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SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales.
Swift, Candice L; Isanovic, Mirza; Correa Velez, Karlen E; Norman, R Sean.
  • Swift CL; Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA.
  • Isanovic M; Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA.
  • Correa Velez KE; Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA.
  • Norman RS; Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA.
Environ Adv ; 11: 100347, 2023 Apr.
Article in English | MEDLINE | ID: covidwho-2210247
ABSTRACT
Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal: Environ Adv Year: 2023 Document Type: Article Affiliation country: J.envadv.2023.100347

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal: Environ Adv Year: 2023 Document Type: Article Affiliation country: J.envadv.2023.100347