ArticleACS ES&T water2022
Development and Validation of a Simplified Method for Analysis of SARS-CoV-2 RNA in University Dormitories.
Article in ACS ES&T water, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- Article
- Clinical correlation of SARS-CoV-2 wastewater passive sampling in long-term care facilities and wastewater treatment plants.Environmental advances · 2025Article
- Implementing Wastewater-Based Epidemiology for Long-Read Metagenomic Sequencing of Antimicrobial Resistance in Kampala, Uganda.Microorganisms · 2025Article
- Extraction of redox extracellular vesicles using exclusion-based sample preparation.Analytical and bioanalytical chemistry · 2024Article
- Wastewater Surveillance for Identifying SARS-CoV-2 Infections in Long-Term Care Facilities, Kentucky, USA, 2021-2022.Emerging infectious diseases · 2024Article
- Simple SARS-CoV-2 concentration methods for wastewater surveillance in low resource settings.The Science of the total environment · 2024Article
- Wastewater Surveillance for SARS-CoV-2 at Long-Term Care Facilities: Mixed Methods Evaluation.JMIR public health and surveillance · 2023Article
- Stabilization of SARS-CoV-2 RNA in wastewater via rapid RNA extraction.The Science of the total environment · 2023Article
- Improving wastewater-based epidemiology performance through streamlined automation.Journal of environmental chemical engineering · 2023Article
- Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks.Journal of medical virology · 2023Article
- Evaluating various composite sampling modes for detecting pathogenic SARS-CoV-2 virus in raw sewage.Frontiers in microbiology · 2023Article
Corrections and comments
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Authors and funding
17 authors at 2 institutions in 1 country.
Funding
Abstract
Over the course of the COVID-19 pandemic, wastewater surveillance has become a useful tool for describing SARS-CoV-2 prevalence in populations of varying size, from individual facilities (e.g., university residence halls, nursing homes, prisons) to entire municipalities. Wastewater analysis for SARS-CoV-2 RNA requires specialized equipment, expensive consumables, and expert staff, limiting its feasibility and scalability. Further, the extremely labile nature of viral RNA complicates sample transportation, especially in regions with limited access to reliable cold chains. Here, we present a new method for wastewater analysis, termed exclusion-based sample preparation (ESP), that substantially simplifies workflow (at least 70% decrease in time; 40% decrease in consumable usage compared with traditional techniques) by targeting the labor-intensive processing steps of RNA purification and concentration. To optimize and validate this method, we analyzed wastewater samples from residence halls at the University of Kentucky, of which 34% (44/129) contained detectible SARS-CoV-2 RNA. Although concurrent clinical testing was not comprehensive, student infections were identified in the 7 days following a positive wastewater detection in 68% of samples. This pilot study among university residence halls validated the performance and utility of the ESP method, laying the foundation for future studies in regions of the world where wastewater testing is not currently feasible.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.