Quantitative Risk Assessment Model Research Articles

Analysis of scenarios to reduce the probability of acquiring hemolytic uremic syndrome associated with beef consumption.

The objective of this study was to develop a quantitative microbial risk assessment (QMRA) model to evaluate potential risk mitigation strategies to reduce the probability of acquiring hemolytic uremic syndrome (HUS) associated with beef consumption in Argentina. Five scenarios were simulated to evaluate the effect of interventions on the probability of acquiring HUS from Shiga toxin-producing Escherichia coli (STEC)-contaminated ground beef and commercial hamburger consumption. These control strategies were chosen based on previous results of the sensitivity analysis of a baseline QMRA model. The application of improvement actions in abattoirs not applying Hazard Analysis and Critical Control Points (HACCP) for STEC would result 7.6 times lower in the probability that consumers acquired HUS from ground beef consumption, while the implementation of improvements in butcher shops would lead to a smaller reduction. In abattoirs applying HACCP for STEC, the risk of acquiring HUS from commercial hamburger consumption was significantly reduced. Treatment with 2% lactic acid, hot water and irradiation reduced 4.5, 3.5 and 93.1 times the risk of HUS, respectively. The most efficient interventions, in terms of case reduction, being those that are applied in the initial stages of the meat chain.

Rethinking the uncertainty of African swine fever virus contamination in feed ingredients and risk of introduction into the United States.

Economically relevant pathogens, such as African swine fever virus (ASFV), have been shown to survive when experimentally inoculated in some feed ingredients under the environmental conditions in transoceanic transport models. However, these models did not characterize the likelihood of virus survival under various time and temperature processes that feed ingredients undergo before they are added to swine diets. Here, we developed a quantitative risk assessment model to estimate the probability that one or more corn or soybean meal ocean vessels (25,000 tonnes) contaminated with ASFV would be imported into the United States annually. This final probability estimate was conditionally based on five likelihoods: the probability of initial ASFV contamination (p0), ASFV inactivation during processing (p1) and transport (p2), recontamination (pR), and ASFV inactivation while awaiting customs clearance at United States entry (p3). The probability of ASFV inactivation was modelled using corn and soybean (extruded or solvent extracted) processing conditions (times and temperatures), D-values (time to reduce 90% or 1-log) estimated from studies of ASFV thermal inactivation in pork serum (p1), and survival in feed ingredients during transoceanic transport (p2 and p3). 'What-if' scenarios using deterministic values for p0 and pR (1%, 10%, 25%, 50%, 75%, and 100%) were used to explore their impact on risk. The model estimated complete inactivation of ASFV after extrusion or solvent extraction processes regardless of the initial ASFV contamination probability assumed. The value of recontamination (ranging from 1% to 75%) was highly influential on the risk of one ASFV-contaminated soybean meal vessel entering the United States. Median risk estimates ranged from 0.064% [0.006%-0.60%; 95% probability interval (PI)], assuming a pR of 1.0%, up to 4.67% (0.45%-36.50% 95% PI) assuming a pR of 75.0%. This means that at least one vessel with ASFV-contaminated soybean meal would be imported once every 1563-21 years, respectively. When all raw corn was assumed to be contaminated (p0=100%), and no recontamination was assumed to occur (pR=0%), the median probability of one vessel with ASFV-contaminated corn entering the United States was 2.02% (0.28%-9.43% 95% PI) or once every 50 years. Values of recontamination between 1% and 75% did not substantially change the risk of corn. Days of transport, virus survival during transport (D-value), and number of vessels shipped were the parameters most influential for increased likelihood of a vessel with ASFV-contaminated soybean meal or corn entering the United States. The model helped to identify knowledge gaps that are most influential on output values and serves as a framework that could be updated and parameterized as new scientific information becomes available. We propose that the quantitative risk assessment model developed in this study can be used as a framework for estimating the risk of ASFV entry into the United States and other ASFV-free countries through other types of imported feed ingredients that may potentially become contaminated. Ultimately, this model can be used to develop risk mitigation strategies and critical control points for inactivating ASFV during feed ingredient processing, storage, and transport, and contribute to the design and implementation of biosecurity measures to prevent the introduction of ASFV into the United States and other ASFV-free countries.

A systematic review and meta-analysis of the efficacy of processing stages and interventions for controlling Campylobacter contamination during broiler chicken processing.

