Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high

Abstract

Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this limitation. Here we investigated how the dynamics of new COVID-19 infections estimated based on wastewater monitoring or confirmed cases compare to true COVID-19 incidence dynamics. We focused on the first pandemic wave in Switzerland (February to April, 2020), when test positivity ranged up to 26%. SARS-CoV-2 RNA loads were determined 2-4 times per week in three Swiss wastewater treatment plants (Lugano, Lausanne and Zurich). Wastewater and case data were combined with a shedding load distribution and an infection-to-case confirmation delay distribution, respectively, to estimate incidence dynamics. Finally, the estimates were compared to reference incidence dynamics determined by a validated compartmental model. Incidence dynamics estimated based on wastewater data were found to better track the timing and shape of the reference infection peak compared to estimates based on confirmed cases. In contrast, case confirmations provided a better estimate of the subsequent decline in infections. Under a regime of high-test positivity rates, WBE thus provides critical information that is complementary to clinical data to monitor the pandemic trajectory.

Mathematical modeling and adequate environmental sampling plans are essential for the public health assessment of COVID-19 pandemics : development of a monitoring indicator for SARS-CoV-2 in wastewater

“…Figure 6 and Table 3 show some interplant variance on the time lag and the correlation between WWI and incidence rate. Such a variance in time lag between WWTPs has already been reported [20]. The intra-experimental variance is significantly higher for the WWTP of Nancy, whose average correlation with the incidence rate is not as strong as that of the other WWTPs.…”

Metrics to relate COVID-19 wastewater data to clinical testing dynamics

“…For example, wastewater viral titers and clinically reported cases are inherently linked to the number of true infections in the population. More mechanistic modeling is necessary to infer the underlying trend of true infections from the observable wastewater and clinical data (Fernandez-Cassi et al, 2021). Similarly, wastewater viral titers are linked to true infections by a transfer function that describes population-level shedding, while clinical cases are linked to true infections by a transfer function that describes population-level testing availability and turnaround time (Olesen et al, 2021).…”

Making waves: Defining the lead time of wastewater-based epidemiology for COVID-19

“…If trends in both case rates and wastewater change directions, public health officials can be more certain that disease prevalence has truly passed an inflection point. If wastewater measurements rise while case counts remain stable, then diagnostic testing may be undercounting cases ( Fernandez-Cassi et al 2021 ; Wu et al 2020 a). Conversely, if rates of positive diagnostic tests rise but wastewater measurements remain stable, then the apparent increase in cases may be due to increased testing (i.e., less undercounting) rather than to increased prevalence ( Gerrity et al 2021 ; McClary-Gutierrez et al 2021 ).…”

“…These delays mean that the timeseries of new case counts is offset relative to WBE measurements. However, there is also variability in those factors, which leads to a smoothing of case counts relative to shedding rates ( Fernandez-Cassi et al 2021 ; Wu et al 2020 b). This combination of shifting and smoothing means that the temporal relationship between wastewater measurements and case counts is complex ( Weidhaas et al 2021 ).…”