Predictive power of SARS-CoV-2 wastewater surveillance for diverse populations across a large geographical range (preprint)

ABSTRACT

The COVID-19 pandemic has exacerbated the disparities in healthcare delivery in the US. Many communities had, and continue to have, limited access to COVID-19 testing, making it difficult to track the spread and impact of COVID-19 in early days of the outbreak. To address this issue we monitored severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA at the population-level using municipal wastewater influent from 19 cities across the state of Minnesota during the COVID-19 outbreak in Summer 2020. Viral RNA was detected in wastewater continually for 20-weeks for cities ranging in populations from 500 to >1, 000, 000. Using a novel indexing method, we were able to compare the relative levels of SARS-CoV-2 RNA for each city during this sampling period. Our data showed that viral RNA trends appeared to precede clinically confirmed cases across the state by several days. Lag analysis of statewide trends confirmed that wastewater SARS-CoV-2 RNA levels preceded new clinical cases by 15-17 days. At the regional level, new clinical cases lagged behind wastewater viral RNA anywhere from 4- 20 days. Our data illustrates the advantages of monitoring at the population-level to detect outbreaks. Additionally, by tracking infections with this unbiased approach, resources can be directed to the most impacted communities before the need outpaces the capacity of local healthcare systems.