Microbial Risk Analysis最新文献

{"title":"Genomic, pangenomic, metagenomic and trancriptomics perspectives to enhance microbial modeling and quantitative risk assessment in food environments","authors":"Wilson José Fernandes Lemos Junior ,&nbsp;Larissa P Margalho ,&nbsp;Claudio Cipolat-Gotet ,&nbsp;Anderson S. Sant'Ana","doi":"10.1016/j.mran.2026.100364","DOIUrl":"10.1016/j.mran.2026.100364","url":null,"abstract":"<div><div>Recent advances in genomics, pangenomics, transcriptomics, and metatranscriptomics have expanded the resolution with which microbial traits relevant to food safety can be described. These approaches complement classical predictive models, which traditionally rely on population-averaged parameters and may overlook the heterogeneity that exists among strains and microbial communities. Omics data help identify genetic, functional, and regulatory features that underpin differences in stress tolerance, growth potential, and virulence, offering a more precise basis for hazard identification and exposure assessment. Genomic and pangenomic analyses clarify how core and accessory gene pools shape strain-level behavior, while transcriptomic studies reveal active pathways during acid, cold, or osmotic challenges. Metatranscriptomics extends this insight to complex communities, capturing how dominant and satellite members contribute to ecosystem function under food-relevant conditions. Incorporating these datasets into predictive microbiology and quantitative microbial risk assessment (QMRA) supports more realistic estimates of growth, survival, and persistence, reducing uncertainty in hazard characterization. Evidence shows that many food-associated strains are hypovirulent or slow-growing, indicating that risk may be overestimated when genetic heterogeneity is not considered. Although molecular data do not directly prescribe mitigation strategies, they support risk management by identifying which subpopulations merit targeted interventions, clarifying which process parameters influence persistence, and refining prioritization decisions. Our work discusses how omics tools align with primary, secondary, and tertiary predictive models and examines the complementarity between traditional decision-making frameworks and AI-based methods. Emphasis is also placed on sustainability, as omics-informed modeling enables more efficient in silico assessments and reduces dependence on resource-intensive challenge testing. Together, these developments strengthen the connection between risk assessment and risk management, supporting more proportionate and informed food safety decisions.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100364"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037796","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":"Public awareness and risk-related practices regarding Hydatid Disease in Türkiye: a cross-sectional survey","authors":"Sehriban Yurekturk ,&nbsp;Canan Demir ,&nbsp;Abdurrahman Ekici","doi":"10.1016/j.mran.2026.100369","DOIUrl":"10.1016/j.mran.2026.100369","url":null,"abstract":"<div><h3>Introduction</h3><div>This study aimed to evaluate public awareness, knowledge, and risk-related practices regarding hydatid disease among adults in Türkiye.</div></div><div><h3>Method</h3><div>This cross-sectional survey included 1135 individuals aged ≥18 years residing in Türkiye. This internet-based cross-sectional study was conducted between February and May 2025. Data were collected using an online questionnaire distributed via social media platforms. Knowledge levels, sources of information, and risk-related practices were assessed. Associations between sociodemographic variables and knowledge levels were analyzed using appropriate statistical tests.</div></div><div><h3>Results</h3><div>Among the participants, 56.1% were unaware of the etiological agent of hydatid disease, and only 33.7% correctly identified parasites as the cause. Knowledge regarding transmission routes was limited, with only 24.2% recognizing the role of infected dogs. Risk-related practices were common; 42.7% reported home slaughtering, while 22.5% disposed of infected organs in household waste and 32.4% buried them. Significant associations were observed between occupational groups and knowledge levels concerning disease etiology and transmission, with students demonstrating higher awareness compared to other occupational groups (<em>p</em> = 0.001).</div></div><div><h3>Conclusion</h3><div>This study reveals that the level of knowledge and awareness regarding hydatid cyst disease in Turkish society is insufficient and that high-risk practices are widespread. These findings indicate the existence of a significant public health problem that hinders the control and prevention of the disease..</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100369"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188400","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":"Monthly incidence prediction of foodborne diseases: case study in Nanning City of China","authors":"Peng Li ,&nbsp;Liting Cen ,&nbsp;Siyan Li ,&nbsp;Jing Zhang ,&nbsp;Qi Li ,&nbsp;Xiangzhi Li ,&nbsp;Hui Li","doi":"10.1016/j.mran.2026.100368","DOIUrl":"10.1016/j.mran.2026.100368","url":null,"abstract":"<div><h3>Objective</h3><div>To construct an Autoregressive Integrated Moving Average (ARIMA) multiplicative seasonal model for predicting the monthly incidence of foodborne diseases in Nanning City and provide a scientific basis for disease prevention and control strategies.