Evolution of regulatory targets for drinking water quality

Research gaps and priorities for quantitative microbial risk assessment (QMRA)

The coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose-response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co-exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source-to-outcome continuum. Cross-cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.

Surveillance of Waterborne Disease Outbreaks Associated with Drinking Water - United States, 2015-2020

Problem/Condition

Public health agencies in U.S. states, territories, and freely associated states investigate and voluntarily report waterborne disease outbreaks to CDC through the National Outbreak Reporting System (NORS). This report summarizes NORS drinking water outbreak epidemiologic, laboratory, and environmental data, including data for both public and private drinking water systems. The report presents outbreak-contributing factors (i.e., practices and factors that lead to outbreaks) and, for the first time, categorizes outbreaks as biofilm pathogen or enteric illness associated.

Period Covered

2015-2020.

Description of System

CDC launched NORS in 2009 as a web-based platform into which public health departments voluntarily enter outbreak information. Through NORS, CDC collects reports of enteric disease outbreaks caused by bacterial, viral, parasitic, chemical, toxin, and unknown agents as well as foodborne and waterborne outbreaks of nonenteric disease. Data provided by NORS users, when known, for drinking water outbreaks include 1) the number of cases, hospitalizations, and deaths; 2) the etiologic agent (confirmed or suspected); 3) the implicated type of water system (e.g., community or individual or private); 4) the setting of exposure (e.g., hospital or health care facility; hotel, motel, lodge, or inn; or private residence); and 5) relevant epidemiologic and environmental data needed to describe the outbreak and characterize contributing factors.

Results

During 2015-2020, public health officials from 28 states voluntarily reported 214 outbreaks associated with drinking water and 454 contributing factor types. The reported etiologies included 187 (87%) biofilm associated, 24 (11%) enteric illness associated, two (1%) unknown, and one (<1%) chemical or toxin. A total of 172 (80%) outbreaks were linked to water from public water systems, 22 (10%) to unknown water systems, 17 (8%) to individual or private systems, and two (0.9%) to other systems; one (0.5%) system type was not reported. Drinking water-associated outbreaks resulted in at least 2,140 cases of illness, 563 hospitalizations (26% of cases), and 88 deaths (4% of cases). Individual or private water systems were implicated in 944 (43%) cases, 52 (9%) hospitalizations, and 14 (16%) deaths.Enteric illness-associated pathogens were implicated in 1,299 (61%) of all illnesses, and 10 (2%) hospitalizations. No deaths were reported. Among these illnesses, three pathogens (norovirus, Shigella, and Campylobacter) or multiple etiologies including these pathogens resulted in 1,225 (94%) cases. The drinking water source was identified most often (n = 34; 7%) as the contributing factor in enteric disease outbreaks. When water source (e.g., groundwater) was known (n = 14), wells were identified in 13 (93%) of enteric disease outbreaks.Most biofilm-related outbreak reports implicated Legionella (n = 184; 98%); two nontuberculous mycobacteria (NTM) (1%) and one Pseudomonas (0.5%) outbreaks comprised the remaining. Legionella-associated outbreaks generally increased over the study period (14 in 2015, 31 in 2016, 30 in 2017, 34 in 2018, 33 in 2019, and 18 in 2020). The Legionella-associated outbreaks resulted in 786 (37%) of all illnesses, 544 (97%) hospitalizations, and 86 (98%) of all deaths. Legionella also was the outbreak etiology in 160 (92%) public water system outbreaks. Outbreak reports cited the premise or point of use location most frequently as the contributing factor for Legionella and other biofilm-associated pathogen outbreaks (n = 287; 63%). Legionella was reported to NORS in 2015 and 2019 as the cause of three outbreaks in private residences (2).

Interpretation

The observed range of biofilm and enteric drinking water pathogen contributing factors illustrate the complexity of drinking water-related disease prevention and the need for water source-to-tap prevention strategies. Legionella-associated outbreaks have increased in number over time and were the leading cause of reported drinking water outbreaks, including hospitalizations and deaths. Enteric illness outbreaks primarily linked to wells represented approximately half the cases during this reporting period. This report enhances CDC efforts to estimate the U.S. illness and health care cost impacts of waterborne disease, which revealed that biofilm-related pathogens, NTM, and Legionella have emerged as the predominant causes of hospitalizations and deaths from waterborne- and drinking water-associated disease.