Systematic review and meta-analysis were conducted to quantify the effects of processing stages and interventions on the prevalence and concentration of Campylobacter on broiler carcasses. To comprehensively capture relevant evidence, six databases were searched using the keywords "Campylobacter" and "broiler chicken." The literature search yielded 10,450 unique citations, and after applying predetermined inclusion and exclusion criteria, 72 and 53 relevant citations were included in meta-analyses for processing stages and interventions, respectively. As the two primary outcomes, log reduction and prevalence changes were estimated for each stage or intervention using a random-effects meta-analysis approach whenever possible. The outcome-level quality assessment was conducted following the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The analysis revealed that scalding and chilling majorly reduces the prevalence and concentration of Campylobacter. Immersion chilling reduces the concentration regardless of chemical additives, but its effect on prevalence is not conclusive. The effects of carcass washing applications remain uncertain due to the inconsistency and imprecision of both outcomes. Defeathering and evisceration were identified as stages that can increase both prevalence and concentration. Both chemical and physical processing interventions provide limited efficacy in concentration and prevalence reduction. Major limitations of the review were inconsistency and imprecision at the outcome level and reporting issues and data gaps at the study level. The results are expected to inform quantitative microbial risk assessment model development and support evidence-based decision-making.

Quantitative microbial risk assessment associated with ready-to-eat salads following the application of farmyard manure and slurry or anaerobic digestate to arable lands

Farmyard manure and slurry (FYM&S) and anaerobic digestate are potentially valuable soil conditioners providing important nutrients for plant development and growth. However, these organic fertilisers may pose a microbial health risk to humans. A quantitative microbial risk assessment (QMRA) model was developed to investigate the potential human exposure to pathogens following the application of FYM&S and digestate to agricultural land. The farm-to-fork probabilistic model investigated the fate of microbial indicators (total coliforms and enterococci) and foodborne pathogens in the soil with potential contamination of ready-to-eat salads (RTEs) at the point of human consumption. The processes examined included pathogen inactivation during mesophilic anaerobic digestion (M-AD), post-AD pasteurisation, storage, dilution while spreading, decay in soil, post-harvest washing processes, and finally, the potential growth of the pathogen during refrigeration/storage at the retail level in the Irish context. The QMRA highlighted a very low annual probability of risk (Pannual) due to Clostridium perfringens, norovirus, and Salmonella Newport across all scenarios. Mycobacterium avium may result in a very high mean Pannual for the application of raw FYM&S, while Cryptosporidium parvum and pathogenic E. coli showed high Pannual, and Listeria monocytogenes displayed moderate Pannual for raw FYM&S application. The use of AD reduces this risk; however, pasteurisation reduces the Pannual to an even greater extent posing a very low risk. An overall sensitivity analysis revealed that mesophilic-AD's inactivation effect is the most sensitive parameter of the QMRA, followed by storage and the decay on the field (all negatively correlated to risk estimate). The information generated from this model can help to inform guidelines for policymakers on the maximum permissible indicator or pathogen contamination levels in the digestate. The QMRA can also provide the AD industry with a safety assessment of pathogenic organisms resulting from the digestion of FYM&S.

Controlling risk of SARS-CoV-2 infection in essential workers of enclosed food manufacturing facilities.

