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A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19.
Rainey, Andrew L; Liang, Song; Bisesi, Joseph H; Sabo-Attwood, Tara; Maurelli, Anthony T.
  • Rainey AL; Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America.
  • Liang S; Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.
  • Bisesi JH; Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America.
  • Sabo-Attwood T; Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.
  • Maurelli AT; Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America.
PLoS One ; 18(4): e0284370, 2023.
Article in English | MEDLINE | ID: covidwho-2302240
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: North America Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2023 Document Type: Article Affiliation country: Journal.pone.0284370

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: North America Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2023 Document Type: Article Affiliation country: Journal.pone.0284370