Microbial Risk Analysis最新文献

{"title":"Quantifying microbial risk from drinking water production process under changing climate and socio-economic conditions","authors":"M․M․ Majedul Islam","doi":"10.1016/j.mran.2024.100321","DOIUrl":"10.1016/j.mran.2024.100321","url":null,"abstract":"<div><p>Consumption of drinking water containing pathogenic microorganisms may pose serious health risks from waterborne diseases. Quantifying such risks is essential for guiding interventions and policy decisions. Quantitative microbial risk assessment (QMRA) is a very useful method to estimate the public's risk of infection from disease-causing microorganisms in water sources. QMRA of drinking water production process is limited worldwide and so far no such QMRA study has been conducted in Bangladesh. Moreover, climate and socio-economic changes may impact waterborne pathogens and associated health risks, but to what extent remains unclear, because comprehensive QMRA by taking into account combined impact of climatic and socio-economic factors has never been done worldwide so far. In this study, the Swedish QMRA tool was applied to evaluate public health risk from drinking water production process in Dhaka, Bangladesh as a case study. At first, current risk was quantified, and then the potential future risk was projected by taking into account climate and socio-economic factors. The results revealed that the annual infection risks at the current (2020s) baseline condition were below the acceptable risk threshold 10^–4 infections per person per year (as proposed by several USEPA scientists) for all three pathogens <em>Salmonella,</em> norovirus and <em>Giardia</em>. However, after extreme events with sewer overflow and agricultural runoff, norovirus violates the acceptable risk thresholds, and the risks for <em>Salmonella</em> and <em>Giardia</em> are in borderline. The selected sustainable future scenario showed some improvement in terms of annual infection risks, while the uncontrolled scenario resulted in substantially higher infection risks both in the near and far future compared to the current scenarios. installment of a UV treatment step as an additional treatment barrier resulted in significant infection risk reduction. According to the sensitivity analysis results, socio-economic factors such as human population, livestock, and pathogen removal in wastewater were found to have greater influence on the infection risks, compared to climate change. The study can help policy makers and water managers to identify interventions to reduce the burden of disease on the population. The tool can be used to assess the health risk associated with drinking water production process in other areas of the world with similar characteristics.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100321"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing urban street food safety among youth: The impact of road dust on potential microbial contamination risks to student health","authors":"Thanh Tran ,&nbsp;Van Huu Dat ,&nbsp;Vu Nhat Phuong ,&nbsp;Tran Hoang Cam Tu ,&nbsp;Do Vinh Duong ,&nbsp;Ho Huu Loc","doi":"10.1016/j.mran.2024.100327","DOIUrl":"10.1016/j.mran.2024.100327","url":null,"abstract":"<div><div>This study investigates the potential impact of air pollution on street food safety within educational environments, highlighting how airborne pollutants contribute to the microbial contamination of food, beverages, and environmental dust. A mixed-method approach was employed, combining microbial analyses with a survey of 200 students using the Theory of Planned Behavior (TPB) to assess attitudes, social pressures, and control over food safety practices. The findings reveal significant contamination levels: dust samples showed Coliform and E. coli concentrations of 3 × 10³ CFU/g and 2 × 10³ CFU/g, respectively, while food samples exhibited even higher microbial loads, with Coliform levels reaching 6.4 × 10⁶ CFU/g and E. coli up to 1 × 10⁴ CFU/g. SPSS 20 analysis reflects substantial concerns among students regarding the safety of street foods, emphasizing the need for increased public awareness. By establishing a clear link between air pollution and the microbial risks associated with street food, the study advocates for enhanced consumer education and regulatory measures to mitigate health risks and protect public health.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100327"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Growth limits of psychrotrophic Bacillus cereus as a function of temperature, pH, water activity, and lactic or acetic acid","authors":"Yvan Le Marc,&nbsp;Emilie Petton,&nbsp;Anne Lochardet,&nbsp;Florence Postollec,&nbsp;Véronique Huchet","doi":"10.1016/j.mran.2024.100310","DOIUrl":"https://doi.org/10.1016/j.mran.2024.100310","url":null,"abstract":"<div><p>This work focuses on the effects of temperature, pH, water activity, and concentrations of acetic or lactic acid on the growth limits of psychrotrophic <em>Bacillus cereus sensu lato</em> (<em>s.l.