Affiliation:
1. School of Chemistry, Environmental, and Geosciences Lake Superior State University Sault Ste. Marie Michigan USA
Abstract
AbstractThe prevalence of coronavirus disease 2019 (Covid‐19) in the community has become more difficult to gauge utilizing clinical testing due to a decrease in reported test results stemming from the availability of at‐home test kits and a reduction in the number of cases seeking medical treatment. The purpose of this study was to examine the trend of diminishing correlation between reported clinical cases of Covid‐19 and wastewater‐based surveillance epidemiological data as home testing became available in the Eastern Upper Peninsula of Michigan. Wastewater grab samples were collected weekly from 16 regional locations from June 2021 to December 2022. Samples were analyzed for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) N1 and N2 viral particles using reverse transcriptase digital droplet polymerase chain reaction (RT ddPCR). N1 and N2 gene copies were correlated with clinical cases. The t test was used to determine the correlation deterioration point. Clinical cases postdeterioration were calculated for high‐correlated predeterioration locations using linear regression. Correlation between the wastewater‐based surveillance of SARS‐CoV‐2 and reported clinical cases deteriorated after February 1, 2022. This corresponds with the timeframe in which commercially available at‐home test kits became available in the United States. The increase in at‐home testing for SARS‐CoV‐2 likely contributed to the decrease in reported clinical positive tests in early 2022, providing an unrealistic picture of the presence of Covid‐19 in the community. As measures to reduce exposure such as personal masking, clinical testing, social isolating, and quarantining continue to decline, wastewater surveillance for the presence of SARS‐CoV‐2 may be the best method for public health professionals to remain aware of virus dynamics in localized regions. Time‐series modeling adds another layer of information when clinical data is unobtainable or underreported.
Funder
Michigan Department of Health and Human Services