The SARS-CoV-2 global pandemic poses significant health risks to workers who are essential to maintaining the food supply chain. Using a quantitative risk assessment model, this study characterized the impact of risk reduction strategies for controlling SARS-CoV-2 transmission (droplet, aerosol, fomite-mediated) among front-line workers in a representative indoor fresh fruit and vegetable manufacturing facility. We simulated: 1) individual and cumulative SARS-CoV-2 infection risks from close contact (droplet and aerosols at 1–3 m), aerosol, and fomite-mediated exposures to a susceptible worker following exposure to an infected worker during an 8 h-shift; and 2) the relative reduction in SARS-CoV-2 infection risk attributed to infection control interventions (physical distancing, mask use, ventilation, surface disinfection, hand hygiene, vaccination). Without mitigation measures, the SARS-CoV-2 infection risk was largest for close contact (droplet and aerosol) at 1 m (0.96, 5th – 95th percentile: 0.67–1.0). In comparison, risk associated with fomite (0.26, 5th – 95th percentile: 0.10–0.56) or aerosol exposure alone (0.05, 5th – 95th percentile: 0.01–0.13) at 1 m distance was substantially lower (73–95%). At 1 m, droplet transmission predominated over aerosol and fomite-mediated transmission, however, this changed by 3 m, with aerosols comprising the majority of the exposure dose. Increasing physical distancing reduced risk by 84% (1–2 m) and 91% (1–3 m). Universal mask use reduced infection risk by 52–88%, depending on mask type. Increasing ventilation (from 0.1 to 2–8 air changes/hour) resulted in risk reductions of 14–54% (1 m) and 55–85% (2 m). Combining these strategies, together with handwashing and surface disinfection, resulted in <1% infection risk. Partial or full vaccination of the susceptible worker resulted in risk reductions of 73–92% (1 m risk range: 0.08–0.26). However, vaccination paired with other interventions (ACH 2, mask use, or distancing) was necessary to achieve infection risks <1%. Current industry SARS-CoV-2 risk reduction strategies, particularly when bundled, provide significant protection to essential food workers.

Risk to human health from protozoan (oo)cysts in water treatment plants

ABSTRACT The presence of waterborne pathogens, when associated with the water supply system, poses risks to public health. This study investigated the occurrence of (oo)cysts of Cryptosporidium spp. and Giardia spp. in two Water Treatment Plants, with full-cycle technology, and assessed the microbiological risk to consumers’ health. The membrane filtration technique was employed to identify the protozoan load in 24 samples of raw and filtered water. Physicochemical and bacteriological parameters were also analyzed. The Quantitative Microbial Risk Assessment model was used to determine the risk of daily and annual infection associated with the ingestion of filtered water. A total of 66.67% of raw water samples were positive for Cryptosporidium; and 33.33%, for Giardia. The maximum concentrations of 200 (oo)cysts/L and 50 cysts/L were detected in the Cerrado stream (located in Sanclerlândia, state of Goiás, Brazil), due to the predominance of grazing areas and intense agricultural activity. Water Treatment Plants did not completely remove the protozoa and the retention efficiency was lower than that recommended by the United States Environmental Protection Agency, with average values of 1.27 log for cysts and 1.04 log for oocysts. The probability of annual infection by cysts (100%) was higher than that of oocysts (86.61 - 98.32%) as for consumption of filtered water, and in the dry season, there was a higher risk of infection, due to the low performance of the Water Treatment Plants and higher concentration of pathogens. According to the results, the continuous intake of filtered water above the warning level can cause infectious diseases in the supplied population.

Changes in Escherichia coli to enteric protozoa ratios in rivers: Implications for risk-based assessment of drinking water treatment requirements

Minimum treatment requirements are set in response to established or anticipated levels of enteric pathogens in the source water of drinking water treatment plants (DWTPs). For surface water, contamination can be determined directly by monitoring reference pathogens or indirectly by measuring fecal indicators such as Escherichia coli (E. coli). In the latter case, a quantitative interpretation of E. coli for estimating reference pathogen concentrations could be used to define treatment requirements. This study presents the statistical analysis of paired E. coli and reference protozoa (Cryptosporidium, Giardia) data collected monthly for two years in source water from 27 DWTPs supplied by rivers in Canada. E. coli/Cryptosporidium and E. coli/Giardia ratios in source water were modeled as the ratio of two correlated lognormal variables. To evaluate the potential of E. coli for defining protozoa treatment requirements, risk-based critical mean protozoa concentrations in source water were determined with a reverse quantitative microbial risk assessment (QMRA) model. Model assumptions were selected to be consistent with the World Health Organization (WHO) Guidelines for drinking-water quality. The sensitivity of mean E. coli concentration trigger levels to identify these critical concentrations in source water was then evaluated. Results showed no proportionalities between the log of mean E. coli concentrations and the log of mean protozoa concentrations. E. coli/protozoa ratios at DWTPs supplied by small rivers in agricultural and forested areas were typically 1.0 to 2.0-log lower than at DWTPs supplied by large rivers in urban areas. The seasonal variations analysis revealed that these differences were related to low mean E. coli concentrations during winter in small rivers. To achieve the WHO target of 10−6 disability-adjusted life year (DALY) per person per year, a minimum reduction of 4.0-log of Cryptosporidium would be required for 20 DWTPs, and a minimum reduction of 4.0-log of Giardia would be needed for all DWTPs. A mean E. coli trigger level of 50 CFU 100 mL−1 would be a sensitive threshold to identify critical mean concentrations for Cryptosporidium but not for Giardia. Treatment requirements higher than 3.0-log would be needed at DWTPs with mean E. coli concentrations as low as 30 CFU 100 mL−1 for Cryptosporidium and 3 CFU 100 mL−1 for Giardia. Therefore, an E. coli trigger level would have limited value for defining health-based treatment requirements for protozoa at DWTPs supplied by small rivers in rural areas.