Public Health Action

Public health departments, regulators, and drinking water partners can use these findings to identify emerging waterborne disease threats, guide outbreak response and prevention programs, and support drinking water regulatory efforts.

Enteric pathogen reduction targets for onsite non-potable water systems: A critical evaluation

Onsite non-potable water systems (ONWS) collect and treat local source waters for non-potable end uses such as toilet flushing and irrigation. Quantitative microbial risk assessment (QMRA) has been used to set pathogen log10-reduction targets (LRTs) for ONWS to achieve the risk benchmark of 10-4 infections per person per year (ppy) in a series of two efforts completed in 2017 and 2021. In this work, we compare and synthesize the ONWS LRT efforts to inform the selection of pathogen LRTs. For onsite wastewater, greywater, and stormwater, LRTs for human enteric viruses and parasitic protozoa were within 1.5-log10 units between 2017 and 2021 efforts, despite differences in approaches used to characterize pathogens in these waters. For onsite wastewater and greywater, the 2017 effort used an epidemiology-based model to simulate pathogen concentrations contributed exclusively from onsite waste and selected Norovirus as the viral reference pathogen; the 2021 effort used municipal wastewater pathogen data and cultivable adenoviruses as the reference viral pathogen. Across source waters, the greatest differences occurred for viruses in stormwater, given the newly available municipal wastewater characterizations used for modeling sewage contributions in 2021 and the different selection of reference pathogens (Norovirus vs. adenoviruses). The roof runoff LRTs support the need for protozoa treatment, but these remain difficult to characterize due to the pathogen variability in roof runoff across space and time. The comparison highlights adaptability of the risk-based approach, allowing for updated LRTs as site specific or improved information becomes available. Future research efforts should focus on data collection of onsite water sources.

Tenets of a holistic approach to drinking water-associated pathogen research, management, and communication

In recent years, drinking water-associated pathogens that can cause infections in immunocompromised or otherwise susceptible individuals (henceforth referred to as DWPI), sometimes referred to as opportunistic pathogens or opportunistic premise plumbing pathogens, have received considerable attention. DWPI research has largely been conducted by experts focusing on specific microorganisms or within silos of expertise. The resulting mitigation approaches optimized for a single microorganism may have unintended consequences and trade-offs for other DWPI or other interests (e.g., energy costs and conservation). For example, the ecological and epidemiological issues characteristic of Legionella pneumophila diverge from those relevant for Mycobacterium avium and other nontuberculous mycobacteria. Recent advances in understanding DWPI as part of a complex microbial ecosystem inhabiting drinking water systems continues to reveal additional challenges: namely, how can all microorganisms of concern be managed simultaneously? In order to protect public health, we must take a more holistic approach in all aspects of the field, including basic research, monitoring methods, risk-based mitigation techniques, and policy. A holistic approach will (i) target multiple microorganisms simultaneously, (ii) involve experts across several disciplines, and (iii) communicate results across disciplines and more broadly, proactively addressing source water-to-customer system management.

Whither regulation, risk and water safety plans? Case studies from Malaysia and from England and Wales

We explore the interplay between preventative risk management and regulatory style for the implementation of water safety plans in Malaysia and in England and Wales, two jurisdictions with distinct philosophies of approach. Semi-structured interviews were conducted with 32 water safety professionals in Malaysia, 23 in England and Wales, supported by 6 Focus Group Discussions (n = 53 participants). A grounded theory approach produced insights on the transition from drinking water quality surveillance to preventative risk management. Themes familiar to this type of regulatory transition emerged, including concerns about compliance policy; overseeing the risk management controls of regulatees with varied competencies and funds available to drive change; and the portfolio of interventions suited to a more facilitative regulatory style. Because the potential harm from waterborne illness is high where pathogen exposures occur, the transition to risk-informed regulation demands mature organisational cultures among water utilities and regulators, and a laser-like focus on ensuring risk management controls are delivered within water supply systems.

