Pub Date : 2024-12-28DOI: 10.1016/j.mran.2024.100340
Alexandra Fetsch , Nunzio Sarnino , Konstantinos Koutsoumanis , Maarten Nauta , Martin Wiedmann , Katharina D.C. Stärk , Monika Ehling-Schulz , Roger Stephan , Sophia Johler
Foodborne microbial hazards lead to substantial morbidity and mortality. To assure consumer protection, a need to move from hazard-based to risk-based food safety approaches is increasingly recognized. Food-business-operators play a crucial role by implementing risk management practices in their facilities. Still, there is very limited data on current approaches to ensure microbial food safety and the profiles and perceptions of professionals assessing, managing, and communicating risks in food industry. This study addresses food safety approaches and challenges in food industry aiming to provide data on microbial risk analysis according to Codex Alimentarius. A survey elicited responses from 108 food professionals involved in microbial risk assessment, risk management, or risk communication in the food industry. The findings highlight drivers and trends relevant to food safety and the food industries’ internal decision-making processes. Most participants had risk-based food-safety management systems established. A microbial risk assessment according to Codex Alimentarius principles was conducted by 85 %. Professionals pinpointed areas that led to significant microbial incidents such as contaminated raw materials, poor hygiene, or emerging pathogens. Interestingly, one third of the participants believed that zero risk is possible, which contrasts with the scientific consensus that microbial food safety is not absolute as zero risk is not feasible. The results of this work provide insights into the implementation and understanding of microbial risk analysis from a food industrial perspective and could be leveraged to develop innovative microbial risk analysis frameworks that meet the challenges of future food systems.
{"title":"Microbial risk analysis from a food industry perspective – insights from an international survey","authors":"Alexandra Fetsch , Nunzio Sarnino , Konstantinos Koutsoumanis , Maarten Nauta , Martin Wiedmann , Katharina D.C. Stärk , Monika Ehling-Schulz , Roger Stephan , Sophia Johler","doi":"10.1016/j.mran.2024.100340","DOIUrl":"10.1016/j.mran.2024.100340","url":null,"abstract":"<div><div>Foodborne microbial hazards lead to substantial morbidity and mortality. To assure consumer protection, a need to move from hazard-based to risk-based food safety approaches is increasingly recognized. Food-business-operators play a crucial role by implementing risk management practices in their facilities. Still, there is very limited data on current approaches to ensure microbial food safety and the profiles and perceptions of professionals assessing, managing, and communicating risks in food industry. This study addresses food safety approaches and challenges in food industry aiming to provide data on microbial risk analysis according to Codex Alimentarius. A survey elicited responses from 108 food professionals involved in microbial risk assessment, risk management, or risk communication in the food industry. The findings highlight drivers and trends relevant to food safety and the food industries’ internal decision-making processes. Most participants had risk-based food-safety management systems established. A microbial risk assessment according to Codex Alimentarius principles was conducted by 85 %. Professionals pinpointed areas that led to significant microbial incidents such as contaminated raw materials, poor hygiene, or emerging pathogens. Interestingly, one third of the participants believed that zero risk is possible, which contrasts with the scientific consensus that microbial food safety is not absolute as zero risk is not feasible. The results of this work provide insights into the implementation and understanding of microbial risk analysis from a food industrial perspective and could be leveraged to develop innovative microbial risk analysis frameworks that meet the challenges of future food systems.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"29 ","pages":"Article 100340"},"PeriodicalIF":3.0,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140945","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}
Pub Date : 2024-12-25DOI: 10.1016/j.mran.2024.100339
Hernán G. Redondo , Laurent Guillier , Virginie Desvignes , Matthias Filter , Sara M. Pires , Maarten Nauta
In a previous study, we integrated data from individual consumers collected in a dietary survey in France in a multi-food quantitative microbiological risk assessment (QMRA) for listeriosis. Here, we compared the “individual-based” modelling approach applied in that study with several other approaches where the data are treated as in more “traditional” QMRA methods, for example by assuming independent randomly sampled variables from distributions fitted through the data, instead of the observed individual data themselves. We found that assigning randomly sampled storage times instead of the reported individual storage times resulted in a higher risk estimate than the baseline, expressed as expected annual number of cases in the population. Assigning randomly sampled storage temperature and point estimates for portion size and frequency of consumption, slightly increased the estimated risk. Statistical analysis did not show dependency between portion size, frequency of consumption, storage temperature and storage time in the data set, which can be explained by the fact that only a few individuals had a large impact on the final population risk. Analysis of expected numbers of cases per age class, sex and food group showed small differences between approaches. Our analysis was challenged by the difference between a model structure where the risk is calculated per individual (when based on a dietary survey with individual data) and one where it is calculated per serving, as in “traditional” QMRA. We showed that an “individual-based” QMRA is more resource-demanding but can give fundamentally different risk estimates, which are potentially more accurate. The application of tools for efficient knowledge exchange and integration is needed to facilitate the usage of this type of QMRA.
