Review of quantitative microbial risk assessments for potable water reuse†

Potable water reuse is becoming more common as communities deal with increased water demands and climate change. Understanding the risks associated with potable reuse is essential to ensuring that public health is protected from waterborne pathogens. This paper provides a review on the studies that have performed quantitative microbial risk assessments (QMRAs) on potable reuse. The 30 articles included here studied direct potable reuse (DPR), indirect potable reuse (IPR), and/or de facto reuse (DFR), and a variety of pathogens, including norovirus, adenovirus, Cryptosporidium, Giardia, Campylobacter, and Salmonella. The QMRAs were either ‘top-down’ or regulations-focused, where log reduction targets (LRTs) were determined based on initial (e.g., raw wastewater) pathogen concentrations and risk goals (e.g., 10⁻⁴ annual risk benchmark), or ‘bottom-up’ or risk-estimation-focused, where risks were calculated based on known pathogen concentrations and observed/credited log reduction values (LRVs). Some studies incorporated process failures and pathogen decay, which were often a driving factor for risk, but several studies omitted one or both. Many studies compared multiple treatment trains (e.g., carbon-based advanced treatment (CBAT) vs. reverse-osmosis-based advanced treatment (RBAT)). They found that treatment-based differences were pathogen-dependent because certain processes are better able to inactivate or remove certain pathogens. Many factors influence the risks reported in the various studies, including the assumed ratios of gene copies to infectious units (GC : IU), assumptions related to ingestion volume and frequency, dynamic vs. static modeling, and Bayesian approaches. The LRTs for the top-down QMRAs varied within and between studies, depending partially on the pathogen concentrations used and whether redundancy was included. The key findings from this review were that while QMRAs often have different goals warranting different assumptions, it is essential that researchers report these assumptions and their justifications so that policymakers and regulators fully understand their implications to avoid overly stringent or nonprotective regulations.