Dataset Information

Scaling SARS-CoV-2 wastewater concentrations to population estimates of infection.

ABSTRACT: 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.

SUBMITTER: Kaplan EH

PROVIDER: S-EPMC8894397 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Scaling SARS-CoV-2 wastewater concentrations to population estimates of infection.

Kaplan Edward H EH Zulli Alessandro A Sanchez Marcela M Peccia Jordan J

Scientific reports 20220303 1

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 co ...[more]

PMID: 35241744

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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

Project description:Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the SARS-CoV-2 levels in the communities since the COVID-19 outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater can be critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (pMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated for their utility in normalizing the SARS-CoV-2 loads through developed direct and indirect approaches. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performed candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuated population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population at any given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation ( rho =0.5878, p <0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker offers an excellent alternative to the currently CDC-recommended pMMoV genetic biomarker to help us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.Highlight bullet pointsThe paraxanthine (PARA), the metabolite of the caffeine, is a more reliable population biomarker in SARS-CoV-2 wastewater-based epidemiology studies than the currently recommended pMMoV genetic marker.SARS-CoV-2 load per capita could be directly normalized using the regression functions derived from correlation between paraxanthine and population without flowrate and population data.Normalizing SARS-CoV-2 levels with the chemical marker PARA significantly improved the correlation between viral loads per capita and case numbers per capita.The chemical marker PARA demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater.

Project description:Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) levels in the communities since the coronavirus disease 2019 (COVID-19) outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater is critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (PMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated and validated for their utility in normalizing the SARS-CoV-2 loads through two normalizing approaches using the data from 64 wastewater treatment plants (WWTPs) in Missouri. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performing candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuating population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population of the given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation (rho=0.5878, p < 0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker complements the current normalization scheme recommended by CDC and helps us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

Dataset Information

Scaling SARS-CoV-2 wastewater concentrations to population estimates of infection.

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Scaling SARS-CoV-2 wastewater concentrations to population estimates of infection.

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