Quantitative Microbial Risk Assessment Model Research Articles

Approach to a water safety plan for recreational waters: disinfection of a drainage pumping station as an unconventional point source of fecal contamination

Abstract In the context of the management of bathing water quality, the intermittent contamination of rainwater drainage pumps (unconventional point sources) could be controlled by peracetic acid disinfection. Thus, a field experimental study was carried out to set up a water safety plan, determining the monitoring parameters and the critical limit for corrective actions. With a 0.5 mg/l dosage, the average logarithmic microbial reduction was 0.50 ± 0.48 for Escherichia coli (EC) and 0.43 ± 0.54 for intestinal enterococci. Among the chemical and physical parameters that could be monitored in real time, the oxidation–reduction potential was the only one able to predict the microbial concentration discharged from a drainage pump and the logarithmic abatement of EC. Considering the possible impact of this source on bathing waters in terms of additional risk of gastrointestinal infections, the critical limit for continuous monitoring was established using a quantitative microbial risk assessment (QMRA) model.

An Advanced Risk Modeling Method to Estimate Legionellosis Risks Within a Diverse Population

Quantitative microbial risk assessment (QMRA) is a computational science leveraged to optimize infectious disease controls at both population and individual levels. Often, diverse populations will have different health risks based on a population’s susceptibility or outcome severity due to heterogeneity within the host. Unfortunately, due to a host homogeneity assumption in the microbial dose-response models’ derivation, the current QMRA method of modeling exposure volume heterogeneity is not an accurate method for pathogens such as Legionella pneumophila. Therefore, a new method to model within-group heterogeneity is needed. The method developed in this research uses USA national incidence rates from the Centers for Disease Control and Prevention (CDC) to calculate proxies for the morbidity ratio that are descriptive of the within-group variability. From these proxies, an example QMRA model is developed to demonstrate their use. This method makes the QMRA results more representative of clinical outcomes and increases population-specific precision. Further, the risks estimated demonstrate a significant difference between demographic groups known to have heterogeneous health outcomes after infection. The method both improves fidelity to the real health impacts resulting from L. pneumophila infection and allows for the estimation of severe disability-adjusted life years (DALYs) for Legionnaires’ disease, moderate DALYs for Pontiac fever, and post-acute DALYs for sequela after recovering from Legionnaires’ disease.

An Assessment of Listeriosis Risk Associated with a Contaminated Production Lot of Frozen Vegetables Consumed Under Alternative Consumer Handling Scenarios

Frozen foods do not support the growth of Listeria monocytogenes (LM) and should be handled appropriately for safety. However, consumer trends regarding preparation of some frozen foods may contribute to the risk of foodborne listeriosis, specifically when cooking instructions are not followed and frozen products are instead added directly to smoothies or salads. A quantitative microbial risk assessment model FFLLoRA (Frozen Food Listeria Lot Risk Assessment) was developed to assess the lot-level listeriosis risk due to LM contamination in frozen vegetables consumed as a ready-to-eat food. The model was designed to estimate listeriosis risk per serving and the number of illnesses per production lot of frozen vegetables contaminated with LM, considering individual facility factors such as lot size, prevalence of LM contamination, and consumer handling prior to consumption. A production lot of 1 million packages with 10 servings each was assumed. When at least half of the servings were cooked prior to consumption, the median risk of invasive listeriosis per serving in both the general and susceptible population was <1.0 × 10-16 with the median (5th, 95th percentiles) predicted number of illnesses per lot as 0 (0, 0) and 0 (0, 1) under the exponential and Weibull-gamma dose-response functions, respectively. In scenarios in which all servings are consumed as ready-to-eat, the median predicted risk per serving was 1.8 × 10-13 and 7.8 × 10-12 in the general and susceptible populations, respectively. The median (5th, 95th percentile) number of illnesses was 0 (0, 0) and 0 (0, 6) for the exponential and Weibull-Gamma models, respectively. Classification tree analysis highlighted initial concentration of LM in the lot, temperature at which the product is thawed, and whether a serving is cooked as main predictors for illness from a lot. Overall, the FFLLoRA provides frozen food manufacturers with a tool to assess LM contamination and consumer behavior when managing rare and/or minimal contamination events in frozen foods.

Roles of Vegetable Surface Properties and Sanitizer Type on Annual Disease Burden of Rotavirus Illness by Consumption of Rotavirus-Contaminated Fresh Vegetables: A Quantitative Microbial Risk Assessment.