Quantitative microbial human exposure model for faecal indicator bacteria and risk assessment of pathogenic Escherichia coli in surface runoff following application of dairy cattle slurry and co-digestate to grassland

Animal waste contains high numbers of microorganisms and therefore can present a potential biological threat to human health. During episodic rainfall events resulting in runoff, microorganisms in the waste and soil may migrate into surface runoff, contaminating surface water resources. A probabilistic human exposure (HE) model was created to determine exposure to faecal indicator bacteria (FIB): total coliforms (TC), E. coli and enterococci following application of bio-based fertiliser (dairy cattle slurry, digestate) to grassland; using a combination of experimental field results and literature-based data. This step was followed by a quantitative microbial risk assessment (QMRA) model for pathogenic E. coli based on a literature-based dose-response model. The results showed that the maximum daily HE (HEdaily) is associated with E. coli for unprocessed slurry (treatment T1) on day 1, the worst-case scenario where the simulated mean HEdaily was calculated as 2.84 CFU day −1. The results indicate that the overall annual probability of risk (Pannual) of illness from E. coli is very low or low based on the WHO safe-limit of Pannual as 10 −6. In the worst-case scenario, a moderate risk was estimated with simulated mean Pannual as 1.0 × 10 −5. Unpasteurised digestate application showed low risk on day 1 and 2 (1.651 × 10 −6, 1.167 × 10 −6, respectively). Pasteurised digestate showed very low risk in all scenarios. These results support the restriction imposed on applying bio-based fertiliser if there is any rain forecast within 48 h from the application time. This study proposes a future extension of the probabilistic model to include time, intensity, discharge, and distance-dependant dilution factor. The information generated from this model can help policymakers ensure the safety of surface water sources through the quality monitoring of FIB levels in bio-based fertiliser.

Quantitative risk assessment of human Taenia solium exposure from consuming pork produced in Punjab, India.

Taenia solium cysticercosis is a neglected zoonosis that affects people throughout much of the developing world. The disease is endemic in Punjab state of India and controlling it is a public health challenge. No studies have been conducted to quantify the risk of T.solium exposure from consuming pork produced in the state. A stochastic quantitative risk assessment (QRA) model was constructed to understand the risk of human T.solium infection from consuming pork produced in Punjab. Input data were collected from official records, published literature, active surveillance and specifically for this study. Sensitivity analyses were conducted to assess the influence of the input parameters on the main output probability that any one pork meal is infective (contains at least one viable cyst) at consumption. The probability of any pork meal in Punjab containing at least one viable T.solium cyst post-storage and post-cooking was median 5.57×10-4 (95% PI 1.06×10-4 -1.95×10-3 ). Sobol' sensitivity analysis demonstrated that the most influential input parameters on consumption of a pork meal with at least one viable T.solium were the probability that a meal is insufficiently cooked to render cysts unviable, and the proportion of infected carcasses following informal slaughter. Whilst improved sanitation and hygiene can prevent cysticercosis in people, efforts to reduce the prevalence of T.solium cysts in pig carcases by preventing pigs' access to human waste, increasing meat inspection and promoting effective cooking practices are also important to reduce this source of taeniasis.

Domain-specific risk assessment using integrated simulation: a case study of an onshore wind project

Although many quantitative risk assessment models have been proposed in literature, their use in construction practice remain limited due to a lack of domain-specific models, tools, and application examples. This is especially true in wind farm construction, where the state-of-the-art integrated Monte Carlo simulation and critical path method (MCS–CPM) risk assessment approach has yet to be demonstrated. The present case study is the first reported application of the MCS–CPM method for risk assessment in wind farm construction and is the first case study to consider correlations between cost and schedule impacts of risk factors using copulas. MCS–CPM provided reasonable risk assessment results for a wind farm project, and its use in practice is recommended. To facilitate the practical application of quantitative risk assessment methods, this case study provides a much-needed analytical generalization of MCS–CPM, offering application examples, discussion of expected results, and recommendations to wind farm construction practitioners.

