ArticleThe Science of the total environment2023
Simple methods for early warnings of COVID-19 surges: Lessons learned from 21 months of wastewater and clinical data collection in Detroit, Michigan, United States.
Article in The Science of the total environment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 36 citations in OpenAlex.
- Wastewater Surveillance for SARS-CoV-2 in Northern Italy: An Evaluation of Three Different Gene Targets.Microorganisms · 2025Article
- The impact of signal variability on COVID-19 epidemic growth rate estimation from wastewater surveillance data.PloS one · 2025Article
- Bioaerosols and Airway Diseases: Mechanisms of Epithelial Dysfunction, Immune Activation, and Strategies for Exposure Mitigation.Archives of internal medicine research · 2025Article
- Tracking Chlamydia and Syphilis in the Detroit Metro Area by Molecular Analysis of Environmental Samples.Environmental science & technology · 2024Article
- Temporal assessment of SARS-CoV-2 detection in wastewater and its epidemiological implications in COVID-19 case dynamics.Heliyon · 2024Article
- Innovations in public health surveillance: An overview of novel use of data and analytic methods.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2024Article
- A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan.Human genomics · 2024Article
- Article
- Community case study: an academia-industry-government partnership that monitors and predicts outbreaks in Tri-County Detroit area since 2017.Frontiers in public health · 2024Article
- Wastewater surveillance beyond COVID-19: a ranking system for communicable disease testing in the tri-county Detroit area, Michigan, USA.Frontiers in public health · 2023Article
- Wastewater-based surveillance identifies start to the pediatric respiratory syncytial virus season in two cities in Ontario, Canada.Frontiers in public health · 2023Article
- Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for SARS-CoV-2: a methods comparison spanning the transition between delta and omicron variants in a large urban center.Frontiers in public health · 2023Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wastewater-based epidemiology (WBE) has drawn great attention since the Coronavirus disease 2019 (COVID-19) pandemic, not only due to its capability to circumvent the limitations of traditional clinical surveillance, but also due to its potential to forewarn fluctuations of disease incidences in communities. One critical application of WBE is to provide "early warnings" for upcoming fluctuations of disease incidences in communities which traditional clinical testing is incapable to achieve. While intricate models have been developed to determine early warnings based on wastewater surveillance data, there is an exigent need for straightforward, rapid, broadly applicable methods for health departments and partner agencies to implement. Our purpose in this study is to develop and evaluate such early-warning methods and clinical-case peak-detection methods based on WBE data to mount an informed public health response. Throughout an extended wastewater surveillance period across Detroit, MI metropolitan area (the entire study period is from September 2020 to May 2022) we designed eight early-warning methods (three real-time and five post-factum). Additionally, we designed three peak-detection methods based on clinical epidemiological data. We demonstrated the utility of these methods for providing early warnings for COVID-19 incidences, with their counterpart accuracies evaluated by hit rates. "Hit rates" were defined as the number of early warning dates (using wastewater surveillance data) that captured defined peaks (using clinical epidemiological data) divided by the total number of early warning dates. Hit rates demonstrated that the accuracy of both real-time and post-factum methods could reach 100 %. Furthermore, the results indicate that the accuracy was influenced by approaches to defining peaks of disease incidence. The proposed methods herein can assist health departments capitalizing on WBE data to assess trends and implement quick public health responses to future epidemics. Besides, this study elucidated critical factors affecting early warnings based on WBE amid the COVID-19 pandemic.
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