Quantitative Reverse Transcription PCR Surveillance of SARS-CoV-2 Variants of Concern in Wastewater of Two Counties in Texas, United States
Author(s) -
Laura M. Langan,
Megan O’Brien,
Lea M. Lovin,
Kendall R. Scarlett,
Haley Davis,
Abigail N. Henke,
Sarah Seidel,
Natalie P. Archer,
Eric Lawrence,
R. Sean Norman,
Heidi Bojes,
Bryan W. Brooks
Publication year - 2022
Publication title -
acs esandt water
Language(s) - English
Resource type - Journals
ISSN - 2690-0637
DOI - 10.1021/acsestwater.2c00103
Subject(s) - wastewater , covid-19 , biology , virology , sewage , epidemiology , population , feces , coronavirus , viral load , virus , medicine , environmental health , microbiology and biotechnology , environmental engineering , environmental science , disease , infectious disease (medical specialty)
After its emergence in late November/December 2019, the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) rapidly spread globally. Recognizing that this virus is shed in feces of individuals and that viral RNA is detectable in wastewater, testing for SARS-CoV-2 in sewage collections systems has allowed for the monitoring of a community's viral burden. Over a 9 month period, the influents of two regional wastewater treatment facilities were concurrently examined for wild-type SARS-CoV-2 along with variants B.1.1.7 and B.1.617.2 incorporated as they emerged. Epidemiological data including new confirmed COVID-19 cases and associated hospitalizations and fatalities were tabulated within each location. RNA from SARS-CoV-2 was detectable in 100% of the wastewater samples, while variant detection was more variable. Quantitative reverse transcription PCR (RT-qPCR) results align with clinical trends for COVID-19 cases, and increases in COVID-19 cases were positively related with increases in SARS-CoV-2 RNA load in wastewater, although the strength of this relationship was location specific. Our observations demonstrate that clinical and wastewater surveillance of SARS-CoV-2 wild type and constantly emerging variants of concern can be combined using RT-qPCR to characterize population infection dynamics. This may provide an early warning for at-risk communities and increases in COVID-19 related hospitalizations.
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