Meta-analyses on SARS-CoV-2 Viral Titers in Wastewater and Their Correlations to Epidemiological Indicators

Abstract

ABSTRACTBackgroundRecent applications of wastewater-based epidemiology (WBE) have demonstrated its ability to track the spread and dynamics of COVID-19 at the community level. Despite the growing body of research, quantitative synthesis of SARS-CoV-2 titers in wastewater generated from studies across space and time using diverse methods has not been performed.ObjectiveThe objective of this study is to examine the correlations between SARS-CoV-2 viral titers in wastewater across studies, stratified by key covariates in study methodologies. In addition, we examined the associations of proportions of positive detections (PPD) in wastewater samples and methodological covariates.MethodsWe systematically searched the Web of Science for studies published by February 16th, 2021, performed a reproducible screen, and employed mixed-effects models to estimate the levels of SARS-CoV-2 viral titers in wastewater samples and their correlations to case prevalence, sampling mode (grab or composite sampling), and the fraction of analysis (FOA, i.e., solids, solid-supernatant mixtures, or supernatants/filtrates)ResultsA hundred and one studies were found; twenty studies (1,877 observations) were retained following a reproducible screen. The mean of PPD across all studies was 0.67 (95%-CI, [0.56, 0.79]). The mean titer was 5,244.37 copies/mL (95%-CI, [0; 16,432.65]). The Pearson Correlation coefficients (PCC) between viral titers and case prevalences were 0.28 (95%-CI, [0.01; 0.51) for daily new cases or 0.29 (95%-CI, [-0.15; 0.73]) for cumulative cases. FOA accounted for 12.4% of the variability in PPD, followed by case prevalence (9.3% by daily new cases and 5.9% by cumulative cases) and sampling mode (0.6%). Among observations with positive detections, FOA accounted for 56.0% of the variability in titers, followed by sampling mode (6.9%) and case prevalence (0.9% by daily new cases and 0.8% by cumulative cases). While sampling mode and FOA both significantly correlated with SARS-CoV-2 titers, the magnitudes of increase in PPD associated with FOA were larger. Mixed-effects model treating studies as random effects and case prevalence as fixed effects accounted for over 90% of the variability in SARS-CoV-2 PPD and titers.InterpretationsPositive pooled means and confidence intervals in PCC between SARS-CoV-2 titers and case prevalence indicators provide quantitative evidence reinforcing the value of wastewater-based monitoring of COVID-19. Large heterogeneities among studies in proportions of positive detections, titers, and PCC suggest a strong demand in methods to generate data accounting for cross-study heterogeneities and more detailed metadata reporting. Large variance explained by FOA suggesting FOA as a direction that needs to be prioritized in method standardization. Mixed-effects models accounting for study level variations provide a new perspective to synthesize data from multiple studies.