Regional replacement of SARS-CoV-2 variant BA.1 with BA.2 as observed through wastewater surveillance

Boehm, Alexandria B.; Hughes, Bridgette; Wolfe, Marlene K.; White, Bradley J.; Duong, Dorothea; Chan-Herur, Vikram

doi:10.1101/2022.04.22.22274160

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…Data between November 15, 2020, and March 31, 2021, have been previously published by Wolfe et al [35] and are publicly available through the Stanford Digital Repository (https://doi.org/10.25740/bx987vn9177) [39]. Data between January 1, 2022, and April 12, 2022, have been previously published by Boehm et al [40] and are publicly available through the Stanford Digital Repository (https://doi.org/10.25740/cf848zx9249) [41]. The remaining data (April 1, 2021-December 31, 2021, and April 13, 2022-September 15, 2022) have not been previously published.…”

Section: Wastewater Datamentioning

confidence: 99%

Identifying trends in SARS-CoV-2 RNA in wastewater to infer changing COVID-19 incidence: Effect of sampling frequency

et al. 2023

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SARS-CoV-2 RNA concentrations in wastewater solids and liquids are correlated with reported incident COVID-19 cases. Reporting of incident COVID-19 cases has changed dramatically with the availability of at-home antigen tests. Wastewater monitoring therefore represents an objective tool for continued monitoring of COVID-19 occurrence. One important use case for wastewater data is identifying when there are sustained changes or trends in SARS-CoV-2 RNA concentrations. Such information can be used to inform public health messaging, testing, and vaccine resources. However, there is limited research on best approaches for identifying trends in wastewater monitoring data. To fill this knowledge gap, we applied three trend analysis methods (relative strength index (RSI), percent change (PC), Mann-Kendall (MK) trend test) to daily measurements of SARS-CoV-2 RNA in wastewater solids from a wastewater treatment plant to characterize trends. Because daily measurements are not common for wastewater monitoring programs, we also conducted a downsampling analysis to determine the minimum sampling frequency necessary to capture the trends identified using the “gold standard” daily data. The PC and MK trend test appear to perform similarly and better than the RSI in terms of first detecting increasing and decreasing trends using a 14-day look-back period, so we only considered the PC and MK trend test methods in the downsampling analysis. Using an acceptable sensitivity and specificity cutoff of 0.5, we found that a minimum of 4 samples/week and 5 samples/week is necessary to detect trends identified by daily sampling using the PC and MK trend test method, respectively. If a higher sensitivity and specificity is needed, then more samples per week would be needed. Public health officials can adopt these trend analysis approaches and sampling frequency recommendations to wastewater monitoring programs aimed at providing information on how incident COVID-19 cases are changing in the contributing communities.

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Section: Wastewater Datamentioning

confidence: 99%

Identifying trends in SARS-CoV-2 RNA in wastewater to infer changing COVID-19 incidence: Effect of sampling frequency

et al. 2023

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Wastewater-Based Epidemiology: Detection of SARS-CoV-2 RNA in Different Stages of Domestic Wastewater Treatment in Santa Fe, Argentina

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Regaldo

Ojeda³

et al. 2022

Water Air Soil Pollut

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The COVID-19 pandemic affected human life at every level. In this study, we analyzed genetic markers (N and ORF1ab, RNA genes) of SARS-CoV-2 in domestic wastewaters (DWW) in San Justo City (Santa Fe, Argentina), using reverse transcription-quantitative real-time PCR. Out of the 30 analyzed samples, 30% were positive for SARS-CoV-2 RNA. Of the total positive samples, 77% correspond to untreated DWW, 23% to pre-chlorination, and no SARS-CoV-2 RNA was registered at the post-chlorination sampling site. The viral loads of N and OFR1ab genes decreased significantly along the treatment process, and the increase in the number of viral copies of the N gene could anticipate, by 6 days, the number of clinical cases in the population. The concentration of chlorine recommended by the WHO (≥ 0.5 mg L −1 after at least 30 min of contact time at pH 8.0) successfully removed SARS-CoV-2 RNA from DWW. The efficiency of wastewater-based epidemiology (WBE) confirms the need to control and increase DWW treatment systems on a regional and global scale. This work could contribute to building a network for WBE to monitor SARS-CoV-2 in wastewaters during the pandemic waves and the epidemic remission phase. Graphical abstract Supplementary Information The online version contains supplementary material available at 10.1007/s11270-022-05772-w.

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Regional replacement of SARS-CoV-2 variant BA.1 with BA.2 as observed through wastewater surveillance

Cited by 2 publications

References 23 publications

Identifying trends in SARS-CoV-2 RNA in wastewater to infer changing COVID-19 incidence: Effect of sampling frequency

Identifying trends in SARS-CoV-2 RNA in wastewater to infer changing COVID-19 incidence: Effect of sampling frequency

Wastewater-Based Epidemiology: Detection of SARS-CoV-2 RNA in Different Stages of Domestic Wastewater Treatment in Santa Fe, Argentina

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