Evaluation of virus removal in membrane bioreactor (MBR) and conventional activated sludge (CAS) processes based on long-term monitoring at two wastewater treatment plants.

The membrane bioreactor (MBR) process always offers better wastewater treatment than conventional activated sludge (CAS) treatment. However, the difference in their efficacy of virus reduction remains unknown. To investigate this, we monitored virus concentrations before and after MBR and CAS processes over 2 years. Concentrations of norovirus genotypes I and II (NoV GI and GII), aichivirus (AiV), F-specific RNA phage genotypes I, II, and III (GI-, GII-, and GIII-FRNAPHs), and pepper mild mottle virus (PMMoV) were measured by a quantitative polymerase chain reaction (qPCR) method at two municipal wastewater treatment plants (WWTPs A and B) in Japan. Virus concentration datasets containing left-censored data were estimated by using both maximum likelihood estimation (MLE) and robust regression on order statistics (rROS) approaches. PMMoV was the most prevalent at both WWTPs, with median concentrations of 7.5 to 8.8 log10 copies/L before treatment. Log10 removal values (LRVs) of all viruses based on means and standard deviations of concentrations before and after treatment were consistently higher following MBR than following CAS. We used NoV GII as a model pathogen in a quantitative microbial risk assessment of the treated water, and we estimated the additional reductions required following MBR and CAS processes to meet the guideline of 10-6 DALYs pppy for safe wastewater reuse.

Quantitative microbial risk assessment for ingestion of antibiotic resistance genes from private wells contaminated by human and livestock fecal sources.

We used quantitative microbial risk assessment to estimate ingestion risk for intI1, erm(B), sul1, tet(A), tet(W), and tet(X) in private wells contaminated by human and/or livestock feces. Genes were quantified with five human-specific and six bovine-specific microbial source-tracking (MST) markers in 138 well-water samples from a rural Wisconsin county. Daily ingestion risk (probability of swallowing ≥1 gene) was based on daily water consumption and a Poisson exposure model. Calculations were stratified by MST source and soil depth over the aquifer where wells were drilled. Relative ingestion risk was estimated using wells with no MST detections and >6.1 m soil depth as a referent category. Daily ingestion risk varied from 0 to 8.8 × 10-1 by gene and fecal source (i.e., human or bovine). The estimated number of residents ingesting target genes from private wells varied from 910 (tet(A)) to 1,500 (intI1 and tet(X)) per day out of 12,000 total. Relative risk of tet(A) ingestion was significantly higher in wells with MST markers detected, including wells with ≤6.1 m soil depth contaminated by bovine markers (2.2 [90% CI: 1.1-4.7]), wells with >6.1 m soil depth contaminated by bovine markers (1.8 [1.002-3.9]), and wells with ≤6.1 m soil depth contaminated by bovine and human markers simultaneously (3.1 [1.7-6.5]). Antibiotic resistance genes (ARGs) were not necessarily present in viable microorganisms, and ingestion is not directly associated with infection. However, results illustrate relative contributions of human and livestock fecal sources to ARG exposure and highlight rural groundwater as a significant point of exposure.IMPORTANCEAntibiotic resistance is a global public health challenge with well-known environmental dimensions, but quantitative analyses of the roles played by various natural environments in transmission of antibiotic resistance are lacking, particularly for drinking water. This study assesses risk of ingestion for several antibiotic resistance genes (ARGs) and the class 1 integron gene (intI1) in drinking water from private wells in a rural area of northeast Wisconsin, United States. Results allow comparison of drinking water as an exposure route for antibiotic resistance relative to other routes like food and recreational water. They also enable a comparison of the importance of human versus livestock fecal sources in the study area. Our study demonstrates the previously unrecognized importance of untreated rural drinking water as an exposure route for antibiotic resistance and identifies bovine fecal material as an important exposure factor in the study setting.

Occurrence, transmission and risks assessment of pathogens in aquatic environments accessible to humans.

