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Welling CM, Singleton DR, Haase SB, Browning CH, Stoner BR, Gunsch CK, Grego S. Predictive values of time-dense SARS-CoV-2 wastewater analysis in university campus buildings. Sci Total Environ 2022; 835:155401. [PMID: 35469858 PMCID: PMC9026951 DOI: 10.1016/j.scitotenv.2022.155401] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 04/15/2022] [Accepted: 04/16/2022] [Indexed: 05/14/2023]
Abstract
Wastewater-based SARS-CoV-2 surveillance on college campuses has the ability to detect individual clinical COVID-19 cases at the building-level. High concordance of wastewater results and clinical cases has been observed when calculated over a time window of four days or longer and in settings with high incidence of infection. At Duke University, twice a week clinical surveillance of all resident undergraduates was carried out in the spring 2021 semester. We conducted simultaneous wastewater surveillance with daily frequency on selected residence halls to assess wastewater as an early warning tool during times of low transmission with the hope of scaling down clinical test frequency. We evaluated the temporal relationship of the two time-dense data sets, wastewater and clinical, and sought a strategy to achieve the highest wastewater predictive values using the shortest time window to enable timely intervention. There were 11 days with clinical cases in the residence halls (80-120 occupants) under wastewater surveillance with 5 instances of a single clinical case and 3 instances of two clinical cases which also corresponded to a positive wastewater SARS-CoV-2 signal. While the majority (71%) of our wastewater samples were negative for SARS-CoV-2, 29% resulted in at least one positive PCR signal, some of which did not correlate with an identified clinical case. Using a criteria of two consecutive days of positive wastewater signals, we obtained a positive predictive value (PPV) of 75% and a negative predictive value of 87% using a short 2 day time window for agreement. A conventional concordance over a much longer 4 day time window resulted in PPV of only 60%. Our data indicated that daily wastewater collection and using a criteria of two consecutive days of positive wastewater signals was the most predictive approach to timely early warning of COVID-19 cases at the building level.
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Affiliation(s)
- Claire M Welling
- Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America
| | - David R Singleton
- Department of Civil and Environmental Engineering, Duke University, Durham, NC, United States of America
| | - Steven B Haase
- Departments of Biology and Medicine, Duke University, Durham, NC, United States of America
| | - Christian H Browning
- Office of Information Technology, Duke University, Durham, NC, United States of America
| | - Brian R Stoner
- Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America
| | - Claudia K Gunsch
- Department of Civil and Environmental Engineering, Duke University, Durham, NC, United States of America
| | - Sonia Grego
- Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America.
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Wang Y, Liu P, Zhang H, Ibaraki M, VanTassell J, Geith K, Cavallo M, Kann R, Saber L, Kraft CS, Lane M, Shartar S, Moe C. Early warning of a COVID-19 surge on a university campus based on wastewater surveillance for SARS-CoV-2 at residence halls. Sci Total Environ 2022; 821:153291. [PMID: 35090922 PMCID: PMC8788089 DOI: 10.1016/j.scitotenv.2022.153291] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 01/15/2022] [Accepted: 01/16/2022] [Indexed: 05/05/2023]
Abstract
As COVID-19 continues to spread globally, monitoring the disease at different scales is critical to support public health decision making. Surveillance for SARS-CoV-2 RNA in wastewater can supplement surveillance based on diagnostic testing. In this paper, we report the results of wastewater-based COVID-19 surveillance on Emory University campus that included routine sampling of sewage from a hospital building, an isolation/quarantine building, and 21 student residence halls between July 13th, 2020 and March 14th, 2021. We examined the sensitivity of wastewater surveillance for detecting COVID-19 cases at building level and the relation between Ct values from RT-qPCR results of wastewater samples and the number of COVID-19 patients residing in the building. Our results show that weekly wastewater surveillance using Moore swab samples was not sensitive enough (6 of 63 times) to reliably detect one or two sporadic cases in a residence building. The Ct values of the wastewater samples over time from the same sampling location reflected the temporal trend in the number of COVID-19 patients in the isolation/quarantine building and hospital (Pearson's r < -0.8), but there is too much uncertainty to directly estimate the number of COVID-19 cases using Ct values. After students returned for the spring 2021 semester, SARS-CoV-2 RNA was detected in the wastewater samples from most of the student residence hall monitoring sites one to two weeks before COVID-19 cases surged on campus. This finding suggests that wastewater-based surveillance can be used to provide early warning of COVID-19 outbreaks at institutions.
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Affiliation(s)
- Yuke Wang
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
| | - Pengbo Liu
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Haisu Zhang
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Makoto Ibaraki
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jamie VanTassell
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Kelly Geith
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Matthew Cavallo
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Rebecca Kann
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Lindsay Saber
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Colleen S Kraft
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA; Division of Infectious Diseases, Emory University, Atlanta, GA, USA
| | - Morgan Lane
- Division of Infectious Diseases, Emory University, Atlanta, GA, USA
| | - Samuel Shartar
- Emory University Office of Critical Event Preparedness and Response, Atlanta, GA, USA
| | - Christine Moe
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
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