates.
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Project description:Estimating total infection levels, including unreported and asymptomatic infections, is important for understanding community disease transmission. Wastewater can provide a pooled community sample to estimate total infections that is independent of case reporting biases toward individuals with moderate to severe symptoms and by test-seeking behavior and access. We derive three mechanistic models for estimating community infection levels from wastewater measurements based on a description of the processes that generate SARS-CoV-2 RNA signals in wastewater and accounting for the fecal strength of wastewater through endogenous microbial markers, daily flow, and per-capita wastewater generation estimates. The models are illustrated through two case studies of wastewater data collected during 2020-2021 in Virginia Beach, VA, and Santa Clara County, CA. Median simulated infection levels generally were higher than reported cases, but at times, were lower, suggesting a discrepancy between the reported cases and wastewater data, or inaccurate modeling results. Daily simulated infection estimates showed large ranges, in part due to dependence on highly variable clinical viral fecal shedding data. Overall, the wastewater-based mechanistic models are useful for normalization of wastewater measurements and for understanding wastewater-based surveillance data for public health decision-making but are currently limited by lack of robust SARS-CoV-2 fecal shedding data.
| S-EPMC10911093 | biostudies-literature
Project description:The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.
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Project description:This study presents the results of systematic wastewater monitoring of SARS-CoV-2 RNA and basic wastewater parameters from four different wastewater treatment plants (WWTPs) in the Czech Republic over the 2020-2022 epidemic. Two-step reverse-transcription quantitative PCR targeting genes encoding the N and Nsp12 proteins was employed to detect SARS-CoV-2 RNA loading in 420 wastewater samples. The results obtained were used to evaluate the potential of wastewater analysis for describing the epidemiological situation in cities of different sizes and determining temporal differences based on the prevailing SARS-CoV-2 variant. Strong correlations between the number of active and hospitalised COVID-19 cases in each WWTP catchment area and the concentration of SARS-CoV-2 RNA detected in the wastewater clearly demonstrated the suitability of this wastewater-based epidemiological approach for WWTPs of different sizes and characteristics, despite differences in SARS-CoV-2 variant waves, with some WWTPs showing high predictive potential. This study demonstrated on the data from the Czech Republic that targeted systematic monitoring of wastewater provides sufficiently robust data for surveillance of viral loads in sample populations, and thus contributes to preventing the spread of infection and subsequent introduction of appropriate measures.
| S-EPMC11017050 | biostudies-literature
Project description:SARS-CoV-2 RNA loads can be detected in the excreta of individuals with COVID-19 and have demonstrated positive correlations with clinical infection trends. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor community-level prevalence of infections. The majority of wastewater specimens are gathered as either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and can be challenging to maintain in cold weather, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Passive sampling can provide an affordable, practical, and scalable sampling system while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from 1 February 2021-21 May 2021. Samples (n = 64) were collected 3-5 times weekly and remained within the sewer for a median duration of 24 h. SARS-CoV-2 RNA was quantified using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) targeting the N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform building-level public health responses.
| S-EPMC9517461 | biostudies-literature
Project description:SARS-CoV-2 RNA can be detected in the excreta of individuals with COVID-19 and has demonstrated a positive correlation with various clinical parameters. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor the community-level prevalence of infections. Over 270 higher education campuses monitor wastewater for SARS-CoV-2, with most gathering either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and challenging to manage with seasonal variability, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Prior studies have demonstrated encouraging results utilizing passive sampling swabs. Such methods can offer affordable, practical, and scalable alternatives to traditional methods while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from February 1, 2021 â€" May 21, 2021. Samples were collected several times weekly and remained within the sewer for a minimum of 24 hours (n = 64). SARS-CoV-2 RNA was quantified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) targeting the viral N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform public health responses in a range of settings.HighlightsDaily SARS-CoV-2 RNA loads in building-level wastewater were positively associated with the total number of COVID-19 positive individuals in the residenceThe variation in individual fecal shedding rates of SARS-CoV-2 extended four orders of magnitudeWastewater sample replicates were highly correlated using distinct processing pipelines in two independent laboratoriesWhile the isolation residence was occupied, SARS-CoV-2 RNA was detected in all passive samples.
| S-EPMC9016645 | biostudies-literature
Project description: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.
| S-EPMC9791714 | biostudies-literature