Enteric viruses are often detected in water used for crop irrigation. One concern is foodborne viral disease via the consumption of fresh produce irrigated with virus-contaminated water. Although the food industry routinely uses chemical sanitizers to disinfect post-harvest fresh produce, it remains unknown how sanitizer and fresh produce properties affect the risk of viral illness through fresh produce consumption. A quantitative microbial risk assessment model was conducted to estimate (i) the health risks associated with consumption of rotavirus (RV)-contaminated fresh produce with different surface properties (endive and kale) and (ii) how risks changed when using peracetic acid (PAA) or a surfactant-based sanitizer. The modeling results showed that the annual disease burden depended on the combination of sanitizer and vegetable type when vegetables were irrigated with RV-contaminated water. Global sensitivity analyses revealed that the most influential factors in the disease burden were RV concentration in irrigation water and postharvest disinfection efficacy. A postharvest disinfection efficacy of higher than 99% (2-log10 ) was needed to decrease the disease burden below the World Health Organization (WHO) threshold, even in scenarios with low RV concentrations in irrigation water (i.e., river water). All scenarios tested here with at least 99.9% (3-log10 ) disinfection efficacy had a disease burden lower than the WHO threshold, except for the endive treated with PAA. The disinfection efficacy for the endive treated with PAA was only about 80%, leading to a disease burden 100 times higher than the WHO threshold. These findings should be considered and incorporated into future models for estimating foodborne viral illness risks.

Quantitative risk assessment of meat-borne Toxoplasma gondii infection in the mainland of China

Toxoplasma gondii, a protozoan zoonotic parasite, has a worldwide distribution. It can cause severe pathological damage to the fetus in primary infected pregnant women and life-threatening encephalitis in immunocompromised patients. One of the main transmission routes to humans is consumption of raw or undercooked meat containing viable T. gondii tissue cysts. In China, the lack of quantitative information on the risk and incidence of infection due to consumption of meat hampers the development of prevention strategies to reduce the burden of toxoplasmosis. The aim of this study was to set up a quantitative microbial risk assessment (QMRA) model to estimate the relative attribution of different types of meat (i.e., pork, beef, lamb and mutton, chicken and duck) to human T. gondii infections in China. The model was built based on the structure of the first meat-borne T. gondii infection QMRA model developed in the Netherlands and applied for seven regions of mainland China. Data on the prevalence of T. gondii in livestock and consumption were obtained from China, however information on preparation habits was lacking. Consumption data were available as average consumption amounts per day collected over three days. The results calculated from the QMRA model were at least thousand-fold higher compared to the incidence rate obtained from an epidemiological susceptible-infected (SI) type model. In general, pork and chicken meat contributed more to the estimated number of infections than beef, small ruminant and duck meat. Cooking temperature was identified as one of the parameters that most strongly affected the estimated incidence rate in the QMRA model. Sensitivity analysis showed that the estimated incidence rate from the QMRA model would be comparable to the results obtained from the SI model if final cooking temperatures are around 1.7 times higher than the temperatures based on a dataset for American consumers. Scenario analysis demonstrated that it is important to know portion size and frequency of consumption in addition to total consumed amounts to calculate incidence of infection. Due to uncertainties present in the input data and the at least thousand-fold overestimated incidence rates, the results merely give an indication of the relative importance of different types of meat. However, the QMRA model clearly identified the key knowledge gaps for future research and can subsequently support cost-effective decisions to reduce the disease burden of human toxoplasmosis.

