Back

Assessing the performance and suitability of wastewater based-surveillance for SARS-CoV-2 RNA in public schools

Acosta, N.; Buchner Beaudet, A.; Westlund, P.; Hu, J.; Sedaghat, N.; Pradhan, P.; Man, L.; Hollman, J.; Bautista, M. A.; Waddell, B. J.; McCalder, J.; Penney, M.; Chen, J.; Meddings, J.; Achari, G.; Ryan, M. C.; Breton, D.; Wood, E. A.; Cabaj, J. L.; Clark, R. C.; Frankowski, K.; Hubert, C. R. J.; Parkins, M. D.

2025-01-17 infectious diseases
10.1101/2025.01.16.25320681 medRxiv
Show abstract

Municipal wastewater-based surveillance (WBS) programs for SARS-CoV-2 were valuable tools for epidemiological modelling and informing COVID-19 health policy during the pandemic. We conducted a "near to source" study to assess the capacity and performance of SARS-CoV-2 WBS programs in schools relative to municipal wastewater treatment plants (WWTP). Only 4/17 schools screened had plumbing systems that were amenable to WBS. From December 2020 - March 2021 composite wastewater collected 2X/week from four schools and three municipal WWTP were assessed for SARS-CoV-2 and fecal biomarkers. Schools had lower rates of successful sample collection relative to WWTP (44.7% vs 100%, p<0.001). In a time of low COVID-19 activity, 13/64 of school samples were positive of SARS-CoV-2-N1 vs 100% of WWTP. SARS-CoV-2-N1 detected in school wastewater associated with and preceded clinically identified infections, but did not correlate with rates of overall absenteeism. Notably levels of SARS-CoV-2-N1 and fecal biomarkers were markedly lower in wastewater from schools relative to WWTP. While our SARS-CoV-2 WBS program in schools did generate a leading signal relative to clinical disease, the significantly lower levels of SARS-CoV-2 and fecal biomarkers suggests that toileting habits of children who may avoid defecation at school adversely impact school-based WBS of targets shed in feces.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.