An approach of quantitative risk assessment for release of supercritical CO2 pipelines

Transportation of Carbon Dioxide (CO2) is an essential part of Carbon Capture and Storage (CCS) chain. Transportation using pipelines is known as one of the most economical ways for large-quantity of CO2. In CCS projects, it is very important to ensure the safe operation of the CO2 pipelines. Thus in the design stage, the risk associated with CO2 pipelines should be identified. This paper reports a method of Quantitative Risk Assessment (QRA) for the possible release of supercritical CO2 (scCO2) pipelines, including the individual risk and social risk. In this method, the data of failure frequency was summarized and the failure frequency suitable for CO2 pipelines was modified based on the effect of third-party activities. Furthermore, the fatal length was introduced to describe the integrated fatality along the pipeline. A two-phase model for CO2 release and a modified Gaussian plume model for CO2 dispersion were used to obtain the release consequences in CO2 pipeline QRAs for the first time. The results show that the modified failure frequencies of a full-bore rupture and a puncture are both 2.32 × 10−4 km−1 year−1. To demonstrate the method, a QRA case based on a hypothetical accident release of a scCO2 pipeline was presented. The QRA model proposed provides a potential framework to determine the safe distance of CO2 pipelines.

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.

Risk assessment of Escherichia coli in bioaerosols generated following land application of farmyard slurry

Transfer of Escherichia coli in bioaerosols to humans during and shortly after the land application of farmyard slurry may pose human health hazards, but it has not been extensively explored to date. The present study developed a quantitative risk assessment model for E. coli through the air exposure route. The probabilistic model assessed the predicted number of microorganisms in the air (PNair) to which humans may be exposed. A Gaussian air dispersion model was used to calculate the concentration of E. coli transmitted through aerosols. Human exposure (HE) to E. coli was estimated using a Monte Carlo simulation approach. This research predicted the mean HE as 26 CFU day−1 (95th percentile 263 CFU day−1) and suggests the importance of keeping a distance of at least 100 m for the residential population from land spreading activities. However, the simulated mean daily or annual (once a year application) risk of 2.65 × 10−7 person−1 year−1 due to land application of slurry indicates very low occupational risk for farmworkers not equipped with the personal protective equipment (PPE), who are potentially exposed to E. coli indirectly. The model found that the decay constant of E. coli in air, duration of decay, and bio-aerosolisation efficiency factor (top three) could influence HE to airborne E. coli. Furthermore, this research recommends an average time lag of at least 2.5 h following the application of farmyard slurry to the field before humans access the field again without PPE, allowing the airborne pathogen to decay, thereby ensuring occupational safety. The model suggested that the bio-aerosolisation efficiency factor (E) for other pathogens requires further investigation. The information generated from this model can help to assess likely exposure from bioaerosols triggered by land application of farmyard slurry.

Methodology of Urban Safety and Security Assessment Based on the Overall Risk Management Perspective

With the expansion of urbanization, the interaction between different hazards has become increasing evident. In order to promote sustainable development of urban areas, it is particularly important to systematically analyze and evaluate urban safety and security under the coupling effect of multi-hazard risks. In response to the practical needs of urban safety and security assessment practice, this paper constructs an application-oriented urban safety and security quantitative assessment methodology. First, following the comprehensive risk management perspective, the logical relationship between urban safety and security elements is analyzed. It proposes “comprehensive screening, key analysis, and comprehensive evaluation” as a new assessment concept. Second, a system of urban safety and security assessment methods consisting of a weighting method and a function model is constructed. The function model includes two sub-models: a quantitative risk assessment model that considers triggering effects and a quantitative assessment model of emergency capacity that considers the evolution of emergencies. Finally, the method was applied to a coastal urban area in south China. The case study proved that the proposed method system can not only effectively evaluate various disaster risks and emergency capacity but also provide evidence for the formulation and implementation of urban safety and security management measures.