A within-flock model of Salmonella Heidelberg transmission in broiler chickens

As part of the development of a quantitative microbial risk assessment (QMRA) model of third-generation cephalosporins (3GC)-resistant Salmonella Heidelberg, a compartmental (SEIR) model for S. Heidelberg transmission within a typical Canadian commercial broiler chicken flock was developed. The model was constructed to estimate the within-flock prevalence and the bacterial concentration in the barn environment at pre-harvest, and to assess the effect of selected control measures.The baseline scenario predicted an average within-flock prevalence of 23.5 % (95 % tolerance interval: 15.7–31.4) and an average bacterial concentration of 3.579 (0–4.294) log CFU/g of feces in the barn environment at pre-harvest (on the day the flock is sent to slaughter). Because vertical introduction of S. Heidelberg into the barn was already uncommon in the baseline scenario, vaccination of broiler parent flocks appeared to have a negligible effect, while vaccination of broiler chicken flocks substantially reduced the bacterial concentration at pre-harvest. Cleaning and disinfection between batches markedly reduced the within-flock prevalence at pre-harvest, but the effect on bacterial concentration was limited outside of the beginning of the production period. Extending downtime between batches by 7 days had little effect on within-flock prevalence or bacterial concentration of S. Heidelberg when compared to the baseline scenario.This study provides a basis to describe S. Heidelberg dynamics within a broiler chicken flock and to predict the within-flock prevalence and bacterial concentration at pre-harvest, and includes a description of the limitations and data gaps. The results of these analyses and associated uncertainties are critical information for populating QMRA models of the downstream impacts on public health from on-farm and other food-chain practices. Specifically, the study findings will be integrated into a broader farm-to-fork QMRA model to support the risk-based control of S. Heidelberg resistant to 3GC in broiler chicken in Canada.

Linking Decision Theory and Quantitative Microbial Risk Assessment: Tradeoffs Between Compliance and Efficacy for Waterborne Disease Interventions.

Achieving health gains from the U.N. Sustainable Development Goals of universal coverage for water and sanitation will require interventions that can be widely adopted and maintained. Effectiveness-how an intervention performs based on actual use-as opposed to efficacy will therefore be central to evaluations of new and existing interventions. Incomplete compliance-when people do not always use the intervention and are therefore exposed to contamination-is thought to be responsible for the lower-than-expected risk reductions observed from water, sanitation, and hygiene interventions based on their efficacy at removing pathogens. We explicitly incorporated decision theory into a quantitative microbial risk assessment model. Specifically, we assume that the usability of household water treatment (HWT) devices (filters and chlorine) decreases as they become more efficacious due to issues such as taste or flow rates. Simulations were run to examine the tradeoff between device efficacy and usability. For most situations, HWT interventions that trade lower efficacy (i.e., remove less pathogens) for higher compliance (i.e., better usability) contribute substantial reductions in diarrheal disease risk compared to devices meeting current World Health Organization efficacy guidelines. Recommendations that take into account both the behavioral and microbiological properties of treatment devices are likely to be more effective at reducing the burden of diarrheal disease than current standards that only consider efficacy.

Legionella pneumophila as a Health Hazard to Miners: A Pilot Study of Water Quality and QMRA.

Legionella pneumophila (L. pneumophila), the causative agent of legionellosis, is an aquatic bacterium that grows in warm water. Humans are only presented with a health risk when aerosolized water containing L. pneumophila is inhaled. In mining operations, aerosolized water is used as dust control and as part of the drilling operations, a currently ignored exposure route. This study characterized L. pneumophila concentrations in the mine’s non-potable water and the relationship between L. pneumophila and chlorine concentrations. These concentrations informed a quantitative microbial risk assessment (QMRA) model to estimate the infection risk to miners exposed to aerosolized water containing L. pneumophila. Fourteen water samples were collected from seven locations at a mine and analyzed for temperature, pH, chlorine, and L. pneumophila serogroup. Most samples (93%) tested positive for L. pneumophila cells. The faucet from the sprinkler system on the adit level (entrance to the underground mine levels) showed the highest concentration of L. pneumophila (8.35 × 104 MPN/L). Disability adjusted life years (DALYs) were estimated in the QMRA model and showed that the risk for all miners was significantly lower (p < 0.0001) with the ventilation system on than when the system was off. Our study showed that the use of a ventilation system at the adit level of the mine reduced the risk of infection with aerosolized L. pneumophila.

Assessing microbial risk through event-based pathogen loading and hydrodynamic modelling