Pathogens are ubiquitously detected in various natural and engineered water systems, posing potential threats to public health. However, it remains unclear which human-accessible waters are hotspots for pathogens, how pathogens transmit to these waters, and what level of health risk associated with pathogens in these environments. This review collaboratively focuses and summarizes the contamination levels of pathogens on the 5 water systems accessible to humans (natural water, drinking water, recreational water, wastewater, and reclaimed water). Then, we showcase the pathways, influencing factors and simulation models of pathogens transmission and survival. Further, we compare the health risk levels of various pathogens through Quantitative Microbial Risk Assessment (QMRA), and assess the limitations of water-associated QMRA application. Pathogen levels in wastewater are consistently higher than in other water systems, with no significant variation for Cryptosporidium spp. among five water systems. Hydraulic conditions primarily govern the transmission of pathogens into human-accessible waters, while environmental factors such as temperature impact pathogens survival. The median and mean values of computed public health risk levels posed by pathogens consistently surpass safety thresholds, particularly in the context of recreational waters. Despite the highest pathogens levels found in wastewater, the calculated health risk is significantly lower than in other water systems. Except pathogens concentration, variables like the exposure mode, extent, and frequency are also crucial factors influencing the public health risk in water systems. This review shares valuable insights to the more accurate assessment and comprehensive management of public health risk in human-accessible water environments.

Social Distance Approximation on Public Transport Using Stereo Depth Camera and Passenger Pose Estimation.

In order to effectively balance enforced guidance/regulation during a pandemic and limit infection transmission, with the necessity for public transportation services to remain safe and operational, it is imperative to understand and monitor environmental conditions and typical behavioural patterns within such spaces. Social distancing ability on public transport as well as the use of advanced computer vision techniques to accurately measure this are explored in this paper. A low-cost depth-sensing system is deployed on a public bus as a means to approximate social distancing measures and study passenger habits in relation to social distancing. The results indicate that social distancing on this form of public transport is unlikely for an individual beyond a 28% occupancy threshold, with an 89% chance of being within 1-2 m from at least one other passenger and a 57% chance of being within less than one metre from another passenger at any one point in time. Passenger preference for seating is also analysed, which clearly demonstrates that for typical passengers, ease of access and comfort, as well as seats having a view, are preferred over maximising social-distancing measures. With a highly detailed and comprehensive set of acquired data and accurate measurement capability, the employed equipment and processing methodology also prove to be a robust approach for the application.

Quantitative risk assessment of foodborne Salmonella illness by estimating cooking effect on eggs from retail markets.

In this study, we performed a quantitative microbial risk assessment (QMRA) of Salmonella through intake of egg consumption after cooking (dry-heat, moist-heat, and raw consumption). Egg samples (n = 201) from retail markets were analyzed for the presence of Salmonella. In addition, temperature and time were investigated during egg transit, storage, and display. A predictive model was developed to characterize the kinetic behavior of Salmonella in eggs, and data on egg consumption and frequency were collected. Eventually, the data was simulated to estimate egg-related foodborne illnesses. Salmonella was not found in any of the 201 egg samples. Thus, the estimated initial contamination level was -4.0 Log CFU/g. With R2 values of 0.898 and 0.922, the constructed predictive models were adequate for describing the fate of Salmonella in eggs throughout distribution and storage. Eggs were consumed raw (1.5%, 39.2 g), dry-heated (57.5%, 43.0 g), and moist-heated (41%, 36.1 g). The probability of foodborne Salmonella illness from the consumption of cooked eggs was evaluated to be 6.8×10-10. Additionally, the probability of foodborne illness not applied cooking methods was 1.9×10-7, indicating that Salmonella can be reduced by cooking. Therefore, the risk of Salmonella infection through consumption of eggs after cooking might be low in S. Korea.

Is Personal Protective Equipment Worth the Hassle? Annual Risk of Cryptosporidiosis to Dairy Farmers and How Personal Protective Equipment and Handwashing Can Mitigate It.