</em>). A previously published growth boundary model, based on an ‘interaction term’, was extended by the integration of new environmental factors. Further development has been made by replacing, wherever possible, the single values for strain-dependent parameters by statistical distributions, making it possible to describe the intra-group variability in <em>B. cereus s.l.</em> behaviour. The parameters associated with organic acid (i.e., the Minimum Inhibitory Concentrations, MIC) were determined for one strain for lactic acid and three strains for acetic acid. The MICs estimated were close to previously published values for mesophilic reference group III strain F4810/72. The growth/ no growth interface for psychrotrophic <em>B. cereus s.l.</em> in absence of organic acid was defined by the lower growth limits obtained separately for “groups II and V” and “group VI”. The model predictions for the transition between the “no-growth only” and “possible growth” provide fail-safe predictions for ComBase and literature data (468 records). To investigate behaviour of psychrotrophic <em>B. cereus s.l.</em> under organic acid, growth/ no growth data were generated at 15 °C (simulating mild temperature abuse) for three <em>B. cereus s.l.</em> strains (one from group II and two from group VI) at different pH levels (between 4.8 and 6.2), water activities (between 0.974 and 0.997) and concentrations of acetic acid (up to 45 mM) or lactic acid (up to 100 mM). Each of the three strains was studied separately for a total of 312 experiments. The minimum pH levels required for growth increase in the presence of lactic or acetic acid, highlighting their inhibitory effects. These inhibitory effects are enhanced at the lowest water activity tested. Although, group VI strains were reported to be more affected by low a_w, only small differences were observed between group II and group VI at a_w 0.974. The developed model was found to provide conservative (i.e. fail-safe) predictions for the growth limits under acetic or lactic acid at 15 °C.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100310"},"PeriodicalIF":2.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141240377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Food Safety Knowledge Exchange (FSKX) format: Current status and strategic development plans based on a SWOT analysis","authors":"Matthias Filter,&nbsp;Thomas Schüler,&nbsp;Racem Ben Romdhane","doi":"10.1016/j.mran.2024.100309","DOIUrl":"https://doi.org/10.1016/j.mran.2024.100309","url":null,"abstract":"<div><p>The Food Safety Knowledge Exchange (FSKX) format is a community-driven effort initially created to promote the efficient exchange of data and models in the food safety domain. Over the past years this effort was driven by the Risk Assessment Knowledge Integration Platform (RAKIP) Initiative that also provided a number of software tools and FSKX-compliant model files via their website <span>https://foodrisklabs.bfr.bund.de/rakip-initiative/</span><svg><path></path></svg>.</p><p>This paper describes the results of a SWOT analysis that was conducted to identify strategic avenues for enhancing FSKX's usability and adoption. The SWOT analysis identified a number of recommendations for the future evolution of FSKX. First, it is recommended to reduce the complexity of the annotation schema to ease the adoption of the format. Second, a clear distinction between the descriptive part of FSKX and the executable part is proposed. To promote the broad usage of FSKX-compliant models, it is also recommended to develop and provide FSKX-compliant APIs and resources that facilitate cloud-based execution.</p><p>As part of the research to prioritize future FSKX development options, we also considered the implications of the emerging generative AI technologies, particularly which impact large language models (LLMs) might have in supporting the adoption of FSKX by the research community. Recognizing the format's application potential beyond the food safety domain, we then proposed to re-brand the FSKX acronym as \"FAIR Scientific Knowledge Exchange Format\" which better reflects its broad applicability in various scientific domains. Our research findings suggest that with the implementation of the improvements identified by the SWOT analysis and the broader availability of generative AI technologies the broad adoption of FSKX as a method to share data and models in a FAIR way comes into reach.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100309"},"PeriodicalIF":2.