The aim of this study was to assess the variability of microbial risk associated with drinking water under various contaminant loading conditions in a drinking water source. For this purpose, a probabilistic-deterministic approach was applied to estimate the loadings of Cryptosporidium, Giardia, and Escherichia coli (E. coli) from fecal contamination sources during both dry and wet weather conditions. The relative importance of loads originating from various fecal contamination sources was also determined by a probabilistic approach. This study demonstrates that water resource recovery facilities were the dominant source of Giardia, yet rivers were more important with regards to Cryptosporidium. Estimated loadings were used as input to a three-dimensional hydrodynamic model of Lake Ontario; the fate and transport of microbial organisms were simulated at the influent of a drinking water intake. Discharge-based hydrodynamic modelling results were compared to observed concentrations. Simulated probability distributions of concentrations at the intake were used as an input to a quantitative microbial risk assessment (QMRA) model such that the variability of microbial risk in the context of drinking water could be examined. Depending on wind and currents, higher levels of fecal contamination reached the intake during wet weather loading scenarios. Probability distribution functions of Cryptosporidium, Giardia and E. coli concentrations at the intake were significantly higher during wet weather conditions when compared to dry conditions (p < 0.05). For all contaminants studied, the QMRA model showed a higher risk during wet weather (over 1 order of magnitude) compared to dry weather conditions. When considering sewage by-pass scenarios, risks remained below 2.7 × 10−7 person−1 day−1 for Giardia and E. coli O157:H7. Limited data were available for Cryptosporidium in by-pass effluents and the risk is unknown; hence it is critical to obtain reliable loading data for the riskiest scenarios, such as those associated with water resource recovery facility by-passes.

Evaluation of the physical and chemical characteristics of water on the removal efficiency of rotavirus in drinking water treatment plants and change in induced health risk

Rotavirus is one of the main waterborne causes of diarrhoea. Rotavirus type A is responsible for diarrhoea in infants and causes thousands of deaths annually around the world, especially in developing countries. Rotavirus is very small and is highly resistant to common disinfectants, so the World Health Organization (WHO) has chosen this virus as a reference pathogen in drinking water and has recommended a its 6-log removal by the conventional water treatment process to supply safe drinking water. We measured some physical and chemical characteristics of raw water at a water treatment plant in Tehran, Iran, including temperature, pH, total organic compound (TOC) concentration and initial turbidity, to determine their effect on rotavirus removal efficiency in various processes. We then measured rotavirus removal efficiency in clarified water and filtrate to determine their removal efficiency. Finally, we applied the WHO guideline and an empirical quantitative microbial risk assessment (QMRA) model to estimate probable health risk based on a residual number of rotavirus in finished water. We found that TOC concentration and water temperature are both effective on residual rotavirus in clarified water but they have no significant effect on the efficacy of filtration in rotavirus removal. Maximum rotavirus removal efficiency by clarification and filtration was 97.2% and 4.5% in April and January respectively. TOC and water temperature were shown to have a significant effect on clarification virus efficiency, so filtration performance was independent of these variables. The results showed that induced risk by residual rotavirus is in an acceptable range (99.99945% removal annually), and also showed that the critical process in virus removal is clarification that can be affected by raw water quality.

Probabilistic model for the estimation of the consumer exposure to methicillin-resistant Staphylococcus aureus due to cross-contamination and recontamination.

The presence of multidrug‐resistant bacteria like methicillin‐resistant Staphylococcus aureus (MRSA) in retail meat is one of the current concerns of the public health authorities. Bacterial cross‐contamination and recontamination during household food preparation could play an important role in the dissemination of such bacteria, and therefore could contribute to a serious health problem, more specifically for immunocompromised people. In order to evaluate the importance of such events, a probabilistic model was developed to estimate the likelihood and extent of cross‐contamination and recontamination and the burden of MRSA from contaminated raw chicken meat via hands and kitchen utensils in a serving (consisting on a slice of bread and a piece of grilled chicken meat) during a household barbecue in Germany. A modular design was used, taking into account the chronological order of the routines during the barbecue event, and Monte Carlo simulations were applied. Available data on the prevalence and burden of MRSA in chicken meat at retail in Germany were used as starting point and were incorporated in the model as probability distributions. The probabilities and extent of bacterial transfer between food items and kitchen utensils (referred to as “Objects”) and the routines performed during food preparation (referred to as “Actions”) specified by their probabilities of occurrence were incorporated as the main input parameters. The model was set up in R 3.5.0 and converted to a standardized format (FSKX file). Therefore, the code can be easily accessed, evaluated, modified, and reused for different purposes. The present study contributes to the quantification of consumer exposure to MRSA through food consumption once contaminated food has entered the household kitchen. Even when the MRSA prevalence and bacterial load in retail chicken meat in Germany are low, resistant bacteria can reach the consumer due to cross‐contamination and recontamination events. The results show that the probability of one CFU to be transferred from the contaminated raw chicken meat to the final serving and the number of MRSA bacteria transferred due to cross‐contamination and recontamination events are in general low, being the contamination of the final serving more likely to occur via bread, rather than via grilled chicken. The results show that the prevalence of MRSA at retail highly influences the probability of the final serving to be contaminated. However, this study also highlights the importance of keeping good hygiene practices during the household food manipulation for reducing the spread of MRSA. The provision of the model in a standardized data format will allow an easy incorporation of the developed model into a complete quantitative microbial risk assessment model that will greatly help to estimate the risk of consumer exposure to MRSA through the consumption of contaminated food.

