Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology

Hsu, Shu-Yu; Bayati, Mohamed; Li, Chenhui; Hsieh, Hsing‐Hung; Belenchia, Anthony; Klutts, Jessica; Zemmer, Sally A.; Reynolds, Melissa M.; Semkiw, Elizabeth; Johnson, Hwei-Yiing; Foley, Trevor; Wieberg, Chris G.; Wenzel, Jeff; Johnson, Marc C.; Lin, Chung‐Ho

doi:10.1016/j.watres.2022.118985

Cited by 46 publications

(28 citation statements)

References 74 publications

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“…There was no significant correlation observed for PMMoV in Ohio (R = 0.03, P-Value = 0.41) and Virginia (R = -0.04, P-Value = 0.47). The moderate correlation observed for PMMoV and the populations in our study was consistent with a study from Missouri which reported a similar correlation (R = 0.36) for PMMoV with the population served in their study [ 21 ]. Other studies have also reported no correlation with the PMMoV concentration and the population served [ 22 , 47 ].…”

Section: Resultssupporting

confidence: 92%

“…Another limitation of our study is that we only investigated three of the CDC NWSS recommended population biomarkers. Many studies across the globe have proposed and investigated other population biomarkers such as β-2 microglobulin, creatinine, 5-hydroxyindoleacetic acid, caffeine, paraxanthine, ammoniacal total nitrogen, and total phosphorous [ 20 , 21 , 51 ]. These endogenous population biomarkers display a low to strong correlation with the population served (R = 0.06–0.8) [ 21 ].…”

Section: Resultsmentioning

confidence: 99%

“…Many studies across the globe have proposed and investigated other population biomarkers such as β-2 microglobulin, creatinine, 5-hydroxyindoleacetic acid, caffeine, paraxanthine, ammoniacal total nitrogen, and total phosphorous [ 20 , 21 , 51 ]. These endogenous population biomarkers display a low to strong correlation with the population served (R = 0.06–0.8) [ 21 ]. Future multi-site studies across vast geographic and temporal space, such as this study, could include other population biomarkers along with flow rate to investigate and identify the most effective WBE population biomarker.…”

Section: Resultsmentioning

confidence: 99%

“…Population normalization factors can be endogenous or exogenous physical, chemical, or biological biomarkers that are analyzed and quantified from a wastewater sample [16][17][18][19]. Examples of previously used population normalization factors used for SARS-CoV-2 WBE are wastewater flow rate, human fecal indicator organisms, electrical conductivity, ammonium, caffeine, paraxanthine, creatinine, and 5-hydroxyindoleacetic acid [20][21][22][23][24][25]. Currently, CDC NWSS recommends wastewater flow rate and human fecal indicator organisms for normalizing SARS-CoV-2 wastewater concentrations for disease trend analysis [26].…”

Section: Introductionmentioning

confidence: 99%

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A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19

et al. 2023

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Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases.

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Section: Resultssupporting

confidence: 92%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19

et al. 2023

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“…Normalisation of SARS-CoV-2 concentrations is required to account for variations in population feeding the sewershed, faecal load and the dilution of domestic wastewater with industrial waste and stormwaters (Hsu et al, 2022 ; Sweetapple et al, 2022 ; Wilde et al, 2022 ). This has been achieved using physical measurements such as flowrate and the quantification of biomarkers such as pharmaceutical and recreational drugs and their metabolites, markers of excretion such ammonia and microorganisms such as cross assembly phage and pepper mild mottle virus (Been et al, 2014 ; Hsu et al, 2022 ; Wilde et al, 2022 ; Wilder et al, 2021 ). In this study, however, we are concerned with the impact of implementing different RT-qPCR assays on data quality.…”

