Assessment of a SARS-CoV-2 Wastewater Monitoring Program in El Paso, Texas, from November 2020 to June 2022
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2024/01/01
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Details
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Personal Author:Avadhanula V ; Bauer C ; Chavarria C ; Clark JR ; Feliz K ; Gallegos G ; Gitter A ; Maresso A ; Mena KD ; Mezzari M ; Petrosino J ; Piedra T ; Ramphul R ; Terwilliger AL ; Weesner K ; Wu F ; Zhang K
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Description:The border city of El Paso, Texas, and its water utility, El Paso Water, initiated a SARS-CoV-2 wastewater monitoring program to assess virus trends and the appropriateness of a wastewater monitoring program for the community. Nearly weekly sample collection at four wastewater treatment facilities (WWTFs), serving distinct regions of the city, was analyzed for SARS-CoV-2 genes using the CDC 2019-Novel coronavirus Real-Time RT-PCR diagnostic panel. Virus concentrations ranged from 86.7 to 268,000 gc/L, varying across time and at each WWTF. The lag time between virus concentrations in wastewater and reported COVID-19 case rates (per 100,00 population) ranged from 4-24 days for the four WWTFs, with the strongest trend occurring from November 2021 - June 2022. This study is an assessment of the utility of a geographically refined SARS-CoV-2 wastewater monitoring program to supplement public health efforts that will manage the virus as it becomes endemic in El Paso. [Description provided by NIOSH]
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ISSN:0960-3123
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Volume:34
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Issue:1
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NIOSHTIC Number:nn:20067448
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Citation:Int J Environ Health Res 2024 Jan; 34(1):564-574
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Contact Point Address:Anna Gitter, Department of Epidemiology, Human Genetics & Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
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Email:anna.gitter@uth.tmc.edu
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Federal Fiscal Year:2024
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Performing Organization:University of Texas Health Science Center, Houston
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Peer Reviewed:True
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Start Date:20050701
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Source Full Name:International Journal of Environmental Health Research
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End Date:20250630
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Main Document Checksum:urn:sha-512:2453179e9eca82d2037e80703fd8a532b89d6688968e9961e2afadd1c5c482898a5a486c3c947945e726d71aa410dfd631cd3489252a9444795bcab45decefb6
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