Wastewater-based epidemiology predicts COVID-19 community prevalence

Abstract

Wastewater-based epidemiology uses pooled wastewater samples to monitor community health and has been used extensively during the COVID-19 pandemic to track SARS-CoV-2 RNA shed by infected individuals into wastewater. Wastewater concentrations of SARS-CoV-2 RNA have been positively correlated with contemporaneous counts of COVID-19 cases, making it useful for following relative disease burden trends within a community. However, the statistical associations are too weak for wastewater-based epidemiology to reliably predict reported case counts, limiting its potential. Here we show that wastewater SARS-CoV-2 concentrations are highly correlated with the community prevalence estimated from 8 randomized household community surveys in 6 Oregon communities over a 10-month period. We found that wastewater-based epidemiology is a significantly better predictor of COVID-19 community prevalence than reported case counts, which suffer from systematic biases including variations in access to testing and underreporting of asymptomatic cases, even after accounting for uncertainty inherent in the wastewater and prevalence estimates by using Monte Carlo simulations. Additionally, our results show that wastewater-based epidemiology can identify the rise and fall of neighborhood-scale COVID-19 hot spots and provide rapid information about the presence of SARS-CoV-2 variants at the neighborhood- and city-scale through sequence analyses of the wastewater. These results validate the potential of wastewater-based epidemiology to be a quantitative method to predict the prevalence of SARS-CoV-2 and identify the presence of variants of concern in a given community or neighborhood, independent of availability and access to individual-level testing. These advantages in combination with its scalability, relatively modest cost and low labor requirements, makes integrating permanent wastewater-based epidemiology infrastructure into public health systems a key component in creating pandemic-resilient cities in the future.

Predicting COVID-19 Infected Individuals in a Defined Population from Wastewater RNA Data

“…Several WBE studies have reported known numbers of infected individuals. A number of these studies were performed on college campuses and correlated SARS-CoV-2 RNA concentrations to reported cases. − Of these, Karthikeyan et al provided a model to quantitatively link RNA concentrations to numbers of cases. They employed an infinite impulse response filter with wastewater signal as an input.…”

Quantifying the relationship between sub-population wastewater samples and community-wide SARS-CoV-2 seroprevalence

“…Moreover, our results do not support a linear relationship between wastewater and prevalence proposed by Layton et al . 10 and Cao et al . 13 Previous convenience seroprevalence studies paired to wastewater may have underreported the correlation, owing to inadequate or no case data from portions of a community, underreporting of at-home COVID-19 antigen rapid self-test results, and reliance on clinical syndromic surveillance.…”

“…Previous combined wastewater and serological surveys at a community scale have focused on Hepatitis A and E viruses. 11,12 Existing SARS-CoV-2 wastewater to community COVID-19 case models have been fit around results obtained from convenience sampling, models which may underrepresent community trends, 13–17 as well as limited random samples of communities via SARS-CoV-2 in nasal swabs 10 or blood bank serological surveys. 15,18 Nonetheless, robust longitudinal estimates of community serology are more appropriate to interpret wastewater measurements.…”

“…6 In the COVID-19 pandemic, randomized serological surveys have been conducted at varying scales in the United States across the states of California, Georgia, Indiana, Kentucky, Oregon, and Rhode Island, but with narrow temporal resolution. 4,7–10 Although such a snapshot measure of cumulative infection in a narrow window of serology is an accurate way to estimate past prevalence of infection in communities, the lack of repeated measurements reduces the utility of such results for relating to wastewater measures. Wastewater results are not cumulative and change over time, and as such discrete wastewater measurements may fail to identify changes in the infection rates or to identify small recalcitrant refugia of infection in discrete geographic hot spots.…”

Structured Ethical Review for Wastewater-Based Testing in Support of Public Health

“…Distribution of assigned flags (“minimal review required”, “review suggested”, “review strongly suggested”, “not available in the main text”, “not applicable”) for the top 11 categories in the structured ethical review, represented as a fraction percent of all publications analyzed ( n = 53) with multiple reviewers providing reports for select individual studies, resulting in more reviews than studies ( n = 79). ,− ,− In total, 56 publications were represented by these studies, with 3 having two publications describing the same monitoring campaign and considered in concert. The categories are sorted by ascending proportion of “minimal review required”.…”