Estimating SARS-CoV-2 prevalence from large-scale wastewater surveillance: insights from combined analysis of 44 sites in England (preprint)

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 (WW) can be used to infer infection prevalence, but uncertainty in sensitivity and considerable variability has meant that accurate measurement remains elusive. Data from 44 sewage sites in England, covering 31% of the population, shows that SARS-CoV-2 prevalence is estimated to within 1.1% of estimates from representative prevalence surveys (with 95% confidence). Using machine learning and phenomenological models, differences between sampled sites, particularly the WW flow rate, influence prevalence estimation and require careful interpretation. SARS-CoV-2 signals in WW appear 4–5 days earlier in comparison to clinical testing data but are coincident with prevalence surveys suggesting that WW surveillance can be a leading indicator for asymptomatic viral infections. Wastewater-based epidemiology complements and strengthens traditional surveillance, with significant implications for public health.

Faecal shedding models for SARS-CoV-2 RNA amongst hospitalised patients and implications for wastewater-based epidemiology (preprint)

The concentration of SARS-CoV-2 RNA in faeces is not well established, posing challenges for wastewater-based surveillance of COVID-19 and risk assessments of environmental transmission. We develop versatile hierarchical models for faecal RNA shedding and apply them to data collected in six studies. We find that the mean number of gene copies per mL of faeces is 1.9x106 (2.3x105--2.0x108 95% credible interval) amongst hospitalised patients. We find no evidence for a subpopulation of patients who do not shed RNA: limits of quantification can account for negative stool samples. Our models indicate that hospitalised patients represent the tail of the shedding profile with a half-life of 34 hours (28--43 95% credible interval), suggesting that wastewater-based surveillance signals are more indicative of incidence than prevalence and can be a leading indicator of clinical presentation. Shedding amongst inpatients cannot explain high RNA concentrations observed in wastewater, consistent with more abundant shedding during the early infection course.