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.

Small water supply systems (SWSSs) are often more vulnerable to waterborne disease outbreaks. In Japan, many SWSSs operate without regulation under the Waterworks Law, yet there is limited investigation into microbial contamination and the associated health risks. In this study, the microbiological water quality of four SWSSs that utilize mountain streams as water sources and do not install water treatment facilities were monitored for over 2 years. In investigated SWSSs, the mean heterotrophic plate counts were below 350 CFU/mL, and the total bacterial loads (16S rDNA concentration) ranged from 4.71 to 5.35 log10 copies/mL. The results also showed the consistent presence of fecal indicator bacteria (FIB), i.e., Escherichia coli and Clostridium perfringens, suggesting the potential of fecal pollution. E. coli was then utilized as an indicator to assess the health risk posed by E. coli O157:H7 and Campylobacter jejuni. The results indicated that the estimated mean annual risk of infection and disability-adjusted life years (DALYs) exceeded acceptable levels in all SWSSs for the two reference pathogens. To ensure microbial water safety, implementing appropriate water treatment facilities with an estimated mean required reduction of 5-6 log10 was necessary. This study highlighted the potential microbial contamination and health risk level in SWSSs that utilize mountain streams as water sources, even though the water sources were almost not affected by human activities. Furthermore, this study would also be helpful in supporting risk-based water management to ensure a safe water supply in SWSSs.

Wastewater discharge and runoff waters are significant sources of human and animal fecal microbes in surface waters. Human-derived fecal contamination of water is generally estimated to pose a greater risk to human health than animal fecal contamination, but animals may serve as reservoirs of zoonotic pathogens. In this study, quantitative microbial risk assessment (QMRA) tools were used to evaluate the hygienic impact of sewage effluents and runoff water from municipalities and animal farms on surface and bathing waters. The human-specific microbial source tracking (MST) marker HF183 was used to evaluate the dilution of fecal pathogens originating from the sewage effluent discharge to the downstream watershed. As novel risk management options, the efficiency of UV-LED disinfection and wetland treatment as well as biochar filtration was tested on-site for the contamination sources. According to the dilution pattern of the MST marker HF183, microbes from wastewater were diluted (2.3-3.7 log10) in the receiving waters. The scenario-based QMRA revealed, that the health risks posed by exposure to human-specific norovirus GII and zoonotic Campylobacter jejuni during the bathing events were evaluated. The risk for gastroenteritis was found to be elevated during wastewater contamination events, where especially norovirus GII infection risk increased (1-15 cases per day among 50 bathers) compared with the business as usual (BAU) situation (1 case per day). The noted C. jejuni infection risk was associated with animal farm contamination (1 case per day, versus 0.2-0.6 cases during BAU). Tertiary treatment of wastewater with wetland treatment and UV-LED disinfection effectively reduced the waterborne gastroenteritis risks associated with bathing. Based on the experiences from this study, a QMRA-based approach for health risk evaluations at bathing sites can be useful and is recommended for bathing site risk assessments in the future. In case of low pathogen numbers at the exposure sites, the MST marker HF183 could be used as a pathogen dilution coefficient for the watershed under evaluation. The full-scale implementation of novel tertiary treatment options at wastewater treatment plants (WWTPs) as well as on-site runoff water treatment options should be considered for infection risk management at locations where scenario-based QMRA implies elevated infection risks.

Occupational exposure to pathogens can pose health risks. This study investigates the viral exposure of workers in a wastewater treatment plant (WWTP) and a swine farm by analyzing aerosol and surfaces samples. Viral contamination was evaluated using quantitative polymerase chain reaction (qPCR) assays, and target enrichment sequencing (TES) was performed to identify the vertebrate viruses to which workers might be exposed. Additionally, Quantitative Microbial Risk Assessment (QMRA) was conducted to estimate the occupational risk associated with viral exposure for WWTP workers, choosing Human Adenovirus (HAdV) as the reference pathogen. In the swine farm, QMRA was performed as an extrapolation, considering a hypothetical zoonotic virus with characteristics similar to Porcine Adenovirus (PAdV). The modelled exposure routes included aerosol inhalation and oral ingestion through contaminated surfaces and hand-to-mouth contact. HAdV and PAdV were widespread viruses in the WWTP and the swine farm, respectively, by qPCR assays. TES identified human and other vertebrate viruses WWTP samples, including viruses from families such as Adenoviridae, Circoviridae, Orthoherpesviridae, Papillomaviridae, and Parvoviridae. In the swine farm, most of the identified vertebrate viruses were porcine viruses belonging to Adenoviridae, Astroviridae, Circoviridae, Herpesviridae, Papillomaviridae, Parvoviridae, Picornaviridae, and Retroviridae. QMRA analysis revealed noteworthy risks of viral infections for WWTP workers if safety measures are not taken. The probability of illness due to HAdV inhalation was higher in summer compared to winter, while the greatest risk from oral ingestion was observed in workspaces during winter. Swine farm QMRA simulation suggested a potential occupational risk in the case of exposure to a hypothetical zoonotic virus. This study provides valuable insights into WWTP and swine farm worker\'s occupational exposure to human and other vertebrate viruses. QMRA and NGS analyses conducted in this study will assist managers in making evidence-based decisions, facilitating the implementation of protection measures, and risk mitigation practices for workers.

