An educationally inspired illustration of two-dimensional Quantitative Microbiological Risk Assessment (QMRA) and sensitivity analysis

A secondary model for the effect of pH on the variability in growth fitness of Listeria innocua strains

Variability in microbial growth is a keystone of modern Quantitative Microbiological Risk Assessment (QMRA). However, there are still significant knowledge gaps on how to model variability, with the most common assumption being that variability is constant. This is implemented by an error term (with constant variance) added on top of the secondary growth model (for the square root of the growth rate). However, this may go against microbial ecology principles, where differences in growth fitness among bacterial strains would be more prominent in the vicinity of the growth limits than at optimal growth conditions. This study coins the term "secondary models for variability", evaluating whether they should be considered in QMRA instead of the constant strain variability hypothesis. For this, 21 strains of Listeria innocua were used as case study, estimating their growth rate by the two-fold dilution method at pH between 5 and 10. Estimates of between-strain variability and experimental uncertainty were obtained for each pH using mixed-effects models, showing the lowest variability at optimal growth conditions, increasing towards the growth limits. Nonetheless, the experimental uncertainty also increased towards the extremes, evidencing the need to analyze both sources of variance independently. A secondary model was thus proposed, relating strain variability and pH conditions. Although the modelling approach certainly has some limitations that would need further experimental validation, it is an important step towards improving the description of variability in QMRA, being the first model of this type in the field.

Seasonal assessment of risks to canoeists' health in a Taiwanese recreational river

Canoeing is the most favorite recreational activity in several Taiwanese rivers. However, river water frequently contains elevated levels of pathogenic Escherichia coli, which has adverse effects on human health. This study adopted a quantitative microbial risk assessment to analyze seasonal risks to canoeists' health in the Dongshan River, Taiwan. First, river E. coli concentrations were statistically analyzed to determine the seasonal distributions. The exposure duration (ED) was determined by field observations. To propagate the parametric uncertainty, Monte Carlo simulation was employed to model the probability distributions of seasonal pathogenic E. coli levels, ingestion rates, and ED for athletes. Finally, the beta-Poisson dose-response model was implemented to determine seasonal health risks for canoeists. The study results indicated that the health risks in infection probability ranged from 0.5 × 10-3 to 8.8 × 10-3 illnesses/person/day for tourists and 1.2 × 10-3 to 7.7 × 10-3 illnesses/person/day for athletes. The health risks in the Lizejian Bridge area for tourists exceeded an acceptable level suggested by the U.S. Environmental Protection Agency, 8 × 10-3 illnesses/person/day, in spring for an ED of 2 h/day, and the health risks for tourists and athletes approached this level in spring and winter for an ED exceeding or equaling 1.5 h/day. According to sensitivity analysis, the geometric standard deviation of river E. coli levels was the most sensitive parameter affecting seasonal risks to canoeists' health. To protect canoeists' health, effluent sewer systems, best management practices, and total maximum daily loads should be promptly implemented in this watershed.

Shelf life estimation of refrigerated vacuum packed beef accounting for uncertainty

This study estimates the shelf life of vacuum packed beef meat (three muscles: striploin (longissimus thoracis et lumborum, LTL), tenderloin (psoas major, PM) and outside chuck (trapezius thoracis, TT)) at refrigeration temperatures (0 °C-10 °C) based on modelling the growth of two relevant groups of spoilage microorganisms: lactic acid bacteria (LAB) and Enterobacteriaceae. The growth models were developed combining a two-step and a one-step approach. The primary modelling was used to identify the parameters affecting the growth kinetics, guiding the definition of secondary growth models. For LAB, the secondary model included the effect of temperature and initial pH on the specific growth rate. On the other hand, the model for Enterobacteriaceae incorporated the effect of temperature on the specific growth rate and the lag phase; as well as the effect of the initial pH on the specific growth rate, the lag phase and the initial microbial count. We did not observe any significant effect of the type of muscle on the growth kinetics. Once the equations were defined, the models were fitted to the complete dataset using a one-step approach. Model validation was carried out by cross-validation, mitigating the impact of an arbitrary division between training and validation sets. The models were used to estimate the shelf life of the product, based on the maximum admissible microbial concentration (7 log CFU/g for LAB, 5 log CFU/g for Enterobacteriaceae). Although LAB was the dominant microbiota, in several cases, both LAB and Enterobacteriaceae reached the critical concentration practically at the same time. Furthermore, in some scenarios, the end of shelf life would be determined by Enterobacteriaceae, pointing at the potential importance of non-dominant microorganisms for product spoilage. These results can aid in the implementation of effective control measures in the meat processing industry.

Aquatic Ecosystem Risk Assessment Generated by Accidental Silver Nanoparticle Spills in Groundwater

This paper aims to create a new model for assessing the ecosystem risk in rivers and wetlands that are linked to accidental spills of silver nanoparticles (AgNPs) in soil/groundwater. Due to the uncertainty of the modeling inputs, a combination of two well-known risk assessment methodologies (Monte Carlo and fuzzy logic) were used. To test the new model, two hypothetical, accidental AgNP soil spill case studies were evaluated; both of which were located at the end of the Llobregat River basin within the metropolitan area of Barcelona (NE Spain). In both cases, the soil spill reached groundwater. In the first case, it was discharged into a river, and in the second case, it recharged a wetland. Concerning the results, in the first case study, a medium-risk assessment was achieved for most cases (83%), with just 10% of them falling below the future legal threshold concentration value. In the second case study, a high-risk assessment was obtained for most cases (84%), and none of the cases complied with the threshold value. A sensitivity analysis was conducted for the concentration and risk. The developed tool was proven capable of assessing risk in aquatic ecosystems when dealing with uncertain and variable data, which is an improvement compared to other risk assessment methodologies.