Cows are known carriers of Cryptosporidium parvum (C. parvum), a protozoa that can cause the gastrointestinal illness cryptosporidiosis in humans. Despite this potential exposure, dairy farmers tend to wear personal protective equipment (PPE) to protect the milk from contamination, rather than to protect themselves from zoonotic diseases, such as cryptosporidiosis. In this study, cow feces were collected from individual cattle on dairy farms and analyzed for C. parvum using qPCR. Quantitative microbial risk assessment (QMRA) was used to determine the risk of cryptosporidiosis to the dairy farmer with and without the use of handwashing and PPE (gloves and masks). The annualized risk of cryptosporidiosis to dairy farmers was 29.08% but was reduced significantly in each of the three interventions. Among the individual interventions, glove use provided the greatest reduction in risk, bringing the annual risk of cryptosporidiosis to 4.82%. Implementing regular handwashing, the use of gloves and a mask brought the annual risk of cryptosporidiosis to 1.29%. This study provides evidence that handwashing and PPE use can significantly reduce the risk of cryptosporidiosis to farmers and is worth implementing despite potential barriers such as discomfort and cost.

Use of risk assessment and predictive microbiology in regulatory science related to the scientific opinions of the EFSA BIOHAZ Panel.

EFSA's Panel on Biological Hazards (BIOHAZ Panel) deals with questions on biological hazards relating to food safety and food-borne diseases. This covers food-borne zoonoses, transmissible spongiform encephalopathies, antimicrobial resistance, food microbiology, food hygiene, animal-by products, and associated waste management issues. The scientific assessments are diverse and frequently the development of new methodological approaches is required to deal with a mandate. Among the many risk factors, product characteristics (pH, water activity etc.), time and temperature of processing and storage along the food supply chain are highly relevant for assessing the biological risks. Therefore, predictive microbiology becomes an essential element of the assessments. Uncertainty analysis is incorporated in all BIOHAZ scientific assessments, to meet the general requirement for transparency. Assessments should clearly and unambiguously state what sources of uncertainty have been identified and their impact on the conclusions of the assessment. Four recent BIOHAZ Scientific Opinions are presented to illustrate the use of predictive modelling and quantitative microbial risk assessment principles in regulatory science. The Scientific Opinion on the guidance on date marking and related food information, gives a general overview on the use of predictive microbiology for shelf-life assessment. The Scientific Opinion on the efficacy and safety of high-pressure processing of food provides an example of inactivation modelling and compliance with performance criteria. The Scientific Opinion on the use of the so-called 'superchilling' technique for the transport of fresh fishery products illustrates the combination of heat transfer and microbial growth modelling. Finally, the Scientific Opinion on the delayed post-mortem inspection in ungulates, shows how variability and uncertainty, were quantitatively embedded in assessing the probability of Salmonella detection on carcasses, via stochastic modelling and expert knowledge elicitation.

Assessing the additional health burden of antibiotic resistant Enterobacteriaceae in surface waters through an integrated QMRA and DALY approach.

Antibiotic resistant Enterobacteriaceae pose a significant threat to public health. However, limited studies have evaluated the health risks associated with exposure to antibiotic-resistant bacteria (ARB), especially in natural environments. While quantitative microbial risk assessment (QMRA) assesses microbial risks in terms of the probability of infection, it does not account for the severity of health outcomes. In this study, a QMRA-DALY model was developed to integrate QMRA with health burden (disability-adjusted life years (DALY)) from infections caused by ARB. The model considers uncertainties in probability of infection and health burden assessment using Monte Carlo simulations. The study collected antimicrobial resistance (AMR) surveillance data from surface waters with different land uses. Results revealed water bodies with agricultural land use to be the main AMR hotspots, with the highest additional health burden observed in infections caused by meropenem-resistant E. coli (∆DALY = 0.0105 DALY/event) compared to antibiotic-susceptible E. coli. The estimated ∆DALY for antibiotic-resistant K. pneumoniae was lower than for antibiotic-resistant E. coli (highest ∆DALY = 0.00048 DALY/event). The study highlights the need for better evaluation of AMR associated health burden, and effective measures to mitigate the risks associated with antibiotic-resistant bacteria in natural environments.

