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Additional file 1: Table S1. Number of sites testing positive for SPED among over all three runs in Experiment 1. Table S2. Mean SPED1 DNA concentration before and after Experiment 2. Table S3. Recovery fraction of SPED and E. coli after the two-step transfer in Experiment 3.

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.

The frequent contact people have with liquids containing pathogenic microorganisms provides opportunities for disease transmission. In this work, we quantified the transfer of bacteria—using E. coli as a model- from liquid to skin, estimated liquid retention on the skin after different contact activities (hand immersion, wet-cloth and wet-surface contact), and estimated liquid transfer following hand-to-mouth contacts. The results of our study show that the number of E. coli transferred to the skin per surface area (n [E. coli/cm2]) can be modeled using n = C (10−3.38+h), where C [E. coli/cm3] is the concentration of E. coli in the liquid, and h [cm] is the film thickness of the liquid retained on the skin. Findings from the E. coli transfer experiments reveal a significant difference between the transfer of E. coli from liquid to the skin and the previously reported transfer of viruses to the skin. Additionally, our results demonstrate that the time elapsed since the interaction significantly influences liquid retention, therefore modulating the risks associated with human interaction with contaminated liquids. The findings enhance our understanding of liquid-mediated disease transmission processes and provide quantitative estimates as inputs for microbial risk assessments.

Environmental surveillance of surface contamination is an unexplored tool for understanding transmission of SARS-CoV-2 in community settings. We conducted longitudinal swab sampling of high-touch non-porous surfaces in a Massachusetts town during a COVID-19 outbreak from April to June 2020. Twenty-nine of 348 (8.3 %) surface samples were positive for SARS-CoV-2, including crosswalk buttons, trash can handles, and door handles of essential business entrances (grocery store, liquor store, bank, and gas station). The estimated risk of infection from touching a contaminated surface was low (less than 5 in 10,000), suggesting fomites play a minimal role in SARS-CoV-2 community transmission. The weekly percentage of positive samples (out of n=33 unique surfaces per week) best predicted variation in city-level COVID-19 cases using a 7-day lead time. Environmental surveillance of SARS-CoV-2 RNA on high-touch surfaces could be a useful tool to provide early warning of COVID-19 case trends.