Development of a Modeling Tool To Assess and Reduce Regulatory and Recall Risks for Cold-Smoked Salmon Due to Listeria monocytogenes Contamination

ABSTRACT

Although public health risk assessments for Listeria monocytogenes (Lm) have been published for various foods, firm-level decision making on interventions targeting Lm involves considerations of both public health and enterprise risks. Smoked seafood is a ready-to-eat product with a high incidence of Lm contamination and has been associated with several recalls. We used cold-smoked salmon as a model product to develop a decision support tool (the regulatory and recall risk [3R] model) to estimate (i) baseline regulatory and recall (RR) risks (i.e., overall risks of a lot sampled and found positive for Lm, e.g., by food regulatory agencies) due to Lm contamination and (ii) the RR risk reduction that can be achieved through interventions with underlying mechanisms such as reducing the prevalence and/or level of Lm and retarding or preventing Lm growth. Given that a set number of samples (e.g., 10) are tested for a given lot, the RR risk equals the likelihood of detecting Lm in at least one sample. Under the baseline scenario, which assumes a 4% Lm prevalence and no interventions, the median predicted RR risk for a given production lot was 0.333 (95% credible interval: 0.288, 0.384) when 10 25-g samples were tested. Nisin treatments, which reduce both the prevalence and initial level of Lm, reduced RR risks in a concentration-dependent manner to 0.109 (0.074, 0.146) with 5 ppm, 0.049 (0.024, 0.083) with 10 ppm, and 0.017 (0.007, 0.033) with 20 ppm. In general, more effective reduction in RR risks can be achieved by reducing Lm prevalence than by retarding Lm growth; the RR risk was reduced to 0.182 (0.153, 0.213) by a 50% prevalence reduction but to only 0.313 (0.268, 0.367) by bacteriostatic growth inhibitors. Sensitivity analysis indicated that prevalence and initial level of Lm and storage temperature have the greatest impact on predicting RR risks, suggesting that reliable data for these parameters will improve model performance.

HIGHLIGHTS

Quantitative microbial risk assessment and sensitivity analysis for workers exposed to pathogenic bacterial bioaerosols under various aeration modes in two wastewater treatment plants

Wastewater treatment plants (WWTPs) could emit a large amount of bioaerosols containing pathogenic bacteria. Assessing the health risks of exposure to these bioaerosols by using quantitative microbial risk assessment (QMRA) is important to protect workers in WWTPs. However, the relative impacts of the stochastic input variables on the health risks determined in QMRA remain vague. Hence, this study performed a Monte Carlo simulation-based QMRA case study for workers exposing to S. aureus or E. coli bioaerosols and a sensitivity analysis in two WWTPs with various aeration modes. Results showed that when workers equipped without personal protective equipment (PPE) were exposed to S. aureus or E. coli bioaerosol in the two WWTPs, the annual probability of infection considerably exceeded the U.S. EPA benchmark (≤10E-4 pppy), and the disease burden did not satisfy the WHO benchmark (≤10E-6 DALYs pppy) (except exposure to E. coli bioaerosol for disease health risk burden). Nevertheless, the use of PPE effectively reduced the annual infection health risk to an acceptable level and converted the disease health risk burden to a highly acceptable level. Referring to the sensitivity analysis, the contribution of mechanical aeration modes to the variability of the health risks was absolutely dominated in the WWTPs. On the aeration mode that showed high exposure concentration, the three input exposure parameters (exposure time, aerosol ingestion rate, and breathing rate) had a great impact on health risks. The health risks were also prone to being highly influenced by the various choices of the dose-response model and related parameters. Current research systematically delivered new data and a novel perspective on the sensitivity analysis of QMRA. Then, management decisions could be executed by authorities on the basis of the results of this sensitivity analysis to reduce related occupational health risks of workers in WWTPs.

Listeria monocytogenes contamination of ready-to-eat foods and the risk for human health in the EU

Food safety criteria for Listeria monocytogenes in ready-to-eat (RTE) foods have been applied from 2006 onwards (Commission Regulation (EC) 2073/2005). Still, human invasive listeriosis was reported to increase over the period 2009-2013 in the European Union and European Economic Area (EU/EEA). Time series analysis for the 2008-2015 period in the EU/EEA indicated an increasing trend of the monthly notified incidence rate of confirmed human invasive listeriosis of the over 75 age groups and female age group between 25 and 44 years old (probably related to pregnancies). A conceptual model was used to identify factors in the food chain as potential drivers for L. monocytogenes contamination of RTE foods and listeriosis. Factors were related to the host (i. population size of the elderly and/or susceptible people; ii. underlying condition rate), the food (iii. L. monocytogenes prevalence in RTE food at retail; iv. L. monocytogenes concentration in RTE food at retail; v. storage conditions after retail; vi. consumption), the national surveillance systems (vii. improved surveillance), and/or the bacterium (viii. virulence). Factors considered likely to be responsible for the increasing trend in cases are the increased population size of the elderly and susceptible population except for the 25-44 female age group. For the increased incidence rates and cases, the likely factor is the increased proportion of susceptible persons in the age groups over 45 years old for both genders. Quantitative modelling suggests that more than 90% of invasive listeriosis is caused by ingestion of RTE food containing > 2,000 colony forming units (CFU)/g, and that one-third of cases are due to growth in the consumer phase. Awareness should be increased among stakeholders, especially in relation to susceptible risk groups. Innovative methodologies including whole genome sequencing (WGS) for strain identification and monitoring of trends are recommended.