Combined Infection Control Interventions Protect Essential Food Workers from Occupational Exposures to SARS-CoV-2 in the Agricultural Environment.

Essential food workers experience elevated risks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection due to prolonged occupational exposures in food production and processing areas, shared transportation (car or bus), and employer-provided shared housing. Our goal was to quantify the daily cumulative risk of SARS-CoV-2 infection for healthy susceptible produce workers and to evaluate the relative reduction in risk attributable to food industry interventions and vaccination. We simulated daily SARS-CoV-2 exposures of indoor and outdoor produce workers through six linked quantitative microbial risk assessment (QMRA) model scenarios. For each scenario, the infectious viral dose emitted by a symptomatic worker was calculated across aerosol, droplet, and fomite-mediated transmission pathways. Standard industry interventions (2-m physical distancing, handwashing, surface disinfection, universal masking, ventilation) were simulated to assess relative risk reductions from baseline risk (no interventions, 1-m distance). Implementation of industry interventions reduced an indoor worker's relative infection risk by 98.0% (0.020; 95% uncertainty interval [UI], 0.005 to 0.104) from baseline risk (1.00; 95% UI, 0.995 to 1.00) and an outdoor worker's relative infection risk by 94.5% (0.027; 95% UI, 0.013 to 0.055) from baseline risk (0.487; 95% UI, 0.257 to 0.825). Integrating these interventions with two-dose mRNA vaccinations (86 to 99% efficacy), representing a worker's protective immunity to infection, reduced the relative infection risk from baseline for indoor workers by 99.9% (0.001; 95% UI, 0.0002 to 0.005) and outdoor workers by 99.6% (0.002; 95% UI, 0.0003 to 0.005). Consistent implementation of combined industry interventions, paired with vaccination, effectively mitigates the elevated risks from occupationally acquired SARS-CoV-2 infection faced by produce workers. IMPORTANCE This is the first study to estimate the daily risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection across a variety of indoor and outdoor environmental settings relevant to food workers (e.g., shared transportation [car or bus], enclosed produce processing facility and accompanying breakroom, outdoor produce harvesting field, shared housing facility) through a linked quantitative microbial risk assessment framework. Our model has demonstrated that the elevated daily SARS-CoV-2 infection risk experienced by indoor and outdoor produce workers can be reduced below 1% when vaccinations (optimal vaccine efficacy, 86 to 99%) are implemented with recommended infection control strategies (e.g., handwashing, surface disinfection, universal masking, physical distancing, and increased ventilation). Our novel findings provide scenario-specific infection risk estimates that can be utilized by food industry managers to target high-risk scenarios with effective infection mitigation strategies, which was informed through more realistic and context-driven modeling estimates of the infection risk faced by essential food workers daily. Bundled interventions, particularly if they include vaccination, yield significant reductions (>99%) in daily SARS-CoV-2 infection risk for essential food workers in enclosed and open-air environments.

Environmental DNA clarifies impacts of combined sewer overflows on the bacteriology of an urban river and resulting risks to public health.