</div></div><div><h3>Methods</h3><div>Monthly incidence data of foodborne diseases in Nanning City from January 2013 to December 2022 were used to develop an ARIMA multiplicative seasonal model with SPSS 23.0 software. The optimal model was selected through sequence stationarization, model identification, order determination, parameter estimation, and diagnostic checking. The model was validated using data from January to December 2023 (held-out set) and then used to forecast the monthly incidence for 2024–2025.</div></div><div><h3>Results</h3><div>The monthly incidence exhibited significant seasonal fluctuations. The optimal model was identified as ARIMA(1,0,0) × (0,1,1)₁₂, The optimal model was selected based on a combination of a high stationary R² (0.673), adherence to the principle of parsimony, and achieving the lowest Bayesian Information Criterion (BIC = 0.178) among candidate models. The model residuals passed the white noise test (Ljung-Box <em>Q</em> = 22.079, <em>P</em> = 0.141). The model’s out-of-sample performance on the 2023 validation set was assessed, yielding a Root Mean Square Error (RMSE) of 2.65 cases per 100,000 population and a Mean Absolute Percentage Error (MAPE) of 29.7%. Predictions for 2024–2025 suggest a stable incidence level with seasonal peaks in the summer and autumn months, and no indication of a large-scale outbreak beyond historical patterns.</div></div><div><h3>Conclusion</h3><div>The ARIMA multiplicative seasonal model can capture the seasonal pattern of foodborne disease incidence in Nanning City. While short-term prediction accuracy is acceptable, the model's performance can be affected by anomalous data points. It serves as a useful tool for short-term early warning and seasonal resource planning in public health.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100368"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188401","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":"Potential pandemic: Biothermodynamic analysis of the yellow fever virus-host interaction","authors":"Marko E. Popović ,&nbsp;Maja Stevanović ,&nbsp;Stefan Panić","doi":"10.1016/j.mran.2026.100366","DOIUrl":"10.1016/j.mran.2026.100366","url":null,"abstract":"<div><div>The yellow fever virus can infect several kinds of host cells in the human organism. However, liver damage dominates during yellow fever, due to lysis of hepatocytes and accumulation of virus particles inside them. Thermodynamic driving force for multiplication of viruses provides the answer to why the liver is among the most severely damaged organs during yellow fever, while less damage occurs in kidneys, spleen and bone marrow. The physicochemical perspective on pathogenesis indicates the most thermodynamically and kinetically favorable host cells for multiplication. The mechanistic model developed in this way relates the driving force as the fundamental physical force and pathogenesis as a biological phenomenon.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100366"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077971","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":"Optimizing vaccination strategies for mpox control in endemic areas: Modeling insights from the Democratic Republic of Congo","authors":"Aakash Pandey ,&nbsp;Ian Spicknall ,&nbsp;Andrea M. McCollum ,&nbsp;Christine M. Hughes ,&nbsp;Beatrice Nguete ,&nbsp;Toutou Likafi ,&nbsp;Robert Shongo Lushima ,&nbsp;Placide Mbala-Kingebeni ,&nbsp;Joelle Kabamba ,&nbsp;Didine Kaba ,&nbsp;Yoshinori Nakazawa","doi":"10.1016/j.mran.2025.100363","DOIUrl":"10.1016/j.mran.2025.100363","url":null,"abstract":"<div><div>The global mpox outbreak of 2022, caused by the Clade IIb strain of monkeypox virus, underscored the potential of this virus to pose a significant public health threat on a global scale. The Democratic Republic of Congo is currently facing multiple outbreaks associated with Clade I. Effectively controlling localized community transmission within endemic areas through vaccination can reduce the likelihood of broader regional or even global outbreaks. Large-scale community vaccination in DRC is challenged by limited resources, including vaccine availability during early outbreaks in remote areas, whereas limited surveillance, contact tracing, and accessibility to remote locations can reduce the effectiveness of targeted ring vaccination. Furthermore, recent outbreaks in DRC have been driven by both sexual and non-sexual close contact transmissions. Here, we used an agent-based model with stochastic transmission within and between households to assess the effectiveness of ring vaccination for controlling localized community transmission in the presence of incomplete case reporting and delay in vaccination. We consider both nonsexual close contact and sexual transmission. We found that ring vaccination, even with 25–50 % reporting, is effective in reducing outbreak cluster sizes and the likelihood of large cluster sizes (&gt;5 cases), particularly when implemented shortly after detection of initial cases. The effectiveness of ring vaccination reduces with the inclusion of sexual transmission. We show that outbreak size and the likelihood of large clusters are reduced when responding to every reported infection, even with 2–3 weeks of delay. Settings with strong surveillance systems characterized by high levels of reporting will have earlier case detection, enabling earlier response and improving the effectiveness of ring vaccination.