A risk-based evaluation of onsite, non-potable reuse systems developed in compliance with conventional water quality measures

Water quality standards (WQSs) based on water quality measures (e.g., fecal indicator bacteria (FIB)) have been used by regulatory agencies to assess onsite, non-potable water reuse systems. A risk-based approach, based on quantitative microbial risk assessment, was developed to define treatment requirements that achieve benchmark levels of risk. This work compared these approaches using the predicted annual infection risks for non-potable reuse systems that comply with WQSs along with the benchmark risk levels achieved by the risk-based systems. The systems include a recirculating synthetic sand filter or an aerobic membrane bioreactor (MBR) combined with disinfection. The greywater MBR system had predicted risks in the range of the selected benchmark levels. However, wastewater reuse with systems that comply with WQSs had uncertain and potentially high predicted risks (i.e., >10-2 infections per person per year) in residential applications, due to exposures to viruses and protozoa. The predicted risks illustrate that WQSs based on FIB treatment performance do not ensure adequate treatment removal of viruses and protozoa. We present risk-based log10 pathogen reduction targets for intermediate-sized non-potable systems, which are 0.5 log10 less than those previously proposed for district-sized systems. Still, pathogen treatment performance data are required to better manage non-potable reuse risk.

Can routine monitoring of E. coli fully account for peak event concentrations at drinking water intakes in agricultural and urban rivers?

In several jurisdictions, the arithmetic mean of Escherichia coli concentrations in raw water serves as the metric to set minimal treatment requirements by drinking water treatment plants (DWTPs). An accurate and precise estimation of this mean is therefore critical to define adequate requirements. Distributions of E. coli concentrations in surface water can be heavily skewed and require statistical methods capable of characterizing uncertainty. We present four simple parametric models with different upper tail behaviors (gamma, log-normal, Lomax, mixture of two log-normal distributions) to explicitly account for the influence of peak events on the mean concentration. The performance of these models was tested using large E. coli data sets (200-1800 samples) from raw water regulatory monitoring at six DWTPs located in urban and agricultural catchments. Critical seasons of contamination and hydrometeorological factors leading to peak events were identified. Event-based samples were collected at an urban DWTP intake during two hydrometeorological events using online β-d-glucuronidase activity monitoring as a trigger. Results from event-based sampling were used to verify whether selected parametric distributions predicted targeted peak events. We found that the upper tail of the log-normal and the Lomax distributions better predicted large concentrations than the upper tail of the gamma distribution. Weekly sampling for two years in urban catchments and for four years in agricultural catchments generated reasonable estimates of the average raw water E. coli concentrations. The proposed methodology can be easily used to inform the development of sampling strategies and statistical indices to set site-specific treatment requirements.

Cryptosporidium species and subtypes in animals inhabiting drinking water catchments in three states across Australia

As part of long-term monitoring of Cryptosporidium in water catchments serving Western Australia, New South Wales (Sydney) and Queensland, Australia, we characterised Cryptosporidium in a total of 5774 faecal samples from 17 known host species and 7 unknown bird samples, in 11 water catchment areas over a period of 30 months (July 2013 to December 2015). All samples were initially screened for Cryptosporidium spp. at the 18S rRNA locus using a quantitative PCR (qPCR). Positives samples were then typed by sequence analysis of an 825 bp fragment of the 18S gene and subtyped at the glycoprotein 60 (gp60) locus (832 bp). The overall prevalence of Cryptosporidium across the various hosts sampled was 18.3% (1054/5774; 95% CI, 17.3-19.3). Of these, 873 samples produced clean Sanger sequencing chromatograms, and the remaining 181 samples, which initially produced chromatograms suggesting the presence of multiple different sequences, were re-analysed by Next- Generation Sequencing (NGS) to resolve the presence of Cryptosporidium and the species composition of potential mixed infections. The overall prevalence of confirmed mixed infection was 1.7% (98/5774), and in the remaining 83 samples, NGS only detected one species of Cryptosporidium. Of the 17 Cryptosporidium species and four genotypes detected (Sanger sequencing combined with NGS), 13 are capable of infecting humans; C. parvum, C. hominis, C. ubiquitum, C. cuniculus, C. meleagridis, C. canis, C. felis, C. muris, C. suis, C. scrofarum, C. bovis, C. erinacei and C. fayeri. Oocyst numbers per gram of faeces (g^-1) were also determined using qPCR, with medians varying from 6021-61,064 across the three states. The significant findings were the detection of C. hominis in cattle and kangaroo faeces and the high prevalence of C. parvum in cattle. In addition, two novel C. fayeri subtypes (IVaA11G3T1 and IVgA10G1T1R1) and one novel C. meleagridis subtype (IIIeA18G2R1) were identified. This is also the first report of C. erinacei in Australia. Future work to monitor the prevalence of Cryptosporidium species and subtypes in animals in these catchments is warranted.