There is no reference of microbiological water quality in the European Union's Water Framework Directive, adapted into English law, and consequently microbial water quality is not routinely monitored in English rivers, except for two recently designated bathing water sites. To address this knowledge gap, we developed an innovative monitoring approach for quantitative assessment of combined sewer overflow (CSO) impacts on the bacteriology of receiving rivers. Our approach combines conventional and environmental DNA (eDNA) based methods to generate multiple lines of evidence for assessing risks to public health. We demonstrated this approach by investigating spatiotemporal variation in the bacteriology of the Ouseburn in northeast England for different weather conditions in the summer and early autumn of the year 2021 across eight sampling locations that comprised rural, urban, and recreational land use settings. We characterized pollution source attributes by collecting sewage from treatment works and CSO discharge at the peak of a storm event. CSO discharge was characterized by log10 values per 100 mL (average ± stdev) of 5.12 ± 0.03 and 4.90 ± 0.03 for faecal coliforms and faecal streptococci, and 6.00 ± 0.11 and 7.78 ± 0.04 for rodA and HF183 genetic markers, for E. coli and human host associated Bacteroides, respectively, indicating about 5 % sewage content. SourceTracker analysis of sequencing data attributed 72-77 % of bacteria in the downstream section of the river during a storm event to CSO discharge sources, versus only 4-6 % to rural upstream sources. Data from sixteen summer sampling events in a public park exceeded various guideline values for recreational water quality. Quantitative microbial risk assessment (QMRA) predicted a median and 95th percentile risk of 0.03 and 0.39, respectively, of contracting a bacterial gastrointestinal disease when wading and splashing around in the Ouseburn. We show clearly why microbial water quality should be monitored where rivers flow through public parks, irrespective of their bathing water designation.

Quantitative Risk Assessment of Hepatitis a Virus Infection Arising from the Consumption of Fermented Clams in South Korea.

This study estimated the risk of hepatitis A virus (HAV) foodborne illness outbreaks through the consumption of fermented clams in South Korea. HAV prevalence in fermented clams was obtained from the Ministry of Food and Drug Safety Report, 2019. Fermented clam samples (2 g) were inoculated with HAV and stored at -20-25 °C. Based on the HAV titer (determined using plaque assay) in fermented clams according to storage, the Baranyi predictive models provided by Combase were applied to describe the kinetic behavior of HAV in fermented clams. The initial estimated HAV contamination level was -3.7 Log PFU/g. The developed predictive models revealed that, when the temperature increased, the number of HAV plaques decreased. The Beta-Poisson model was chosen for determining the dose-response of HAV, and the simulation revealed that there was a 6.56 × 10-11/person/day chance of contracting HAV foodborne illness by eating fermented clams. However, when only regular consumers of fermented clams were assumed as the population, the probability of HAV foodborne illness increased to 8.11 × 10-8/person/day. These results suggest that, while there is a low likelihood of HAV foodborne illness from consuming fermented clams across the country, regular consumers should be aware of the possibility of foodborne illness.

Occurrence and Quantitative Microbial Risk Assessment of Methicillin-Resistant Staphylococcus aureus (MRSA) in a Sub-Catchment of the Yodo River Basin, Japan.

The occurrence of Staphylococcus aureus (S. aureus) and methicillin-resistant S. aureus (MRSA) in a sub-catchment of the Yodo River Basin, a representative water system of a drinking water source in Japan, was investigated. The chromogenic enzyme-substrate medium method was used for the detection of S. aureus and MRSA by the presence or absence of antimicrobials in the medium for viable bacteria in a culture-based setting. The contributions of S. aureus and MRSA from wastewater to the rivers were estimated based on mass flux-based analysis, and quantitative microbial risk assessment (QMRA) was further conducted for S. aureus and MRSA in river environments. The mean abundance of S. aureus and MRSA was 31 and 29 CFU/mL in hospital effluent, 124 and 117 CFU/mL in sewage treatment plant (STP) influent, 16 and 13 CFU/mL in STP effluent, and 8 and 9 CFU/mL in river water, respectively. Contribution of the pollution load derived from the target STP effluent to river water ranged from 2% to 25%. The QMRA showed that to achieve the established health benchmarks, the drinking water treatment process would need to yield 1.7 log10 and 2.9 log10 inactivation in terms of infection risk and disability-adjusted life year (DALY) indexes, respectively. These findings highlight the link between medical environment and the importance of environmental risk management for antimicrobial-resistant bacteria in aquatic environments.