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100363"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883990","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":"Climate-driven modeling of Japanese spotted fever, an emerging tick-borne disease","authors":"Hoang Thao Giang Nguyen,&nbsp;Kosuke Kamio,&nbsp;Do Tung Dac,&nbsp;J. Luis Espinoza","doi":"10.1016/j.mran.2026.100367","DOIUrl":"10.1016/j.mran.2026.100367","url":null,"abstract":"<div><div>Japanese Spotted Fever (JSF), a tick-borne disease caused by Rickettsia japonica, has shown a sustained increase in incidence and geographic expansion across Japan over the past two decades. Using a 21-year (1999–2019) prefecture-level dataset, we examined associations between climatic conditions and JSF incidence and evaluated their predictive utility within machine learning frameworks. We developed Random Forest regression models incorporating prefecture identifiers, climatic variables, and a one-year lag of JSF cases to account for spatial heterogeneity and temporal autocorrelation. Models based solely on national-average climate variables exhibited poor predictive performance, indicating that climate alone does not explain temporal increases in JSF incidence. In contrast, spatially explicit models achieved substantially improved accuracy, and inclusion of lagged incidence yielded the strongest predictive gains (MSE = 37.03, R² = 0.76 for 2017–2019). Feature importance analyses identified prior-year cases as the dominant predictor, while temperature, sunshine hours, and snow-related variables contributed secondary explanatory signal. These findings suggest that climatic factors primarily define broad regional suitability for JSF, whereas short-term incidence dynamics are largely driven by spatially persistent and temporally autocorrelated processes. Climate-informed models may nonetheless support regional surveillance and risk stratification when combined with historical incidence and spatial context.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100367"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188399","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":"Next generation risk assessment: A proof of concept for the integration of genomic data on cold tolerance into quantitative microbial risk assessment for Campylobacter jejuni in poultry meat","authors":"Eduardo de Freitas Costa ,&nbsp;Andries A. Kampfraath ,&nbsp;Dirkjan Schokker ,&nbsp;Menno van der Voort ,&nbsp;Roan Pijnacker ,&nbsp;Clazien J. de Vos ,&nbsp;Eric G. Evers ,&nbsp;Alex Bossers ,&nbsp;Jose L. Gonzales ,&nbsp;Ewa Pacholewicz","doi":"10.1016/j.mran.2026.100365","DOIUrl":"10.1016/j.mran.2026.100365","url":null,"abstract":"<div><div>Quantitative Microbiological Risk assessment (QMRA) models are essential tools for setting up mitigation strategies. Traditional QMRA modelling approaches do not account for the correlation between genetic traits and variability among pathogens, potentially leading to over- or underestimation of microbial exposure and associated risks. We aimed to integrate genomic data into QMRA to propagate bacterial strain variability and update the existing framework of QMRA, following a Next Generation Risk Assessment (NGRA) approach. We used a benchmark QMRA model describing the prevalence and concentration of <em>Campylobacter jejuni</em> on chicken in all stages from farm-to-fork, to model the risk of infection and illness related to consumption of chicken meat. We integrated extended the storage step, to account for genetic variability in cold inactivation by incorporating gene-level genomic data associated with cold tolerance, derived from literature and a large <em>C. jejuni</em> genomic dataset, into the traditional QMRA model by setting up cold inactivation curves from existing data to map the relationship between the number of cold tolerance genes and temperature-dependent inactivation. The predicted number of cases was 8822 human cases/year in the benchmark QMRA model. The contamination of meat with <em>C. jejuni</em> strains having lower cold tolerance genes can reduce the expected number of human campylobacteriosis cases up to 100%; on the other hand, higher number of cold tolerance genes resulted in an increase up to 335.8% on the expected number of cases. Although our results are based on simulations, we show a potential implementation of the genetic information into QMRA, linking risk estimates with whole-genome sequencing data. More research is needed to understand how genetic features shape phenotypical characteristics, which is one of the main uncertainties in the current NGRA model, and to further explore the implications for risk management.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100365"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037795","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":"Salmonellosis risk assessment for comminuted turkey under different specificities of concentration-based and virulence-based final product standards","authors":"Yiyi Li,&nbsp;Cecil Barnett-Neefs,&nbsp;Matthew J. Stasiewicz","doi":"10.1016/j.mran.2025.100359","DOIUrl":"10.1016/j.mran.2025.100359","url":null,"abstract":"<div><div>Prevalence-based performance standards have guided <em>Salmonella</em> control in poultry industry, but concentration- and virulence-based final product standards could target the most risky contamination more specifically. We adapted our previous risk assessment for chicken parts to comminuted turkey to assess the risk in products implicated by different final product standards, incorporating assumptions from FSIS 2024 risk assessments. We simulated the attributable fraction of illnesses from products contaminated