{"title":"Quantitative microbiological risk assessment using individual data on food storage and consumption (Part 2): A comparison with traditional QMRA approaches","authors":"Hernán G. Redondo , Laurent Guillier , Virginie Desvignes , Matthias Filter , Sara M. Pires , Maarten Nauta","doi":"10.1016/j.mran.2024.100339","DOIUrl":"10.1016/j.mran.2024.100339","url":null,"abstract":"<div><div>In a previous study, we integrated data from individual consumers collected in a dietary survey in France in a multi-food quantitative microbiological risk assessment (QMRA) for listeriosis. Here, we compared the “individual-based” modelling approach applied in that study with several other approaches where the data are treated as in more “traditional” QMRA methods, for example by assuming independent randomly sampled variables from distributions fitted through the data, instead of the observed individual data themselves. We found that assigning randomly sampled storage times instead of the reported individual storage times resulted in a higher risk estimate than the baseline, expressed as expected annual number of cases in the population. Assigning randomly sampled storage temperature and point estimates for portion size and frequency of consumption, slightly increased the estimated risk. Statistical analysis did not show dependency between portion size, frequency of consumption, storage temperature and storage time in the data set, which can be explained by the fact that only a few individuals had a large impact on the final population risk. Analysis of expected numbers of cases per age class, sex and food group showed small differences between approaches. Our analysis was challenged by the difference between a model structure where the risk is calculated per individual (when based on a dietary survey with individual data) and one where it is calculated per serving, as in “traditional” QMRA. We showed that an “individual-based” QMRA is more resource-demanding but can give fundamentally different risk estimates, which are potentially more accurate. The application of tools for efficient knowledge exchange and integration is needed to facilitate the usage of this type of QMRA.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"29 ","pages":"Article 100339"},"PeriodicalIF":3.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140946","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}
Pub Date : 2024-12-18DOI: 10.1016/j.mran.2024.100338
Alex Royden , Robert Dewar , Brendan Cowled , Rohan Sadler , Alison Hillman , Laura C. Gonzalez-Villeta , Helen Roberts , Catherine McCarthy , Robin R.L. Simons
Trade of live animals and products of animal origin (POAO) carries an inherent risk of spreading pathogens. As such, it is essential for any country to have effective early detection and/or horizon scanning systems in place to be aware of the potential entry risks of pathogens. To this end, the United Kingdom has a number of horizon scanning and risk assessment tools to carry out international disease monitoring. Here we develop these ideas further in a generic, semi-quantitative risk assessment tool; the International Disease Monitoring Plus (IDM+) tool.
The IDM+ tool utilises publicly available data on the presence of terrestrial animal health pathogens and volumes of commodities imported into Great Britain (GB) from multiple trading partners. Identifying the likelihood of a pathogen arriving at the GB border involved >550 individual commodity types, 125 pathogens and 55 countries. It also includes expert opinion on country and commodity specific mitigation measures, to derive a likelihood of entry score for each country, commodity, and pathogen combination.
This paper presents an example of the model used to assess commodities being imported into GB. However, the principle could be applied to any country accepting imports of live animals or POAO.
