A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Identifying transcriptomic indicators of tertiary treated municipal effluent in longnose dace (Rhinichthys cataractae) caged under semi-controlled conditions in experimental raceways.

To evaluate effects of tertiary treated wastewater treatment plant effluent (MWWE) on transcriptomic responses in longnose dace (Rhinichthys cataractae; LND) we conducted a semi-controlled study in experimental raceways (Advancing Canadian Water Assets facility) imbedded in the Pine Creek treatment plant (Calgary, AB). LND collected from a reference site in the Bow River (REF) were caged in raceways containing either 5 % Pine Creek effluent (PC) or Bow River water (BR; control) over 28 d. Liver transcriptomes were analyzed in males and females sampled on days 7, 14 and 28 from BR and PC, and compared to REF fish on day 0. Concurrent with the caging, selected environmental substances of concern were analyzed in the BR and PC. Significantly different unigenes (SDUs) in females (vs males) within both BR and PC raceways increased over time and compared to REF fish. Moreover, SDUs in females and males within the same treatment (i.e., BR, PC) showed a temporal increase as well as compared to REF fish. Time was the dominant factor affecting SDUs, whereas sex and treatment had less of an impact on the transcriptome profiling. Gene Set Enrichment Analysis of BR vs PC over time revealed effects on genes involved in growth, metabolism of carbohydrates and lipids, and immune system on day 7; however, by day 28, 80-100 % of the transcripts localized to enriched biomarkers were associated with tissue immune responses in both sexes. Exposure to 5 % effluent had significant effects on female liver somatic index but no effects were observed on other phenotypic health indices in either sex. BR was used as the source of reference water, but analyses showed trace amounts of ESOCs. Analyses did not point towards definitive response patterns that could be used in field-based ecotoxicogenomic studies on the impacts of well-treated MWWE but suggested compromised adaptive immune responses.