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\begin{document}

\title{Leveraging wastewater surveillance to actively monitor Covid-19
community dynamics in rural areas with reduced reliance on clinical
testing}



\author[1]{Michelle M. Jarvie}%
\author[1]{Thu N.T. Nguyen}%
\author[1]{Benjamin Southwell}%
\author[1]{Derek Wright}%
\affil[1]{Lake Superior State University School of Arts and Letters}%


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  \date{May 21, 2024}


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\begin{abstract}
The prevalence of 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-December
2022. Samples were analyzed for 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 correlation deterioration point.
Clinical cases post-deterioration were calculated for high-correlated
pre-deterioration 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.%
\end{abstract}%



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