A review on microbial contaminants in stormwater runoff and outfalls: Potential health risks and mitigation strategies.

Demands on global water supplies are increasing in response to the need to provide more food, water, and energy for a rapidly growing population. These water stressors are exacerbated by climate change, as well as the growth and urbanisation of industry and commerce. Consequently, urban water authorities around the globe are exploring alternative water sources to meet ever-increasing demands. These alternative sources are primarily treated sewage, stormwater, and groundwater. Stormwater including roof-harvested rainwater has been considered as an alternative water source for both potable and non-potable uses. One of the most significant issues concerning alternative water reuse is the public health risk associated with chemical and microbial contaminants. Several studies to date have quantified fecal indicators and pathogens in stormwater. Microbial source tracking (MST) approaches have also been used to determine the sources of fecal contamination in stormwater and receiving waters. This review paper summarizes occurrence and concentrations of fecal indicators, pathogens, and MST marker genes in urban stormwater. A section of the review highlights the removal of fecal indicators and pathogens through water sensitive urban design (WSUD) or Best Management Practices (BMPs). We also discuss approaches for assessing and mitigating health risks associated with stormwater, including a summary of existing quantitative microbial risk assessment (QMRA) models for potable and non-potable reuse of stormwater. Finally, the most critical research gaps are identified for formulating risk management strategies.

Using Nodal Infection Risks to Guide Interventions Following Accidental Intrusion due to Sustained Low Pressure Events in a Drinking Water Distribution System

Improving the risk models to include the possible infection risk linked to pathogen intrusion into distribution systems during pressure-deficient conditions (PDCs) is essential. The objective of the present study was to assess the public health impact of accidental intrusion through leakage points in a full-scale water distribution system by coupling a quantitative microbial risk assessment (QMRA) model with water quality calculations based on pressure-driven hydraulic analysis. The impacts on the infection risk of different concentrations of Cryptosporidium in raw sewage (minimum, geometric mean, mean, and maximum) and various durations of intrusion/PDCs (24 h, 10 h, and 1 h) were investigated. For each scenario, 200 runs of Monte Carlo simulations were carried out to assess the uncertainty associated with the consumers’ behavioral variability. By increasing the concentrations of Cryptosporidium in raw sewage from 1 to 560 oocysts/L for a 24-h intrusion, or by increasing the duration of intrusion from 1 to 24 h, with a constant concentration (560 oocysts/L), the simulated number of infected people was increased by 235-fold and 17-fold, respectively. On the first day of the 1-h PDCs/intrusion scenario, a 65% decrease in the number of infected people was observed when supposing no drinking water withdrawals during low-pressure conditions at nodes with low demand available (&lt;5%) compared to no demand. Besides assessing the event risk for an intrusion scenario, defined as four days of observation, the daily number of infected people and nodal risk were also modeled on different days, including during and after intrusion days. The results indicate that, for the case of a 1-h intrusion, delaying the start of the necessary preventive/corrective actions for 5 h after the beginning of the intrusion may result in the infection of up to 71 people.

Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges.

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of ‘omics’ techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR.

Interventions Targeting Deep Tissue Lymph Nodes May Not Effectively Reduce the Risk of Salmonellosis from Ground Pork Consumption: A Quantitative Microbial Risk Assessment.