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352352224000203/pdfft?md5=e10ede05b06179fd0fb3cf8fff5bd9b6&pid=1-s2.0-S2352352224000203-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141240378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microbiological risk assessment of Bacillus cereus in popular hot dishes eaten by plant-based diet consumers in France","authors":"Pauline Mombert ,&nbsp;Eléonore Blondet ,&nbsp;Jeanne-Marie Membré ,&nbsp;Louis Delaunay","doi":"10.1016/j.mran.2024.100320","DOIUrl":"10.1016/j.mran.2024.100320","url":null,"abstract":"<div><p>There is a current trend towards plant-based diets in Western countries. Since changes in the diet imply possible changes in exposure to foodborne pathogens, there is an increasing need to assess the microbiological risks associated with these diets. This study aims to assess microbiological risks for French adults associated with <em>Bacillus cereus</em> group III and group IV in hot, homemade cereal- and lentil-based dishes. A probabilistic retail-to-fork risk assessment model was developed considering cooking, cooling at ambient temperature, and storage under chilled conditions. Data came from a representative national survey, public database and literature. The model was developed in R, and uncertainty and variability were separated using second-order Monte Carlo simulations. Not all consumers have the same storage and cooling practices, so the results were expressed by probabilistic distributions built by specific storage time. The mean concentration of <em>Bacillus cereus</em> in portions at the time of consumption after 72 h of storage was 1.2 log CFU.<em>g</em>⁻¹ for cereal-based dishes and 3.4 log CFU.<em>g</em>⁻¹ for lentil-based dishes. After 72 h of storage under chilled conditions, the risk per portion, defined as the probability of contamination over 5 log CFU.<em>g</em>⁻¹, was 0 (95 % CI: 0 - 0) for cereal-based dishes and 7.95 × 10⁻⁴ (95 % CI: 5.55 × 10⁻⁴ - 1.12 × 10⁻³) for lentils-based dishes. However, if cooling time at room temperature reached 24 h, the risk for cereal- and lentil-based dishes increased to 2.39 × 10⁻³ (95 % CI: 1.15 × 10⁻³ - 4.90 × 10⁻³) and 4.66 × 10⁻¹ (95 % CI: 3.16 × 10⁻¹ - 6.07 × 10⁻¹), respectively. The sensitivity analysis indicated that the initial prevalence and level of contamination were key factors in limiting the risk, ranking before cooling time or refrigeration conditions. Besides, the scenario analysis revealed an influence of consumer behaviour regarding cooling and storage time on the risk per portion. The environmental trend towards plant-forward diets, combined with the emerging no-food waste and batch cooking practices in France, will likely favour new consumption patterns and increase the risk associated with <em>Bacillus cereus</em>. Our model will help quantify this extra burden.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100320"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The risk of acquiring avian influenza from commercial poultry products and hen eggs: A qualitative assessment","authors":"Erica Kintz ,&nbsp;Wioleta J. Trzaska ,&nbsp;Elaine Pegg ,&nbsp;Wendy Perry ,&nbsp;Alexander W. Tucker ,&nbsp;Alec Kyriakides ,&nbsp;Dragan Antic ,&nbsp;Kathryn Callaghan ,&nbsp;Anthony J. Wilson","doi":"10.1016/j.mran.2024.100317","DOIUrl":"https://doi.org/10.1016/j.mran.2024.100317","url":null,"abstract":"<div><p>High pathogenicity and low pathogenicity avian influenza (HPAI and LPAI) viruses primarily infect birds, but they can also cause illness in other species, including humans. Some avian influenza (AI) strains can cause fatality rates of over 50 % in human infections. In October 2021, there was a substantial increase in the number of AI infections reported in birds in the UK. Given concerns that more infected and/or contaminated poultry products might reach retail, a risk assessment was performed to ensure that advice relating to the handling and consumption of these products remained appropriate.</p><p>The products considered in this risk assessment were commercial chicken and turkey products, farmed duck and geese products, and table eggs. The risk pathway included the likelihood animals or eggs from an infected flock would be sent for further processing, whether the resulting products would be released to retail after inspection, viral persistence during distribution and storage, and the ability of AI viruses to infect humans via the gastrointestinal route. The risk from any AI virus, not just the A(H5N1) strain that began circulating in 2021, was considered. Data was obtained from literature searches and FSA surveys.