The IDM+ model considers changes in global pathogen distribution and trade volumes to provide ongoing and rapid appraisal of the likelihood of entry for different commodities, countries, and pathogens. It is designed to be quick to run with a largely automated process, further enabling rapid updates with new disease and trade source and volume data. The model can present results with and without trade volume weighting and with different likelihoods. When a specific import disease risk is identified to be of concern, carrying out a comprehensive import risk analysis is still recommended. However, this model is a valuable tool to provide a holistic overview and comparison of the likelihood of entry to GB of a large number of potential threats to animal health. It can be utilised in time-constrained environments and when limited data are available. The results can be of direct use for a variety of purposes, including, but not limited to, prioritisation of border inspections and in-country audits, rapid output generation for emergency outbreak assessments and/or assessing risk from specific imported consignments.
{"title":"An international disease monitoring tool to estimate the likelihood of entry of animal health hazards from legal trade of live animals and products of animal origin imported from different countries (IDM+)","authors":"Alex Royden , Robert Dewar , Brendan Cowled , Rohan Sadler , Alison Hillman , Laura C. Gonzalez-Villeta , Helen Roberts , Catherine McCarthy , Robin R.L. Simons","doi":"10.1016/j.mran.2024.100338","DOIUrl":"10.1016/j.mran.2024.100338","url":null,"abstract":"<div><div>Trade of live animals and products of animal origin (POAO) carries an inherent risk of spreading pathogens. As such, it is essential for any country to have effective early detection and/or horizon scanning systems in place to be aware of the potential entry risks of pathogens. To this end, the United Kingdom has a number of horizon scanning and risk assessment tools to carry out international disease monitoring. Here we develop these ideas further in a generic, semi-quantitative risk assessment tool; the International Disease Monitoring Plus (IDM+) tool.</div><div>The IDM+ tool utilises publicly available data on the presence of terrestrial animal health pathogens and volumes of commodities imported into Great Britain (GB) from multiple trading partners. Identifying the likelihood of a pathogen arriving at the GB border involved >550 individual commodity types, 125 pathogens and 55 countries. It also includes expert opinion on country and commodity specific mitigation measures, to derive a likelihood of entry score for each country, commodity, and pathogen combination.</div><div>This paper presents an example of the model used to assess commodities being imported into GB. However, the principle could be applied to any country accepting imports of live animals or POAO.</div><div>The IDM+ model considers changes in global pathogen distribution and trade volumes to provide ongoing and rapid appraisal of the likelihood of entry for different commodities, countries, and pathogens. It is designed to be quick to run with a largely automated process, further enabling rapid updates with new disease and trade source and volume data. The model can present results with and without trade volume weighting and with different likelihoods. When a specific import disease risk is identified to be of concern, carrying out a comprehensive import risk analysis is still recommended. However, this model is a valuable tool to provide a holistic overview and comparison of the likelihood of entry to GB of a large number of potential threats to animal health. It can be utilised in time-constrained environments and when limited data are available. The results can be of direct use for a variety of purposes, including, but not limited to, prioritisation of border inspections and in-country audits, rapid output generation for emergency outbreak assessments and/or assessing risk from specific imported consignments.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"29 ","pages":"Article 100338"},"PeriodicalIF":3.0,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140944","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}
Pub Date : 2024-11-12DOI: 10.1016/j.mran.2024.100330
Shun Takayama , Qian Zhang , Ye Htut Zwe , Dan Li , Daisuke Sano , Wakana Oishi
Hydroponics plays an important role in addressing food security concerns, particularly in countries aiming to increase food self-sufficiency. However, it is vulnerable to microbial contamination, and biofilms formed in hydroponic facilities may promote horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs). Eventually, the bacteria are internalized into the edible parts of the vegetable through the roots, which can lead to human exposure to antibiotic-resistant pathogenic bacteria. Microbial risk assessment can play a pivotal role in microbial risk management; however, it has not been conducted for hydroponic systems. In this study, a quantitative microbial risk assessment of hydroponic vegetables was performed using literature values regarding the concentration of Salmonella spp. in hydroponics, efficiency of HGT, probability and rate of internalization, vegetable consumption patterns, and dose-response relationships. Furthermore, a sensitivity analysis was performed to identify the factors that had a significant impact on the infection probability per single exposure event for all Salmonella spp. by calculating Spearman's correlation coefficients. The estimated annual probability of infection per person by all Salmonella spp. was 2.04 × 10−1, while the estimated probability of infection from Salmonella spp. that acquired ARGs was 2.54 × 10−6. Our sensitivity analysis showed the correlation between the occurrence of internalization and hydroponic contamination levels, highlighting the need for increased awareness and regulatory action.