Assessment of the risk of Legionella pneumophila in water distribution systems in hospitals of Tehran city.

When a sensitive host inhales aerosols containing these bacteria, Legionella infection occurs. Therefore, monitoring and assessing Legionella in the environment and water distribution systems of such places are critical due to the prone population in hospitals. However, the health risks of Legionella bacteria in the environment are not adequately evaluated. In this study, for hospitalized patients, we performed a quantitative health risk assessment of Legionella in selected hospitals in Tehran city using two scenarios of shower and toilet faucet exposure. This study identified Legionella in 38 cases (38%) out of 100 samples collected from toilet faucets and showers in 8 hospitals. The information gathered was used for quantitative microbial risk assessment (QMRA). The microbial load transmitted by inhalation was calculated using the concentration of Legionella in water. Other exposure parameters (inhalation rate and exposure time) were obtained using information from other studies and the median length of hospital stay (3.6 days). The exponential model was used to estimate the risk of infection (γ = 0.06) due to Legionella pneumophila (L. pneumophila) inhalation for each exposure event. For the mean concentration obtained for Legionella (103 CFU/L), the risk of infection for toilet faucets and showers was in the range of 0.23-2.3 and 3.5-21.9, respectively, per 10,000 hospitalized patients. The results were compared with the tolerable risk level of infection determined by the US EPA and WHO. The risk values exceeded the WHO values for waterborne pathogens in hospitals in both exposure scenarios. As a result, our QMRA results based on monitoring data showed that despite using treated water (from distribution networks in the urban areas) by hospitals, 38% of the samples were contaminated with Legionella, and faucets and showers can be sources of Legionella transmission. Hence, to protect the health of hospitalized patients, the risk of Legionella infection should be considered.

Developing an Integrated "Regression-QMRA method" to Predict Public Health Risks of Low Impact Developments (LIDs) for Improved Planning.

Worldwide Low Impact Developments (LIDs) are used for sustainable stormwater management; however, both the stormwater and LIDs carry microbial pathogens. The widespread development of LIDs is likely to increase human exposure to pathogens and risk of infection, leading to unexpected disease outbreaks in urban communities. The risk of infection from exposure to LIDs has been assessed via Quantitative Microbial Risk Assessment (QMRA) during the operation of these infrastructures; no effort is made to evaluate these risks during the planning phase of LID treatment train in urban communities. We developed a new integrated "Regression-QMRA method" by examining the relationship between pathogens' concentration and environmental variables. Applying of this methodology to a planned LID train shows that the predicted disease burden of diarrhea from Campylobacter is highest (i.e. 16.902 DALYs/1000 persons/yr) during landscape irrigation and playing on the LID train, followed by Giardia, Cryptosporidium, and Norovirus. These results illustrate that the risk of microbial infection can be predicted during the planning phase of LID treatment train. These predictions are of great value to municipalities and decision-makers to make informed decisions and ensure risk-based planning of stormwater systems before their development.

Statewide Quantitative Microbial Risk Assessment for Waterborne Viruses, Bacteria, and Protozoa in Public Water Supply Wells in Minnesota.

Infection risk from waterborne pathogens can be estimated via quantitative microbial risk assessment (QMRA) and forms an important consideration in the management of public groundwater systems. However, few groundwater QMRAs use site-specific hazard identification and exposure assessment, so prevailing risks in these systems remain poorly defined. We estimated the infection risk for 9 waterborne pathogens based on a 2-year pathogen occurrence study in which 964 water samples were collected from 145 public wells throughout Minnesota, USA. Annual risk across all nine pathogens combined was 3.3 × 10-1 (95% CI: 2.3 × 10-1 to 4.2 × 10-1), 3.9 × 10-2 (2.3 × 10-2 to 5.4 × 10-2), and 1.2 × 10-1 (2.6 × 10-2 to 2.7 × 10-1) infections person-1 year-1 for noncommunity, nondisinfecting community, and disinfecting community wells, respectively. Risk estimates exceeded the U.S. benchmark of 10-4 infections person-1 year-1 in 59% of well-years, indicating that the risk was widespread. While the annual risk for all pathogens combined was relatively high, the average daily doses for individual pathogens were low, indicating that significant risk results from sporadic pathogen exposure. Cryptosporidium dominated annual risk, so improved identification of wells susceptible to Cryptosporidium contamination may be important for risk mitigation.