over three level thresholds (0.0031 CFU/g, 1 CFU/g, and 10 CFU/g) and/or containing a serotype in three lists (“Top 3 most prevalent higher-virulence serotypes”, “All higher-virulence serotypes”, and “Higher-virulence proportion of each serotype”). Results showed that 87 % of illnesses were attributed to the 0.56 % of products with <em>Salmonella</em> exceeding 10 CFU/g. Under more specific criteria of level “AND” serotype, 60 % of illnesses were attributed to the 0.14 % of products contaminated with <em>Salmonella</em> exceeding 10 CFU/g and one of the three most prevalent higher-virulence serotypes. Further, applying genomic-based clustering information, 75 % of illnesses were attributed to slightly more products (0.19 %) containing <em>Salmonella</em> exceeding 10 CFU/g and higher-virulence proportion of each serotype. Under the less specific standard, however, 99 % of illnesses were attributed to the 5.7 % of products containing <em>Salmonella</em> exceeding 10 CFU/g “OR” one of the higher-virulence serotypes. Our study demonstrated that most salmonellosis risk is concentrated in comminuted turkey products with high levels of higher-virulence contaminations. Importantly, more specifically targeting those products could efficiently reduce public health risk while minimizing products implicated.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100359"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665510","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":"Development and implementation of a rapid risk assessment tool to enhance and standardise aquatic animal health risk management","authors":"Mickael Teixeira Alves ,&nbsp;Mark Thrush ,&nbsp;Edmund J. Peeler ,&nbsp;Sophie Armitage ,&nbsp;Debbie Murphy ,&nbsp;Chantelle Hooper ,&nbsp;John P. Bignell ,&nbsp;Richard Hazelgrove ,&nbsp;David Bass ,&nbsp;Hannah J. Tidbury","doi":"10.1016/j.mran.2025.100362","DOIUrl":"10.1016/j.mran.2025.100362","url":null,"abstract":"<div><div>Timely, comprehensive risk assessments for disease management are often challenging, particularly in the event of sudden epidemiological events, new threats or shifting drivers of disease expression. To better address emerging threats and justify control measures for existing diseases, a rapid risk assessment tool was developed to support strategic decision-making and effective aquatic animal health management. Based on international standards for risk analysis from the World Health Organisation and World Organisation for Animal Health, this tool aims to provide a systematic, transparent and repeatable risk assessment of aquatic animal diseases to advise on policy decision. Accessibility of the tool facilitates rapid gathering and evaluation of a wide range of information and data, in turn ensuring a flexible, dynamic and effective process to respond to rapid changes in knowledge or epidemiological situation. Informing on the amount of uncertainty at each step of the risk assessment, the tool directly supports risk communication by providing a clear, well-defined structure based on common risk methodology and terminology, and assists risk managers in understanding broader threats, including impacts on trade, wildlife and the environment. Applications of the tool to a wide range of epidemiological contexts, including novel domestic events, investigation of mortality events, data collation from expert elicitation, information dissemination and disease ranking for policy strategic prioritisation, provide valuable insights facilitating the provision and communication of risk-based advice to underpin aquatic disease management.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"31 ","pages":"Article 100362"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749926","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":"Quantitative data and models for bacterial cross-contamination in domestic kitchen during food handling and preparation","authors":"Dixuan Cai ,&nbsp;Jinhan He ,&nbsp;Runrun Zhang ,&nbsp;Xinyu Liao ,&nbsp;Juhee Ahn ,&nbsp;Jinsong Feng ,&nbsp;Tian Ding","doi":"10.1016/j.mran.2025.100356","DOIUrl":"10.1016/j.mran.2025.100356","url":null,"abstract":"<div><div>Cross-contamination is a significant factor contributing to outbreaks of foodborne diseases and food spoilage, and is an important component of quantitative microbial risk assessment (QMRA). The domestic environment represents the final stage of exposure assessment, and data underscore that the exposure risk of foodborne pathogens to consumers is closely linked to cross-contamination in household settings. However, transfer rate data and cross-contamination models from previous studies are fragmented and require integration and categorization for more effective utilization within the QMRA framework. This review summarizes the potential impacts of vehicles during bacterial transmission, transfer rate data for common routes, and current models in domestic kitchens, providing valuable support for cross-contamination modeling within the exposure assessment. In the future, the data gap in the household scenario should be further investigated, particularly in water- and glove-mediated processes. The models can be further improved and refined as deeper underlying mechanisms are uncovered, alongside consumer behavior investigations and the application of AI-powered methods.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"30 ","pages":"Article 100356"},"PeriodicalIF":4.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145264932","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}