Wastewater treatment plants (WWTPs) are the leading sources of potential pathogenic bioaerosol that cause non-negligible health risks. However, bioaerosolization behaviour of potential pathogenic microorganisms (PPMs) migrating from wastewater to the atmosphere is still unclear. This study investigated the occurrence profile of PPMs in wastewater, sludge and bioaerosol, then analyzed bioaerosolization level, impact factors and social function. Staphylococcus aureus was selected as the target due to its pathogenicity, and the health risks of workers, engineers and researchers wearing various masks (N90, N95 and medical masks) were evaluated. The results showed that there were 38 and 64 PPMs in bioaerosol from plant A and B. Streptomyces in plant A (average bioaerosolization index, BI= 237.71) and Acinetobacter in plant B (average BI = 505.88) were more likely to migrate from wastewater to the atmosphere forming bioaerosol. Environmental factors (relative humidity, wind speed and temperature) affected both BI and microbial species of PPMs in different ways. PPMs related to fermentation, aerobic chemoheterotrophy, and chemoheterotrophy are the most abundant. Meanwhile microbial networks from plants A and B showed that PPMs were well-connected. Emission level of Staphylococcus aureus bioaerosol can reach 980 ± 309.19 CFU/m3 in plant A and 715.55 ± 44.17 CFU/m3 in plant B. For three exposure population, disease burden (DB) and annual probability infection (Py) of Staphylococcus aureus bioaerosol in two plants were both higher than the U.S.EPA benchmark (10-4 DALYs pppy). All three masks (N90,N95 and medical masks) can decrease Py and DB by at least one order of magnitude. This study illustrated the bioaerosolization behaviour of PPMs comprehensively, which provides a scientific basis for exposure risk prevention and control.

The Dose Consumed step of the Poultry Food Assess Risk Model (PFARM) for Salmonella and chicken gizzards was presented and compared to the Exposure Assessment step of Quantitative Microbial Risk Assessment (QMRA). The specific objectives were 1) to demonstrate the dose consumed step of PFARM for Salmonella and chicken gizzards; 2) to compare Salmonella dose consumed from cooked chicken gizzards to that from cross-contaminated and temperature-abused lettuce; 3) to determine if Salmonella dose consumed changed over time in a production chain; and 4) to compare PFARM and QMRA predictions of Salmonella dose consumed. The PFARM and QMRA were developed in an Excel notebook and simulated with @Risk. Salmonella prevalence and number data (P = 100) for chicken gizzards (56 g) and scenario analysis were used to address objectives 1, 2, and 4, whereas running windows of 60 consecutive chicken gizzard samples and scenario analysis were used to address objective 3. A lot size of 1,000 kg of chicken gizzards was simulated. Mean portion size was 168 g resulting in the simulation of 5,952 meals per lot. Of these, 3.69 ± 0.32% and 0.49 ± 0.07% (mean ± SD) resulted in Salmonella dose consumed of ≥1 per meal from cooked chicken gizzards and lettuce, respectively. However, the total Salmonella dose consumed per lot from cooked chicken gizzards (272 ± 27) was less (P ≤ 0.05) than from lettuce (6,050 ± 4,929) because of a few highly contaminated (>310 Salmonella) lettuce portions at consumption. Over time in the production chain, Salmonella prevalence and total dose consumed per lot changed (P ≤ 0.05) but the patterns differed. The QMRA predicted higher (P ≤ 0.05) Salmonella dose consumed per meal than PFARM. In part, this was because QMRA only simulated contaminated grams, whereas PFARM simulated contaminated and non-contaminated meals. However, other factors, which are discussed, also contributed to the overestimation of Salmonella dose consumed by QMRA.