Direct potable reuse microbial risk assessment methodology: Sensitivity analysis and application to State log credit allocations

Understanding pathogen risks is a critically important consideration in the design of water treatment, particularly for potable reuse projects. As an extension to our published microbial risk assessment methodology to estimate infection risks associated with Direct Potable Reuse (DPR) treatment train unit process combinations, herein, we (1) provide an updated compilation of pathogen density data in raw wastewater and dose-response models; (2) conduct a series of sensitivity analyses to consider potential risk implications using updated data; (3) evaluate the risks associated with log credit allocations in the United States; and (4) identify reference pathogen reductions needed to consistently meet currently applied benchmark risk levels. Sensitivity analyses illustrated changes in cumulative annual risks estimates, the significance of which depends on the pathogen group driving the risk for a given treatment train. For example, updates to norovirus (NoV) raw wastewater values and use of a NoV dose-response approach, capturing the full range of uncertainty, increased risks associated with one of the treatment trains evaluated, but not the other. Additionally, compared to traditional log-credit allocation approaches, our results indicate that the risk methodology provides more nuanced information about how consistently public health benchmarks are achieved. Our results indicate that viruses need to be reduced by 14 logs or more to consistently achieve currently applied benchmark levels of protection associated with DPR. The refined methodology, updated model inputs, and log credit allocation comparisons will be useful to regulators considering DPR projects and design engineers as they consider which unit treatment processes should be employed for particular projects.

Risk-based enteric pathogen reduction targets for non-potable and direct potable use of roof runoff, stormwater, and greywater

This paper presents risk-based enteric pathogen log reduction targets for non-potable and potable uses of a variety of alternative source waters (i.e., locally-collected greywater, roof runoff, and stormwater). A probabilistic Quantitative Microbial Risk Assessment (QMRA) was used to derive the pathogen log10 reduction targets (LRTs) that corresponded with an infection risk of either 10-4 per person per year (ppy) or 10-2 ppy. The QMRA accounted for variation in pathogen concentration and sporadic pathogen occurrence (when data were available) in source waters for reference pathogens in the genera Rotavirus, Mastadenovirus(human adenoviruses), Norovirus, Campylobacter, Salmonella, Giardia and Cryptosporidium. Non-potable uses included indoor use (for toilet flushing and clothes washing) with occasional accidental ingestion of treated non-potable water (or cross-connection with potable water), and unrestricted irrigation for outdoor use. Various exposure scenarios captured the uncertainty from key inputs, i.e., the pathogen concentration in source water; the volume of water ingested; and for the indoor use, the frequency of and the fraction of the population exposed to accidental ingestion. Both potable and non-potable uses required pathogen treatment for the selected waters and the LRT was generally greater for potable use than non-potable indoor use and unrestricted irrigation. The difference in treatment requirements among source waters was driven by the microbial quality of the water - both the density and occurrence of reference pathogens. Greywater from collection systems with 1000 people had the highest LRTs; however, those for greywater collected from a smaller population (~ 5 people), which have less frequent pathogen occurrences, were lower. Stormwater had highly variable microbial quality, which resulted in a range of possible treatment requirements. The microbial quality of roof runoff, and thus the resulting LRTs, remains uncertain due to lack of relevant pathogen data.

