Monitoring Coronavirus at Local and Community Levels using an Environmental Surveillance Method

Abstract

In the post-pandemic era, monitoring the community levels of coronavirus could help us evaluate the current risk of contracting COVID-19. In this study, I aimed to develop an alternative environmental surveillance tool for early detection of emerging SARS-CoV-2 variants and obtain the individual data to provide information to track the virus progression. In order to
rapidly detect viruses that may have been circulating in the community, I implemented a real-
time qPCR assay, which is a highly sensitive method able to detect and quantify trace amounts of live or dead COVID-19 virus RNA. Samples were collected from various public locations
around the highly populated Washington D.C. area. Via the analysis of the RT-qPCR results, I
found trace amounts of COVID-19 RNA in 11 out of 12 of these samples with cycle threshold
(C T ) values close to 40. Due to the very low positivity of the environmental samples, none of
them were deemed as containing enough viral RNA to imply the presence of infectious viruses.
However, the very low level of positive detection in these samples may reflect that our
environment is now contaminated with a low background level of viral RNA due to the global
pandemic. The results both suggest that this environmental surveillance method might be
applicable to monitoring the status of the virus spread and variants, as well as indicate that using a C T value of 40 as a cutoff to diagnose COVID-19 should be revised due to the increased
residual level of coronavirus RNA in our environment.