</p><p>The risk assessment determined that the likelihood of human infection with AI from poultry products for the UK population from handling and consuming commercial chicken or turkey products was <strong>negligible</strong> with <strong>low uncertainty</strong>, and for farmed duck and geese products was <strong>very low</strong> with <strong>medium uncertainty</strong>. The likelihood of infection for people in the UK from handling and consuming hen table eggs was <strong>very low</strong> with <strong>low uncertainty.</strong> The uncertainty rankings relate to the differing amounts of data available for each group of poultry products. The severity of illness in humans from AI infection was considered <strong>high</strong> with <strong>medium</strong> uncertainty. The conclusions of this risk assessment for UK consumers largely reflected advice and assessments from other countries and previous UK assessments. Given this, current guidance for handling and consuming poultry products was considered appropriate despite the increase in infections in birds during the 2021/22 and 2022/23 avian flu seasons. Since AI viruses were considered generally, these risk characterisations may need to be revisited based on evidence specific to a circulating virus to support risk management decisions.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100317"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352352224000288/pdfft?md5=e66300a2f4f81a610c671edae54faa13&pid=1-s2.0-S2352352224000288-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141605462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harmonizing Campylobacter risk assessments across European countries – can the pooled process hygiene criteria data be used in the Danish risk assessment model?","authors":"Francis Lauriau ,&nbsp;Maarten Nauta ,&nbsp;Nabila Haddad ,&nbsp;Sofia Strubbia ,&nbsp;Jean-Michel Cappelier ,&nbsp;Marianne Sandberg ,&nbsp;Sandrine Guillou ,&nbsp;Alessandro Foddai","doi":"10.1016/j.mran.2024.100325","DOIUrl":"10.1016/j.mran.2024.100325","url":null,"abstract":"<div><div>This study investigated the possibility of harmonizing quantitative microbiological risk assessment (QMRA) for <em>Campylobacter</em> spp. across European (EU) countries. French <em>Campylobacter</em> data (2020–2021) from neck skin (NS) pools, sampled at slaughterhouses under the European surveillance component for Food Business Operators (FBOs), were adapted to inform a QMRA model that, among others, has been used within the Danish Action Plan against <em>Campylobacter</em>, on the basis of single leg skins (LS) data. Datasets included culture results (in colony forming unit per gram, CFU/g) from 1,284 broiler flocks slaughtered at 13 slaughterhouses representing broiler production in western France. Five pools (of 2–4 NS samples each) per flock were tested. One pool per tested flock was randomly chosen for the analysis. After conducting descriptive statistics (on flock prevalence and meat contaminations across months and years), three contamination transformation factors (CTFs) were estimated to translate NS pools contaminations into single LS contamination, based on data from French and Danish studies. A reference simulation scenario (ScenRef) was set with CTF = 3.2 (i.e. NS pool concentration divided by 3.2); while other 13 scenarios represented an alternative scenario analysis to investigate the impact of: the CTF value (ScenMin with CTF = 2 and ScenMax with CTF = 10), censored test results (ScenUncens) and random choice of pool per flock (ScenSampling-1 to 10), on the risk estimates. The average monthly/annual risk of human disease per poultry meal and the monthly/annual relative risk (RR) of 2021 compared to 2020, were estimated. In ScenRef, the annual RR was 1.22, suggesting an increase of risk of ≈ 22 % in 2021 compared to 2020. The impact of CTFs, censored data and randomized pool sampling per flock, on the annual and (most) monthly RRs, appeared limited. This study gives an overview of the strengths and limitations to be considered for adapting the French FBO data into the Danish model and to harmonize risk assessments across EU countries, accordingly. To reduce uncertainty in risk estimates, it could be considered increasing representativeness of NS tested flock populations and/or using LS rather than NS samples; because LS samples are more representative of actually retailed meat contaminations. If NS pools are maintained, the relationships between concentrations on NS pools and those on consumed meat requires further investigation.