A quantitative risk assessment to evaluate the efficacy of mitigation strategies to reduce highly pathogenic avian influenza virus, subtype H5N1 (HPAI H5N1) in the Menoufia governorate, Egypt

BackgroundThe poultry industry in Egypt has been suffering from endemic highly pathogenic avian influenza (HPAI) virus, subtype H5N1 since 2006. However, the emergence of H9N2, H5N8, and H5N2 in 2011, 2016, and 2019 respectively, has aggravated the situation. Our objective was to evaluate how effective are the mitigation strategies by a Quantitative Risk Assessment (QRA) model which used daily outbreak data of HPAI-H5N1 subtype in Egypt, stratified by different successive epidemic waves from 2006 to 2016.ResultsBy applying the epidemiologic problem-oriented approach methodology, a conceptual scenario tree was drawn based on the knowledgebase. Monte Carlo simulations of QRA parameters based on outbreak data were performed using @Risk software based on a scenario-driven decision tree. In poultry farms, the expected probability of HPAI H5N1 prevalence is 48% due to failure of mitigation strategies in 90% of the time during Monte Carlo simulations. Failure of efficacy of these mitigations will raise prevalence to 70% with missed vaccination, while failure in detection by surveillance activities will raise it to 99%. In backyard poultry farms, the likelihood of still having a high HPAI-H5N1 prevalence in different poultry types due to failure of passive and active surveillance varies between domestic, mixed and reservoir. In mixed poultry, the probability of HPAI-H5N1 not detected by surveillance was the highest with a mean and a SD of 16.8 × 10–3 and 3.26 × 10–01 respectively. The sensitivity analysis ranking for the likelihood of HPAI-H5N1 in poultry farms due to missed vaccination, failure to be detected by passive and active surveillance was examined. Among poultry farms, increasing vaccination by 1 SD will decrease the prevalence by 14%, while active and passive surveillance decreases prevalence by 12, and 6%, respectively. In backyard, the active surveillance had high impact in decreasing the prevalence by 16% in domestic chicken. Whereas the passive surveillance had less impact in decreasing prevalence by 14% in mixed poultry and 3% in domestic chicken.ConclusionIt could be concluded that the applied strategies were not effective in controlling the spread of the HPAI-H5N1 virus. Public health officials should take into consideration the evaluation of their control strategies in their response.

Using surrogate data to assess risks associated with microbial peak events in source water at drinking water treatment plants

A monitoring strategy was implemented at two drinking water treatment plants in Quebec, Canada, to evaluate microbial reduction performances of full-scale treatment processes under different source water conditions. β-D-glucuronidase activity in source water was automatically monitored in near-real-time to establish baseline and event conditions at each location. High-volume water samples (50–1,500 L) were collected at the inflow and the outflow of coagulation/flocculation, filtration, and UV disinfection processes and were analysed for two naturally occurring surrogate organisms: Escherichia coli and Clostridium perfringens. Source water Cryptosporidium data and full-scale C. perfringens reduction data were entered into a quantitative microbial risk assessment (QMRA) model to estimate daily infection risks associated with exposures to Cryptosporidium via consumption of treated drinking water. Daily mean E. coli and Cryptosporidium concentrations in source water under event conditions were in the top 5% (agricultural site) or in the top 15% (urban site) of what occurs through the year at these drinking water treatment plants. Reduction performances of up to 6.0-log for E. coli and 5.6-log for C. perfringens were measured by concentrating high-volume water samples throughout the treatment train. For both drinking water treatment plants, removal performances by coagulation/flocculation/sedimentation processes were at the high end of the range of those reported in the literature for bacteria and bacterial spores. Reductions of E. coli and C. perfringens by floc blanket clarification, ballasted clarification and rapid sand filtration did not deteriorate during two snowmelt/rainfall events. QMRA results suggested that daily infection risks were similar during two rainfall/snowmelt events than during baseline conditions. Additional studies investigating full-scale reductions would be desirable to improve the evaluation of differences in treatment performances under various source water conditions.

