An analysis of 45 large-scale wastewater sites in England to estimate SARS-CoV-2 community prevalence

Abstract

Accurate surveillance of the COVID-19 pandemic can be weakened by under-reporting of cases, particularly due to asymptomatic or pre-symptomatic infections, resulting in bias. Quantification of SARS-CoV-2 RNA in wastewater can be used to infer infection prevalence, but uncertainty in sensitivity and considerable variability has meant that accurate measurement remains elusive. Here, we use data from 45 sewage sites in England, covering 31% of the population, and estimate SARS-CoV-2 prevalence to within 1.1% of estimates from representative prevalence surveys (with 95% confidence). Using machine learning and phenomenological models, we show that differences between sampled sites, particularly the wastewater flow rate, influence prevalence estimation and require careful interpretation. We find that SARS-CoV-2 signals in wastewater appear 4–5 days earlier in comparison to clinical testing data but are coincident with prevalence surveys suggesting that wastewater surveillance can be a leading indicator for symptomatic viral infections. Surveillance for viruses in wastewater complements and strengthens clinical surveillance, with significant implications for public health.

A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic

“…This study provides a necessary foundation for investigating the link between wastewater and COVID-19 prevalence at any desired spatial resolution. A previous study ( Morvan et al, 2022 ) considered the relationship between wastewater concentration and COVID-19 prevalence using the ONS-CIS survey and testing data on 45 STW catchment areas over the period July 2020 to March 2021. Specifying a spatio-temporal Bayesian model, they reported an overall good correspondence between the wastewater concentration and prevalence, concluding that wastewater can be used to provide reliable estimates of COVID-19 infections.…”

“…More specifically, they found that a decline in the wastewater virus concentration preceded by two to four days the reduction in community cases after lockdown measures were implemented. More recently, Morvan et al (2022) analysed data from 45 STWs across England between July 2020 and March 2021. Using multilevel modelling they reported that wastewater samples can be used to predict COVID-19 prevalence, with a lead time of four to five days.…”

Population-based sero-epidemiological estimates of real-world vaccine effectiveness against Omicron infection in an infection-naive population, Hong Kong, January to July 2022

“…Specifically, for each subject in our serosurvey, we estimated the probability of being infected by SARS-CoV-2 before study recruitment, given age, vaccination record and seropositivity of the serum sample (see Methods). We assumed that: (i) daily age-specific force of infection was proportional to daily viral load from city-wide wastewater surveillance (see Figure 1) which has been shown to be a robust (normalized) proxy for disease prevalence over time [2][3][4]; and (ii) one-dose vaccination provided no protection against infection and each successive homologous dose conferred greater VE which decayed exponentially over time at the same rate between doses of the same vaccine [5].…”

A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic

“…More specifically, they found that a decline in the wastewater virus concentration preceded by two to four days the reduction in community cases after lockdown measures were implemented. More recently, Morvan et al (2022) analysed data from 45 STWs across England between July 2020 and March 2021. Using a multilevel modelling approach they reported that wastewater samples can be used successfully to predict COVID-19 prevalence, with a lead time of four to five days.…”