Setback distances between small biological wastewater treatment systems and drinking water wells against virus contamination in alluvial aquifers

Contamination of groundwater by pathogenic viruses from small biological wastewater treatment system discharges in remote areas is a major concern. To protect drinking water wells against virus contamination, safe setback distances are required between wastewater disposal fields and water supply wells. In this study, setback distances are calculated for alluvial sand and gravel aquifers for different vadose zone and aquifer thicknesses and horizontal groundwater gradients. This study applies to individual households and small settlements (1-20 persons) in decentralized locations without access to receiving surface waters but with the legal obligation of biological wastewater treatment. The calculations are based on Monte Carlo simulations using an analytical model that couples vertical unsaturated and horizontal saturated flow with virus transport. Hydraulic conductivities and water retention curves were selected from reported distribution functions depending on the type of subsurface media. The enteric virus concentration in effluent discharge was calculated based on reported ranges of enteric virus concentration in faeces, virus infectivity, suspension factor, and virus reduction by mechanical-biological wastewater treatment. To meet the risk target of <10^-4infections/person/year, a 12 log₁₀ reduction was required, using a linear dose-response relationship for the total amount of enteric viruses, at very low exposure concentrations. The results of this study suggest that the horizontal setback distances vary widely ranging 39 to 144m in sand aquifers, 66-289m in gravel aquifers and 1-2.5km in coarse gravel aquifers. It also varies for the same aquifers, depending on the thickness of the vadose zones and the groundwater gradient. For vulnerable fast-flow alluvial aquifers like coarse gravels, the calculated setback distances were too large to achieve practically. Therefore, for this category of aquifer, a high level of treatment is recommended before the effluent is discharged to the ground surface.

Cryptosporidium Infection Risk: Results of New Dose-Response Modeling

Cryptosporidium human dose-response data from seven species/isolates are used to investigate six models of varying complexity that estimate infection probability as a function of dose. Previous models attempt to explicitly account for virulence differences among C. parvum isolates, using three or six species/isolates. Four (two new) models assume species/isolate differences are insignificant and three of these (all but exponential) allow for variable human susceptibility. These three human-focused models (fractional Poisson, exponential with immunity and beta-Poisson) are relatively simple yet fit the data significantly better than the more complex isolate-focused models. Among these three, the one-parameter fractional Poisson model is the simplest but assumes that all Cryptosporidium oocysts used in the studies were capable of initiating infection. The exponential with immunity model does not require such an assumption and includes the fractional Poisson as a special case. The fractional Poisson model is an upper bound of the exponential with immunity model and applies when all oocysts are capable of initiating infection. The beta Poisson model does not allow an immune human subpopulation; thus infection probability approaches 100% as dose becomes huge. All three of these models predict significantly (>10x) greater risk at the low doses that consumers might receive if exposed through drinking water or other environmental exposure (e.g., 72% vs. 4% infection probability for a one oocyst dose) than previously predicted. This new insight into Cryptosporidium risk suggests additional inactivation and removal via treatment may be needed to meet any specified risk target, such as a suggested 10^-4 annual risk of Cryptosporidium infection.

Adoption of a microbial health-based target for Australian drinking water regulation

The health-based targets of 1 in 10,000 for infection and 10(-6) disability adjusted life years (DALYs) per person per year are increasingly being considered, or have already been adopted, to define microbial safety targets for water. The aim of this paper is to convey information about how these two targets compare by converting each of the target values to a common metric. The metric chosen for viral (rotavirus and norovirus) and protozoan (Cryptosporidium) reference pathogens is the estimated maximum number of annual drinking water-associated cases of acute diarrhoeal disease tolerated. For the reference bacterial pathogen Campylobacter, sequelae to acute diarrhoeal illness have also been considered in estimating the tolerable number of cases for the DALY target. Also investigated is whether non-compliance with targets would be detected as a waterborne disease outbreak by the health surveillance system in an extreme hypothetical situation whereby all tolerable cases per annum occurred as a single event. The paper highlights that verification of compliance with targets cannot be demonstrated by the absence of reported drinking water-associated outbreaks alone and concludes that introduction of a quantitative health-based outcome for drinking water in Australia would help improve water quality management by providing a common goal directly linked to health outcomes.