Corrosion risk assessment using adaptive bow-tie (ABT) analysis

Corrosion is a major threat to safety and asset integrity in oil and gas production and processing facilities. This paper proposes a simple, yet practical model for quantitative corrosion risk assessment from safety and economic perspectives. This includes an Adaptive Bow-Tie (ABT) model for the corrosion risk with a specific focus on microbiologically influenced corrosion, along with corrosion economic risk profile. The ABT model is logically tested using corrosion science and statistically verified using a pipeline corrosion database, including cases of corrosion-induced failures. The ABT model also provides opportunities to run root-cause contribution (RCC) analysis and to estimate the probability of corrosion, corrosion-induced failures, and highly probable sequences leading to failure. The model application is demonstrated using a crude oil transportation pipeline system. The study identifies and quantifies parameters that helps to prioritize the actions needed to prevent and control corrosion and avoid failures. The proposed model can serve as an important mechanism to identify, assess, and manage corrosion threat to an asset.

RISK ANALYSIS OF MAJOR ENGINEERING GEOLOGICAL HAZARDS FOR SICHUAN-TIBET RAILWAY IN THE PHASE OF FEASIBILITY STUDY

The Sichuan-Tibet Railway is the most challenging railway project ever in the world. The project region is characterized by various adverse geological conditions including active tectonic movement, intensive mega faults, abrupt topographic relief and frequent geological disasters. Therefore, the construction of this project is challenged by complex geological disaster risks from both ground surface and underground. This study comprehensively and quantitatively analyzes the ground surface and underground geological risks along the Sichuan-Tibet Railway, and further evaluates their consequential influences on the project so as to support its feasibility study. The risk analysis utilizes abundant spatial-temporal data, and various approaches including three-dimensional structure modeling, numerical modeling, statistical modeling, dynamic modeling, time series modeling and spatial distribution modeling. The results show that there are three areas concentrated with high ground surface geological hazards risk along the Sichuan-Tibet railway, namely the Xianshuihe fault zone, the Jinshajiang fault zone and the eastern Himalayan syntaxis area. However, ground surface engineering risks of this project are significantly reduced, because its underground tunnels are over 80% of the total railway line length. The universal quantitative risk assessment models are developed for major underground engineering geological risks, including fault activities, rock bursts and large deformations. For several major tunnels such as the Yigong tunnel, risks of typical individual underground geological hazards(e.g. rock burst and large deformation) as well as the integrated risk, are quantitatively evaluated. The results show that both surface and subsurface engineering risks are significant and can threaten the safety of project. This study provides a scientific and technical support for the feasibility study of the Sichuan-Tibet Railway, and is also expected to be a reference for major engineering geological risk control for similar line engineering projects around the world.

Quantitative risk assessment of Listeria monocytogenes in ready-to-eat (RTE) cooked meat products sliced at retail stores in Greece

A quantitative microbial risk assessment (QMRA) model predicting the listeriosis risk related to the consumption of Ready- To- Eat (RTE) cooked meat products sliced at retail stores in Greece was developed. The probability of illness per serving assessed for 87 products available in the Greek market was found highly related to the nitrite concentration; products having a lower concentration showed a higher risk per serving. The predicted 95th percentiles of the annual listeriosis cases totaled 33 of which 13 cases were <65 years old and 20 cases ≥65 years old. The highest number of cases was predicted for mortadella, smoked turkey, boiled turkey and parizer, which were the most frequently consumed product categories. Two scenarios for assessing potential interventions to reduce the risk were tested: setting a use-by date of 14 days (these products have no use-by date based on current European Union legislation) and improving the temperature control during domestic storage. The two scenarios resulted in a decrease of the 95th and 99th percentiles of the total annual cases by 97% and 88%, respectively.

Using Economic Optimization to Derive Site-Specific Treatment Objectives

A procedure to estimate the economically efficient site- or system-specific treatment objective for enteric viruses in drinking water is presented. The health benefits of treatment are estimated using an existing quantitative microbiological risk assessment model for Rotavirus, which yields a reduction in burden of disease, measured in DALYs. The community’s willingness to pay for this reduced disease burden is then inferred using an estimate of the value of an avoided DALY from the literature. Economically efficient treatment occurs where the marginal cost of additional treatment equals the marginal benefit in terms of willingness to pay for avoided illness. In a case study on a small water system, capital and operating costs are estimated for four alternative treatment levels using commercially available UV disinfection systems. The case study results compare the economically efficient virus disinfection level, risk of infection, and burden of disease to international guidelines. A sensitivity analysis suggests that source water quality, population served, and the dose–response model are key inputs. Site-specific treatment objectives offer a viable alternative to prescribed national standards while respecting water safety and local autonomy.