The inclusion of deep tissue lymph nodes (DTLNs) or nonvisceral lymph nodes contaminated with Salmonella in wholesale fresh ground pork (WFGP) production may pose risks to public health. To assess the relative contribution of DTLNs to human salmonellosis occurrence associated with ground pork consumption and to investigate potential critical control points in the slaughter-to-table continuum for the control of human salmonellosis in the United States, a quantitative microbial risk assessment (QMRA) model was established. The model predicted an average of 45 cases of salmonellosis (95% CI = [19, 71]) per 100,000 Americans annually due to WFGP consumption. Sensitivity analysis of all stochastic input variables showed that cooking temperature was the most influential parameter for reducing salmonellosis cases associated with WFGP meals, followed by storage temperature and Salmonella concentration on contaminated carcass surface before fabrication. The input variables were grouped to represent three main factors along the slaughter-to-table chain influencing Salmonella doses ingested via WFGP meals: DTLN-related factors, factors at processing other than DTLNs, and consumer-related factors. The evaluation of the impact of each group of factors by second-order Monte Carlo simulation showed that DTLN-related factors had the lowest impact on the risk estimate among the three groups of factors. These findings indicate that interventions to reduce Salmonella contamination in DTLNs or to remove DTLNs from WFGP products may be less critical for reducing human infections attributable to ground pork than improving consumers' cooking habits or interventions of carcass decontamination at processing.

Confirming the need for virus disinfection in municipal subsurface drinking water supplies

Enteric viruses pose the greatest acute human health risks associated with subsurface drinking water supplies, yet quantitative risk assessment tools have rarely been used to develop health-based targets for virus treatment in drinking water sourced from these supplies. Such efforts have previously been hampered by a lack of consensus concerning a suitable viral reference pathogen and dose-response model as well as difficulties in quantifying pathogenic viruses in water. A reverse quantitative microbial risk assessment (QMRA) framework and quantitative polymerase chain reaction data for norovirus genogroup I in subsurface drinking water supplies were used herein to evaluate treatment needs for such water supplies. Norovirus was not detected in over 90% of samples, which emphasizes the need to consider the spatially and/or temporally intermittent patterns of enteric pathogen contamination in subsurface water supplies. Collectively, this analysis reinforces existing recommendations that a minimum 4-log treatment goal is needed for enteric viruses in groundwater in absence of well-specific monitoring information. This result is sensitive to the virus dose-response model used as there is approximately a 3-log discrepancy among virus dose-response models in the existing literature. This emphasizes the need to address the uncertainties and lack of consensus related to various QMRA modelling approaches and the analytical limitations that preclude more accurate description of virus risks.

A quantitative risk assessment for human Taenia solium exposure from home slaughtered pigs in European countries

BackgroundTaenia solium, a zoonotic tapeworm, is responsible for about a third of all preventable epilepsy human cases in endemic regions. In Europe, adequate biosecurity of pig housing and meat inspection practices have decreased the incidence of T. solium taeniosis and cysticercosis. Pigs slaughtered at home may have been raised in suboptimal biosecurity conditions and slaughtered without meat inspection. As a result, consumption of undercooked pork from home slaughtered pigs could pose a risk for exposure to T. solium. The aim of this study was to quantify the risk of human T. solium exposure from meat of home slaughtered pigs, in comparison to controlled slaughtered pigs, in European countries. A quantitative microbial risk assessment model (QMRA) was developed and porcine cysticercosis prevalence data, the percentage of home slaughtered pigs, meat inspection sensitivity, the cyst distribution in pork and pork consumption in five European countries, Bulgaria, Germany, Poland, Romania and Spain, were included as variables in the model. This was combined with literature about cooking habits to estimate the number of infected pork portions eaten per year in a country.ResultsThe results of the model showed a 13.83 times higher prevalence of contaminated pork portions from home slaughtered pigs than controlled slaughtered pigs. This difference is brought about by the higher prevalence of cysticercosis in pigs that are home raised and slaughtered. Meat inspection did not affect the higher exposure from pork that is home slaughtered. Cooking meat effectively lowered the risk of exposure to T. solium-infected pork.ConclusionsThis QMRA showed that there is still a risk of obtaining an infection with T. solium due to consumption of pork, especially when pigs are reared and slaughtered at home, using data of five European countries that reported porcine cysticercosis cases. We propose systematic reporting of cysticercosis cases in slaughterhouses, and in addition molecularly confirming suspected cases to gain more insight into the presence of T. solium in pigs and the risk for humans in Europe. When more data become available, this QMRA model could be used to evaluate human exposure to T. solium in Europe and beyond.

Impact of a hygiene intervention on virus spread in an office building.

