Tracking the Time Lag between SARS-CoV-2 Wastewater Concentrations and Three COVID-19 Clinical Metrics: A 21-Month Case Study in the Tricounty Detroit Area, Michigan
Publication: Journal of Environmental Engineering
Volume 150, Issue 1
Abstract
Wastewater surveillance has been widely implemented to monitor COVID-19 incidences in communities worldwide. One notable application of wastewater surveillance is for providing early warnings of disease outbreaks. Many studies have reported time lags between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater concentrations and confirmed clinical COVID-19 cases. To our best knowledge, only a few studies to date have explored time lags between SARS-CoV-2 wastewater concentrations and other clinical metrics. In this study, we investigated time lags between SARS-CoV-2 wastewater concentrations and three COVID-19 clinical metrics: confirmed clinical cases, hospitalizations, and intensive care unit (ICU) admissions, in the Tricounty Detroit Area, Michigan, US. The COVID-19 clinical metrics were dated between September 1, 2020, and October 31, 2022, and were collected from public data sources. SARS-CoV-2 N1 and N2 gene concentrations between September 1, 2020, and May 31, 2022, were generated using two sampling and concentration methods: virus adsorption-elution (VIRADEL) and polyethylene glycol precipitation (PEG). The data were collected from our recently published study. Time-lagged cross correlation was implemented to estimate time lags between gene concentrations and the three clinical metrics. Original gene concentrations were normalized by wastewater flow parameters through nine approaches to estimate the impact of wastewater flow on time lags. Vector autoregression models were established to analyze the relationship between gene concentrations and clinical metrics. The results indicate that VIRADEL gene concentrations in wastewater preceded all clinical metrics prior to the COVID-19 Omicron surge, for instance, 32, 47, and 51 days preceding confirmed cases, hospitalizations, and ICU admissions, respectively (gene concentrations unit: ). When translated to a public health context, these time lags become critical lead times for officials to prepare and react. During the Omicron surge, there were significant reductions in time lags, with VIRADEL measurements trailing total ICU admissions. PEG measurements lagged behind the three clinical metrics and did not provide early warnings of disease surges.
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Data Availability Statement
All data, models, and codes generated or used during this study appear in the published article.
Acknowledgments
We thank the Michigan Department of Health and Human Services (MDHHS) and the Great Lakes Water Authority (GLWA) for funding this work.
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Information & Authors
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Published In
Journal of Environmental Engineering
Volume 150 • Issue 1 • January 2024
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jul 13, 2023
Accepted: Aug 31, 2023
Published online: Oct 20, 2023
Published in print: Jan 1, 2024
Discussion open until: Mar 20, 2024
ASCE Technical Topics:
- Business management
- Case studies
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- Detection methods
- Diseases
- Engineering fundamentals
- Environmental engineering
- Epidemic and pandemic
- Health hazards
- Measurement (by type)
- Methodology (by type)
- Metric systems
- Practice and Profession
- Public administration
- Public health and safety
- Research methods (by type)
- Tracking
- Wastewater management
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