Numerical simulation for spatial distribution of water aerosol produced from nozzle spray and health risk related to Legionella pneumophila in spray scenarios.

Water spray facilities are widely used in public places for sprinkling or beautifying the environment. However, the potential health risk induced by water aerosols increasingly calls for attention. In this study, the spatial distribution of water aerosols was investigated through the molecular sieve adsorption method, and predicted by discrete phase model (DPM). On this basis, the health risk regarding Legionella pneumophila for specific spray scenarios was evaluated by quantitative microbial risk assessment (QMRA). The results showed that the original droplet size can be described by the Rosin_Rommaler distribution (R2>0.99). The spatial distribution of water aerosols produced from a nozzle spray can be well predicted by the DPM. The concentration of water aerosols showed a sharp decline within 5 m from the nozzle and was not significantly different within 5 m (p>0.05) as for various spray scenarios. However, the difference was significant outside 5 m (p<0.05). Furthermore, a safe contact distance of exceeding 8 m is proposed in spray scenarios considering the risk threshold of 0.0001. Sensitivity analysis demonstrated the concentration of Legionella pneumophila in water aerosols as the critical factor affecting the health risk.

Assessment of Human Health Risks in Tropical Environmental Waters with Microbial Source Tracking Markers.

Human specific microbial source tracking (MST) markers which are highly specific to human waste contamination offer the advantage of better association with human pathogens than traditional microbial indicators. However, the performance of these MST markers may vary across different geographical regions. The magnitude of MST markers also plays an important role in interpreting the health risks. This study aims to (i) validate the specificity and sensitivity of human markers for tropical urban catchments; (ii) identify the threshold concentrations of MST markers, i.e. human polyomaviruses (HPyVs), Bacteroides thetaiotaomicron (B. theta) and Methanobrevibacter smithii (M. smithii), that correspond to the acceptable gastrointestinal (GI) illness risks associated with swimming using the QMRA approach; and (iii) validate the threshold concentrations of MST markers using the surveillance data obtained from the tropical urban environment. Among the three MST markers, HPyVs showed the highest specificity (100%) to sewage samples, followed by M. smithii (97%) and B. theta (90%). All MST markers showed 100% sensitivity towards sewage contamination, with B. theta present in highest abundance in sewage, followed by HPyVs and M. smithii. This study demonstrates a risk-based framework to identify the threshold concentrations of MST markers associated with GI illness risks in environmental waters by considering two main influencing factors (i.e. decay and dilution factors). This study successfully validated the B. theta threshold concentration range (581 to 8073 GC/100 mL) with field data (370 to 6500 GC/100 mL) in estimating GI illness risks with an Enterococcus model. Field data showed that the MST markers at threshold concentrations were able to classify the safe level in more than 83% of the samples, according to GI illness risks from Enterococcus and adenovirus. The study also highlighted the lack of associations between MST markers and GI illness risks from norovirus. With comprehensive information on specificity, sensitivity and threshold concentrations of MST markers, increasing confidence can be placed on identifying human source contamination and evaluating the health risks posed in environmental waters in Singapore.

Legionnaires' disease in dental offices: Quantifying aerosol risks to dental workers and patients.