Viral illnesses have a significant direct and indirect impact on the workplace that burdens employers with increased healthcare costs, low productivity, and absenteeism. Workers' direct contact with each other and contaminated surfaces contributes to the spread of viruses at work. This study quantifies the impact of an office wellness intervention (OWI) to reduce viral load in the workplace. The OWI includes the use of a spray disinfectant on high-touch surfaces and providing workers with alcohol-based hand sanitizer gel and hand sanitizing wipes along with user instructions. Viral transmission was monitored by applying an MS2 phage tracer to a door handle and the hand of a single volunteer participant. At the same time, a placebo inoculum was applied to the hands of four additional volunteers. The purpose was to evaluate the concentration of viruses on workers' hands and office surfaces before and after the OWI. Results showed that the OWI significantly reduced viable phage concentrations per surface area on participants' hands, shared fomites, and personal fomites (p = 0.0001) with an 85.4% average reduction. Reduction of virus concentrations on hands and fomites is expected to subsequently minimize the risk of infections from common enteric and respiratory pathogens. The surfaces identified as most contaminated were the refrigerator, drawer handles and sink faucets in the break room, along with pushbar on the main exit of the building, and the soap dispensers in the women's restroom. A comparison of contamination in different locations within the office showed that the break room and women's restrooms were the sites with the highest tracer counts. Results of this study can be used to inform quantitative microbial risk assessment (QMRA) models aimed at defining the relationship between surface contamination, pathogen exposure and the probability of disease that contributes to high healthcare costs, absenteeism, presenteeism, and loss of productivity in the workplace.

A quantitative microbial risk assessment model of Campylobacter in broiler chickens: Evaluating processing interventions

A probabilistic, evidence-based, quantitative microbial risk assessment model was developed to investigate public health risks associated with Campylobacter spp. contamination in broiler chicken supply systems in the United States, covering a farm-to-fork continuum. The objective of this study was to evaluate the effectiveness of intervention strategies in processing plants to protect the safety of chicken consumption and associated consumer health. A baseline model was constructed based on most common industrial practices with minimal interventions for model development and validation purposes. Sensitivity analysis was conducted to determine the most important input parameters for the model and identify critical control points along the supply chain. The effectiveness of possible intervention measures applicable during processing, including alternative processing strategies, chemical processing aids and physical methods to reduce risks of Campylobacter contamination in broiler chicken and campylobacteriosis among consumers were compared using scenario analysis. Input parameter distributions for the model were populated by the results of a previous systematic review and meta-analysis study, rather than evidence collected from the literature by convenience, to reduce possible bias in risk estimations. The final risk estimate was expressed as the number of campylobacteriosis cases per 100,000 persons per year and the intervention effectiveness was expressed as the relative change in campylobacteriosis risk if an intervention had been implemented compared with the baseline. The model estimated an occurrence of 274 (95% CI: 0–561) cases per 100,000 persons per year for baseline. Consumers' food safety practices and operations at processing plants are among the most significant factors to be targeted for reduction in consumers’ exposure to Campylobacter through broiler consumption. Scenario analysis results indicate that chemical processing aids (individually or in tandem) can offer significant reduction in risk estimates. The model is expected to provide a framework for risk managers making risk-based decisions on changes in current poultry processing practices or implementation of alternative intervention strategies.

Climate-driven QMRA model for selected water supply systems in Norway accounting for raw water sources and treatment processes

Formulating effective management intervention measures for water supply systems requires investigation of potential long-term impacts. This study applies an integrated multiple regression, random forest regression, and quantitative microbial risk assessment (QMRA) modelling approach to assess the effect of climate-driven precipitation on pathogen infection risks in three drinking water treatment plants (WTPs) in Norway. Pathogen removal efficacies of treatment steps were calculated using process models. The results indicate that while the WTPs investigated generally meet the current water safety guidelines, risks of Norovirus and Cryptosporidium infection may be of concern in the future. The pathogen infections attributable to current projections of average precipitation in the study locations may be low. However, the pathogen increases in the drinking water sources due to the occurrence of extreme precipitation events in the catchments could substantially increase the risks of pathogen infections. In addition, without optimal operation of the UV disinfection steps in the WTPs, both the present and potential future infection risks could be high. Therefore, the QMRA models demonstrated the need for improved optimization of key treatment steps in the WTPs, as well as implementation of stringent regulations in protecting raw water sources in the country. The variety of models applied and the pathogen: E. coli used in the study introduce some uncertainties in the results, thus, management decisions that will be based on the results should consider these limitations. Nevertheless, the integration of predictive models with QMRA as applied in this study could be a useful method for climate impact assessment in the water supply industry.