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

BackgroundWastewater-based epidemiology is a promising approach but robust epidemiological models to relate wastewater to community prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community prevalence because of inherent biases. MethodsFrom August 2020 to February 2021, we conducted a serial stratified randomized samplings to estimate the prevalence of anti-SARS-CoV-2 antibodies in 3,717 participants, and weekly sampling of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY. With the use of a Susceptible, Infected, Recovered (SIR)-type model, we obtained longitudinal estimates of prevalence and compared these with wastewater concentration, using regression analysis. FindingsModel analysis revealed significant temporal differences in epidemic peaks; the average incidence rate based on serological sampling in some areas was up to 50% higher than health department rates based on convenience sampling. The model-estimated average prevalence rates correlated well with wastewater (correlation=0{middle dot}63). In regression analysis, a weekly unit increase in wastewater concentration of SARS-CoV-2 corresponded to an average increase of between 1-1{middle dot}3 cases of SARS-CoV-2 infection per 100K residents. InterpretationPublicly available health department incidence rates vastly underestimate true community incidence and wastewater has a high potential to provide robust estimates of community spread of infection. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSAdministratively reported clinical case rates of coronavirus disease 2019 (COVID-19) infected individuals are biased due to a wide range of factors from testing access to concerns about missing low and non-symptomatic and self-tested individuals. Wastewater estimates offer an alternative to support community monitoring based on fecal shedding of the virus but are difficult to interpret when compared with the available public health data sets of infection rates. We examined all English literature until February 24, 2022, on Web of Science and PubMed with the terms ["seroprevalence" or "antibody"] AND ["COVID-19" or "SARS-CoV-2"] AND ["wastewater"]. We identified six studies. None of these studies considered randomized COVID-19 community anti-SARS-CoV-2 antibody testing paired with wastewater data. Added value of this studyThe study demonstrates how results from serial stratified randomized serological sampling of the community can be used to build a longitudinal model that can interpolate and extrapolate community levels of infection beyond specific testing dates. Such a model correlates well with wastewater concentrations indicating its utility as a surrogate for infection prevalence. The testing data used in the study were collected before wide availability of COVID-19 vaccines and are therefore unique as they are unlikely to include a significant number of false positive results. Implications of all the available evidenceThe study demonstrates that convenience sampling obtained data from health department reporting seriously underestimates community-wide prevalence of infection. In contrast, wastewater-based epidemiology may be a faster, cost-effective, and more robust method of estimating the prevalence of viral infections within specific urban areas.

Increasing viral transmission paradoxically reduces progression rates to severe COVID-19 during endemic transition

Natural infection with SARS-CoV-2 or vaccination induces virus-specific immunity protecting hosts from infection and severe disease. While the infection-preventing immunity gradually declines, the severity-reducing immunity is relatively well preserved. Here, based on the different longevity of these distinct immunities, we develop a mathematical model to estimate courses of endemic transition of COVID-19. Our analysis demonstrates that high viral transmission unexpectedly reduces the rates of progression to severe COVID-19 during the course of endemic transition despite increased numbers of infection cases. Our study also shows that high viral transmission amongst populations with high vaccination coverages paradoxically accelerates the endemic transition of COVID-19 with reduced numbers of severe cases. These results provide critical insights for driving public health policies in the era of living with COVID-19.