Search

We measured concentrations of SARS-CoV-2, influenza A and B virus, respiratory syncytial virus (RSV), mpox virus, human metapneumovirus, norovirus GII, and pepper mild mottle virus nucleic acids in wastewater solids at twelve wastewater treatment plants in Central California, USA. Measurements were made daily for up to two years, depending on the wastewater treatment plant. Measurements were made using digital droplet (reverse-transcription-) polymerase chain reaction (RT-PCR) following best practices for making environmental molecular biology measurements. These data can be used to better understand disease occurrence in communities contributing to the wastewater.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel member of the Coronaviridae family, has been identified as the etiologic agent of an ongoing pandemic of severe pneumonia known as COVID-19.(1) To date there have been millions of cases of COVID-19 diagnosed in 184 countries with case fatality rates ranging from 1.8% in Germany to 12.5% in Italy.(2) Limited diagnostic testing capacity and asymptomatic and oligosymptomatic infections result in significant uncertainty in the estimated extent of SARS-CoV-2 infection.(3) Recent reports have documented that infection with SARS-CoV-2 is accompanied by persistent shedding of virus RNA in feces in 27%(4) to 89% of patients at densities from 0.8 to 7.5 log10 gene copies per gram.(5) The presence of SARS-CoV-2 RNA in feces raises the potential to survey sewage for virus RNA to inform epidemiological monitoring of COVID-19, which we refer to as wastewater-based epidemiology (WBE),(6) but is also known as environmental surveillance.(7) Several studies have reported the detection of SARS-CoV-2 RNA in wastewater in the early stages of local outbreaks, further supporting the technical viability of WBE.(8−10) WBE could be especially informative given that asymptomatic and oligosymptomatic infections are unlikely to be detected during clinical surveillance. In such instances, WBE can be used to determine the burden of undiagnosed infections at the population level, which is critical to refining estimates of case-fatality rates. Additionally, wastewater offers an aggregate sample from an entire community that is more easily accessible than pooled clinical samples.(11) Along with clinical data and other technological approaches, such as contact tracing, WBE could provide critical monitoring of SARS-CoV-2 transmission within a community including the beginning, tapering, or re-emergence of an epidemic (Figure 1). This approach mirrors previous efforts in environmental monitoring, for example poliovirus RNA, to inform mechanistic models of pathogen transmission dynamics.(12)

Background The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change. Objectives We show that the dynamics of SARS-CoV-2 RNA in wastewater can be used to estimate Re in near real-time, independent of clinical data and without the associated biases. Methods We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, CH, and San Jose (CA), USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence. Results The method to estimate Re from wastewater works robustly on data from two different countries and two wastewater matrices. The resulting estimates are as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. Discussion To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens.

To inform the development of global wastewater monitoring systems, we surveyed programmes in 43 countries. Most programmes monitored predominantly urban populations. In high-income countries (HICs), composite sampling at centralised treatment plants was most common, whereas grab sampling from surface waters, open drains, and pit latrines was more typical in low-income and middle-income countries (LMICs). Almost all programmes analysed samples in-country, with an average processing time of 2·3 days in HICs and 4·5 days in LMICs. Whereas 59% of HICs regularly monitored wastewater for SARS-CoV-2 variants, only 13% of LMICs did so. Most programmes share their wastewater data internally, with partnering organisations, but not publicly. Our findings show the richness of the existing wastewater monitoring ecosystem. With additional leadership, funding, and implementation frameworks, thousands of individual wastewater initiatives can coalesce into an integrated, sustainable network for disease surveillance—one that minimises the risk of overlooking future global health threats.

Stormwater biofilters are distributed stormwater control measures for managing urban runoff. Recent work has shown that adding biochar to biofilters can reduce stormwater contaminant concentrations, including fecal indicator bacteria (FIB). However, the potential of biochar-augmented biofilters to remove human pathogens from stormwater has not been investigated. In this study, we investigated the removal of bacterial pathogens Salmonella enterica serovar Typhimurium and Staphylococcus aureus, as well as bacterial and viral indicators Escherichia coli and MS2 coliphage in laboratory-scale biochar-amended biofilters. Biochar-amended biofilters performed better than sand biofilters in removing the microorganisms from stormwater and removal of pathogenic bacteria was greater than that of FIB. Biochar-augmented biofilters provided up to 3.9, 1.9, and 1.8log(10) removal for pathogenic bacteria, E. coli, and MS2, respectively. We utilized colloid filtration theory to elucidate potential microbial removal mechanisms. In biochar-amended biofilters, electrostatic interactions between the virus and collector surfaces likely controlled bacteriophage removal whereas the electrostatic interactions likely played a minor role in bacterial removal. Bacterial removal in biochar-augmented biofilters was likely controlled by straining and hydrophobic interactions. The findings of this study inform the design of geomedia-amended biofilters to reduce stormwater-derived microbial contamination in receiving waters.