There is a limited understanding of the survival responses of Campylobacter jejuni during thermal processing, which must be investigated for appropriate risk assessment and processing. Therefore, we aimed to elucidate the survival response of C. jejuni and develop a predictive model considering strain variability and uncertainty, which are important for quantitative microbial risk assessment (QMRA) or risk-based processing control measures. We employed the most probable curve (MPC) method to consider the uncertainty in cell concentrations. Further, the multivariate normal (MVN) distribution served as a model for strain variability in bacterial survival behavior. The prediction curves from the MVN successfully captured the parameter variability of the most probable curves of each strain. More than ten reference strains effectively described the strain variability in parameters using the MVN distribution. The findings indicated that, with sufficient strain data, the MVN could estimate the strain variability, including unknown strains. The multi-level model for strain variability can potentially become a specialized tool for QMRA and risk-based processing controls. The combined approach of MPC and MVN provides valuable insights into strain variability, emphasizing the importance of accounting for variability and uncertainty in predictive models for QMRA and risk-based processing control measures.

The increase in effluent discharge from wastewater treatment plants (WWTPs) into urban rivers has raised concerns about the potential effects on pathogen risks. This study utilized metagenomic sequencing combined with flow cytometry to analyze pathogen concentrations and antibiotic resistance in a typical effluent-receiving river. Quantitative microbial risk assessment (QMRA) was employed to assess the microbial risks of pathogens. The results indicated obvious spatial-temporal differences (i.e., summer vs. winter and effluent vs. river) in microbial composition. Microcystis emerged as a crucial species contributing to these variations. Pathogen concentrations were found to be higher in the river than in the effluent, with the winter exhibiting higher concentrations compared to the summer. The effluent discharge slightly increased the pathogen concentrations in the river in summer but dramatically reduced them in winter. The combined effects of cyanobacterial bloom and high temperature were considered key factors suppressing pathogen concentrations in summer. Moreover, the prevalence of antibiotic resistance of pathogens in the river was inferior to that in the effluent, with higher levels in winter than in summer. Three high-concentration pathogens (Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa) were selected for QMRA. The results showed that the risks of pathogens exceeded the recommended threshold value. Escherichia coli posed the highest risks. And the fishing scenario posed significantly higher risks than the walking scenario. Importantly, the effluent discharge helped reduce the microbial risks in the receiving river in winter. The study contributes to the management and decision-making regarding microbial risks in the effluent-receiving river.

Extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (E. coli) in animals are considered a human health threat, because this type of bacteria can serve as a reservoir of antibiotic resistant genes and act as a continuous threat of the emergence of new resistant bacteria, in addition to the direct effect of making infection untreatable. Although the prevalence of ESBL producing bacteria in broilers was drastically reduced in the Netherlands, chicken meat still has the highest prevalence among meat products. Therefore, further control of the ESBL-producing E. coli in the broiler production chain is important to reduce public health risks. The main objectives of this study were to evaluate the effectiveness of intervention scenarios to reduce the transmission of ESBL-producing E. coli in the broiler production chain and to quantitatively estimate the risk to public health. In this study, we developed two different types of transmission models that described the observed time-related decline in prevalence during a production round: one with time-dependent decline in susceptibility and one with partial immunity to phylogenetic groups. Both models incorporated the environmental contamination effect between production rounds and within flocks. The parameter values, including transmission rate and recovery rate, were estimated by Approximate Bayesian computation (ABC) method using data from a longitudinal study in a Dutch organic broiler farm. We applied the models to the three production stages in the broiler production chain, beginning from the Parent Stock (PS) farms, the hatcheries, and to the broiler farms. In our models, eggs were collected from different parent stock farms and transported to the hatchery and from there to a broiler farm.The size of a flock and the number of farms were adjusted to the Dutch situation. Both models were able to describe the observed dynamics within and between the production stages equally well, with estimated ESBL-producing E. coli prevalence of 8.98% and 11.47% in broilers at slaughter and 0.12% and 0.15% in humans due to chicken consumption. Both models indicated that improving farm management to eliminate the bacteria from the environment was the most effective intervention, making this outcome robust. Although chicken meat consumption is not a major risk factor for human carriage of the bacteria according to our models, reducing the bacteria in the PS and broiler farm environment to at least one percent can further decrease the prevalence in humans.

In low and medium income countries (LMIC) drinking water sources (wells and boreholes) often contain a high number of pathogenic microorganisms, that can pose significant human and environmental health risks. In this study, a quantitative microbial risk assessment approach based on existing literature was conducted to evaluate and compare the quantitative health risks associated with different age groups using various drinking water supply systems. Results showed that both community-supply and self-supply modes exhibit similar levels of risk. However, the self-supply water source consistently showed higher risks compared to the community-supply one. Borehole water was found to be a more suitable option than well water, consistently showing between 5 and 8 lower health risks for E. coli and fecal coliform levels, respectively. The sensitivity analysis further showed the importance of prioritizing the reduction of E. coli concentration in well water and fecal coliform concentration in borehole water. This study offers a fresh perception on quantifying the impact of exposure concentration and age groups, shedding light on how they affect environmental health risks. These findings provide valuable insights for stakeholders involved in the management and protection of water sources.