Section: Introductionmentioning

confidence: 99%

The Inhibition and Variability of Two Different RT-qPCR Assays Used for Quantifying SARS-CoV-2 RNA in Wastewater

et al. 2023

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Faecal shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its subsequent detection in wastewater turned the spotlight onto wastewater-based epidemiology (WBE) for monitoring the coronavirus-disease 2019 (COVID-19) pandemic. WBE for SARS-CoV-2 has been deployed in 70 countries, providing insights into disease prevalence, forecasting and the spatiotemporal tracking and emergence of SARS-CoV-2 variants. Wastewater, however, is a complex sample matrix containing numerous reverse transcription quantitative PCR (RT-qPCR) inhibitors whose concentration and diversity are influenced by factors including population size, surrounding industry and agriculture and climate. Such differences in the RT-qPCR inhibitor profile are likely to impact the quality of data produced by WBE and potentially produce erroneous results.To help determine the possible impact of RT-qPCR assay on data quality, two assays employed by different laboratories within the UK’s SARS-CoV-2 wastewater monitoring programme were assessed in the Cefas laboratory in Weymouth, UK. The assays were based on Fast Virus (FV) and qScript (qS) chemistries using the same primers and probes, but at different concentrations and under different cycling conditions. Bovine serum albumin and MgSO4 were also added to the FV assay reaction mixture. Two-hundred and eighty-six samples were analysed, and an external control RNA (EC RNA)-based method was used to measure RT-qPCR inhibition. Compared with qS, FV showed a 40.5% reduction in mean inhibition and a 57.0% reduction in inter-sample inhibition variability. A 4.1-fold increase in SARS-CoV-2 quantification was seen for FV relative to qS; partially due (1.5-fold) to differences in reverse transcription efficiency and the use of a dsDNA standard. Analytical variability was reduced by 51.2% using FV while qS increased the number of SARS-CoV-2 negative samples by 2.6-fold. This study indicates the importance of thorough method optimisation for RT-qPCR-based WBE which should be performed using a selection of samples which are representative of the physiochemical properties of wastewater. Furthermore, RT-qPCR inhibition, analytical variability and reverse transcription efficiency should be key considerations during assay optimisation. A standardised framework for the optimisation and validation of WBE procedures should be formed including concessions for emergency response situations that would allow flexibility in the process to address the difficult balance between the urgency of providing data and the availability of resources.

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Critical Needs for Integrated Surveillance: Wastewater-Based and Clinical Epidemiology in Evolving Scenarios with Lessons Learned from SARS-CoV-2

Carducci,

Federigi,

Lauretani

et al. 2024

Food Environ Virol

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During the COVID-19 pandemic, wastewater-based epidemiology (WBE) and clinical surveillance have been used as tools for analyzing the circulation of SARS-CoV-2 in the community, but both approaches can be strongly influenced by some sources of variability. From the challenging perspective of integrating environmental and clinical data, we performed a correlation analysis between SARS-CoV-2 concentrations in raw sewage and incident COVID-19 cases in areas served by medium-size wastewater treatment plants (WWTPs) from 2021 to 2023. To this aim, both datasets were adjusted for several sources of variability: WBE data were adjusted for factors including the analytical protocol, sewage flow, and population size, while clinical data adjustments considered the demographic composition of the served population. Then, we addressed the impact on the correlation of differences among sewerage networks and variations in the frequency and type of swab tests due to changes in political and regulatory scenarios. Wastewater and clinical data were significantly correlated when restrictive containment measures and limited movements were in effect (ρ = 0.50) and when COVID-19 cases were confirmed exclusively through molecular testing (ρ = 0.49). Moreover, a positive (although weak) correlation arose for WWTPs located in densely populated areas (ρ = 0.37) and with shorter sewerage lengths (ρ = 0.28). This study provides methodological approaches for interpreting WBE and clinical surveillance data, which could also be useful for other infections. Data adjustments and evaluation of possible sources of bias need to be carefully considered from the perspective of integrated environmental and clinical surveillance of infections.

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Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology

Cited by 46 publications

References 74 publications

A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19

A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19

The Inhibition and Variability of Two Different RT-qPCR Assays Used for Quantifying SARS-CoV-2 RNA in Wastewater

Critical Needs for Integrated Surveillance: Wastewater-Based and Clinical Epidemiology in Evolving Scenarios with Lessons Learned from SARS-CoV-2

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