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

Abstract

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.

Simultaneous detection and quantification of multiple pathogen targets in wastewater

“…For example, the CDC has expanded upon the previously single-plex N1 assay for SARS-CoV-2 to include influenza A and/or B for increased testing capacity [40]. Practical applications of surveillance suggest that downstream sampling analyses of 3 or 4 samplings per week could provide useful results regarding trends, but the specific design would have to be driven by local public health trends and goals [41][42][43].…”

Piloting wastewater-based surveillance of norovirus in England

“…The log 10 mean averages were calculated for GI, GII, total NoV and ΔG from all sites for each of the national and regional two-weekly aggregates. Upward and downward trends in NoV levels were calculated using a relative strength index (RSI) with the TTR package (Ulrich, 2021) for R (R Core Team, 2023) according to Chan et al (2023), using a rolling 6-week look-back period. Each RSI value was assigned a descriptive trend category according to Table 2.…”

Public health policy impact evaluation: A potential use case for longitudinal monitoring of viruses in wastewater at small geographic scales

“…Wastewater monitoring data can also exhibit high day-to-day variability; potential mechanisms for this variability remain yet to be systematically understood but could be due to heterogeneity of the wastestream [98]. Future studies using longitudinal wastewater monitoring data for causal inference may consider analyzing changes in a computed outcome variable, such as a wastewater-based estimation of the effective reproductive number [54] or wastewater-based measure of trend [99], rather than changes in raw wastewater concentrations. Ultimately, the performance of such computed outcomes still depends on understanding the raw wastewater concentration data that are used to generate computed outcomes.…”