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100325"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Spatial risk assessment of ovine Scrapie in Brazil” [Microbial Risk Analysis 25 (2023) 100282]","authors":"Paulo Gomes do Nascimento Corrêa ,&nbsp;Francisco Alyson Silva Oliveira ,&nbsp;Rivanni Jeniffer Souza Castro ,&nbsp;Carlos Thiago Silveira Alvim Mendes de Oliveira ,&nbsp;Glenda Lídice de Oliveira Cortez Marinho ,&nbsp;Abelardo Silva Júnior ,&nbsp;Ricardo Antonio Pilegi Sfaciotte ,&nbsp;David Germano Gonçalves Schwarz","doi":"10.1016/j.mran.2024.100311","DOIUrl":"10.1016/j.mran.2024.100311","url":null,"abstract":"","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100311"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141255738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New Zealand microbiological risk ranking of imported fruits and vegetables","authors":"Anne-Marie Perchec-Merien,&nbsp;Christine Marie Esguerra","doi":"10.1016/j.mran.2024.100319","DOIUrl":"10.1016/j.mran.2024.100319","url":null,"abstract":"<div><p>This article presents the outcomes of a scientific review and microbiological risk ranking of fresh, frozen, processed, and preserved fruit and vegetables imported into New Zealand. The study was undertaken by New Zealand Food Safety to help in the prioritisation of imported food safety issues for risk management action and ensure that regulatory resources are appropriately focused on food products that represent the highest public health risk.</p><p>Risk ranking, also sometimes called comparative risk assessment, is a methodology where the most significant risks associated with specific hazards and foods are identified and characterised, and then compared. The output is a list of pathogen-food combinations ranked according to their relative level of risks, from highest to lowest.</p><p>This study involved the development of a New Zealand risk ranking model based on two multicriteria analysis models developed separately by the United States Food and Drug Administration and the European Food Safety Authority (BIOHAZ Panel) for similar risk ranking applications. The New Zealand model uses nine criteria that have been adapted to New Zealand data and circumstances.</p><p>The eight top ranking pathogen-produce combinations identified using the New Zealand model were pathogenic <em>E. coli</em> in lettuce, spinach and other leafy greens, <em>Salmonella</em> spp. in lettuce, other leafy greens, tomatoes, melons, and other Cucurbitaceae (e.g. cucumbers, gourds, squashes, pumpkins). Produce categories were also ranked based on overall risk from various pathogens associated with each produce category. The top ranked produce categories, in decreasing order of rank, were: other leafy greens, pods, legumes and grains, tropical fruits, berries, herbs and spinach.</p><p>The risk ranking lists provide a starting point and basis for risk management considerations and prioritisation of resources. They will need to be regularly updated to ensure they remain relevant by incorporating the latest epidemiological, hazard, and import volume data. Updates should also consider the availability of new modelling tools and analytical methods for emerging or less common pathogens.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100319"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141845804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multipathogen quantitative risk assessment in raw milk soft cheese","authors":"Subhasish Basak ,&nbsp;Laurent Guillier ,&nbsp;Julien Bect ,&nbsp;Janushan Christy ,&nbsp;Fanny Tenenhaus-Aziza ,&nbsp;Emmanuel Vazquez","doi":"10.1016/j.mran.2024.100318","DOIUrl":"10.1016/j.mran.2024.100318","url":null,"abstract":"<div><p>We propose a multipathogen Quantitative Microbiological Risk Assessment (QMRA) model to estimate the risk of foodborne illness from bacterial pathogens in raw milk soft cheese. Our work extends an existing QMRA model for pathogenic Shiga toxin-producing <em>Escherichia coli</em> (STEC) (Basak et al.,under review; Perrin et al., 2014) by incorporating the effects of <em>Salmonella</em> and <em>Listeria monocytogenes</em>. This multipathogen model integrates microbial contamination of raw milk at the farm level, as well as the growth and survival of these bacteria during cheese fabrication, ripening, and storage. The public health impact of multipathogen risk associated with raw milk cheese consumption is assessed using Disability-Adjusted Life Years (DALYs). The model evaluates intervention strategies at both pre- and post-harvest stages to estimate intervention costs. Furthermore, it tests various scenarios of these strategies and optimizes intervention parameters to minimize multipathogen risk and associated costs. This article discusses challenges in QMRA model validation, emphasizes model limitations, and explores future perspectives for improvement.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100318"},"PeriodicalIF":3.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S235235222400029X/pdfft?md5=a261136a0233c04d44f8138c9312abc5&pid=1-s2.0-S235235222400029X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141691011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}