Several treatment plants were sampled for influent, primary clarifier sludge, return activated sludge (RAS), and anaerobically digested sludge throughout nine weeks during the summer of the COVID-19 pandemic. Primary clarifier sludge had a significantly higher number of SARS-CoV-2 gene copy number per liter (GC/L) than other sludge samples, within a range from 1.0 × 10
5
to 1.0 × 10
6
GC/L. Gene copy numbers in raw influent significantly correlated with gene copy numbers in RAS in Silver Creek (
p
-value = 0.007, R
2
= 0.681) and East Canyon (p-value = 0.009, R
2
= 0.775) WRFs; both of which lack primary clarifiers or industrial pretreatment processes. This data indicates that SARS-CoV-2 gene copies tend to partition into primary clarifier sludges, at which point a significant portion of them are removed through sedimentation. Furthermore, it was found that East Canyon WRF gene copy numbers in influent were a significant predictor of daily cases (
p
-value = 0.0322, R
2
= 0.561), and gene copy numbers in RAS were a significant predictor of weekly cases (p-value = 0.0597, R
2
= 0.449). However, gene copy numbers found in primary sludge samples from other plants significantly predicted the number of COVID-19 cases for the following week (
t
= 2.279) and the week after that (
t
= 2.122) respectively. These data indicate that SARS-CoV-2 extracted from WRF biosolids may better suit epidemiological monitoring that exhibits a time lag. It also supports the observation that primary sludge removes a significant portion of SARS-CoV-2 marker genes. In its absence, RAS can also be used to predict the number of COVID-19 cases due to direct flow through from influent. This research represents the first of its kind to thoroughly examine SARS-CoV-2 gene copy numbers in biosolids throughout the wastewater treatment process and the relationship between primary, return activated, and anaerobically digested sludge and reported positive COVID-19 cases.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.