Legionella pneumophila is an opportunistic bacterial respiratory pathogen that is one of the leading causes of drinking water outbreaks in the United States. Dental offices pose a potential risk for inhalation or aspiration of L. pneumophila due to the high surface area to volume ratio of dental unit water lines-a feature that is conducive to biofilm growth. This is coupled with the use of high-pressure water devices (e.g., ultrasonic scalers) that produce fine aerosols within the breathing zone. Prior research confirms that L. pneumophila occurs in dental unit water lines, but the associated human health risks have not been assessed. We aimed to: (1) synthesize the evidence for transmission and management of Legionnaires' disease in dental offices; (2) create a quantitative modeling framework for predicting associated L. pneumophila infection risk; and (3) highlight influential parameters and research gaps requiring further study. We reviewed outbreaks, management guidance, and exposure studies and used these data to parameterize a quantitative microbial risk assessment (QMRA) model for L. pneumophila in dental applications. Probabilities of infection for dental hygienists and patients were assessed on a per-exposure and annual basis. We also assessed the impact of varying ventilation rates and the use of personal protective equipment (PPE). Following an instrument purge (i.e., flush) and with a ventilation rate of 1.2 air changes per hour, the median per-exposure probability of infection for dental hygienists and patients exceeded a 1-in-10,000 infection risk benchmark. Per-exposure risks for workers during a purge and annual risks for workers wearing N95 masks did not exceed the benchmark. Increasing air change rates in the treatment room from 1.2 to 10 would achieve an ∼85% risk reduction, while utilization of N95 respirators would reduce risks by ∼95%. The concentration of L. pneumophila in dental unit water lines was a dominant parameter in the model and driver of risk. Future risk assessment efforts and refinement of microbiological control protocols would benefit from expanded occurrence datasets for L. pneumophila in dental applications.

Quantitative microbial risk assessment of a non-membrane based indirect potable water reuse system using Bayesian networks.

Risk-based approaches are used to define performance standards for water and wastewater treatment to meet health-based targets and to ensure safe and reliable water quality for desired end use. In this study, a screening level QMRA for a non-membrane based indirect potable reuse (IPR) system utilizing the sequential managed aquifer recharge technology (SMART) concept was conducted. Ambient removals of norovirus, Campylobacter and Cryptosporidium in advanced water treatment (AWT) steps were combined in a probabilistic QMRA utilizing Bayesian networks constructed in Netica. Results revealed that all pathogens complied with disease burden at the 95th percentile, and according to the assumptions taken about pathogen removal, Cryptosporidium was the pathogen with the greatest risk. Through systematic sensitivity analysis, targeted scenario analysis, and backwards inferencing, critical control points for each pathogen were determined, demonstrating the usefulness of Bayesian networks as a diagnostic tool in quantifying risk of water reuse treatment scenarios.

Minimum Information Required to Annotate Food Safety Risk Assessment Models (MIRARAM).

In the last decades, mathematical models and model-based simulations became important elements not only in the area of risk assessment concerning microbiological and chemical hazards but also in modelling biological phenomena in general. Unfortunately, many of the developed models are published in non-standardized ways, which hinders efficient exchange, re-use and continuous improvement of models within the risk assessment domain. The establishment of guidelines for model annotation is an important pre-condition to overcome these obstacles. Additionally, implementation of annotation guidelines can improve transparency, quality control and even aid the clarification of intellectual property rights. Here, we address the question of "What is the minimum set of metadata that should be provided for a model in the risk assessment domain?". The proposed guideline focuses on food safety risk assessment models and is called "Minimum Information Required to Annotate food safety Risk Assessment Models (MIRARAM)". MIRARAM supports the model creator during the model documentation step and could also be used as a checklist by scientific journal editors or database curators. Software developers could take up MIRARAM and develop easy-to-use software tools or new features in existing programs that can help model creators to provide proposed model annotations in harmonized file formats. Based on experiences from similar guidelines in related scientific disciplines (like systems biology), it is expected that MIRARAM could contribute to the promotion of application and re-use of models as well as to implementing more standardized quality control in the food safety modelling domain.