{"title":"Quantitative microbial risk assessment of antibiotic-resistant Salmonella enterica contaminating hydroponic leafy vegetables","authors":"Shun Takayama , Qian Zhang , Ye Htut Zwe , Dan Li , Daisuke Sano , Wakana Oishi","doi":"10.1016/j.mran.2024.100330","DOIUrl":"10.1016/j.mran.2024.100330","url":null,"abstract":"<div><div>Hydroponics plays an important role in addressing food security concerns, particularly in countries aiming to increase food self-sufficiency. However, it is vulnerable to microbial contamination, and biofilms formed in hydroponic facilities may promote horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs). Eventually, the bacteria are internalized into the edible parts of the vegetable through the roots, which can lead to human exposure to antibiotic-resistant pathogenic bacteria. Microbial risk assessment can play a pivotal role in microbial risk management; however, it has not been conducted for hydroponic systems. In this study, a quantitative microbial risk assessment of hydroponic vegetables was performed using literature values regarding the concentration of <em>Salmonella</em> spp. in hydroponics, efficiency of HGT, probability and rate of internalization, vegetable consumption patterns, and dose-response relationships. Furthermore, a sensitivity analysis was performed to identify the factors that had a significant impact on the infection probability per single exposure event for all <em>Salmonella</em> spp. by calculating Spearman's correlation coefficients. The estimated annual probability of infection per person by all <em>Salmonella</em> spp. was 2.04 × 10<sup>−1</sup>, while the estimated probability of infection from <em>Salmonella</em> spp. that acquired ARGs was 2.54 × 10<sup>−6</sup>. Our sensitivity analysis showed the correlation between the occurrence of internalization and hydroponic contamination levels, highlighting the need for increased awareness and regulatory action.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100330"},"PeriodicalIF":3.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658932","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}
Pub Date : 2024-11-08DOI: 10.1016/j.mran.2024.100329
Nicoletta Vitale , Paola Barzanti , Ines Crescio Maria , Rosanna Desiato , Lisa Guardone , Valeria Listorti , Walter Martelli , Cristiana Maurella , Barbara Moroni , Rosaria Possidente , Francesca Rossi , Giuseppe Ru
The aim of this paper is to describe the impact, dynamics and risk factors of the incursion of the African Swine Fever (ASF) virus detected in early 2022 in the wild boar population straddling Piedmont and Liguria, 24 months after its emergence.
A study area of 4,162.2 km2s, comprising 234 municipalities in Liguria and Piedmont (north-western Italy), along with an external buffer zone, was considered. The epidemiological units were wild boars tested for ASF using real-time PCR between late December 2021 and December 31, 2023. The data were obtained from passive and active surveillance. Conventional methodologies were applied in the analysis of time series of tests, cases, or prevalence rates of positive animals. Maps were used to visualise and compare the monitoring activities, the location of cases and municipal standardised prevalence ratios. Clustering of high and low trends was studied by semester using a space-time permutation model. Risk factors analysis was based on multivariate Poisson regression modelling.
Over the 2-year study period, the epidemic's spread was closely monitored by testing 10,412 wild boars (25 % of them from passive surveillance). Probability of disease detection was 10.9 times higher among found dead animals compared with animals tested in active surveillance. Difficulties in carcass searching led to heterogeneities in surveillance sensitivity achieved locally and inherent uncertainties. A total of 1,165 wild boars that tested positive for ASF have been detected in 125 municipalities across three provinces. The outbreak has expanded over time and exhibited an increasing trend, with an epidemic doubling time of 10.7 months. There was seasonality, with an increasing trend from summer to spring. Prevalence rates followed the same temporal pattern. Significant low and high clusters respectively indicated endemic episodes in the interior areas of virus circulation and an ongoing invasion of surrounding regions.
The characteristics of this outbreak align with the cycle of wild boar habitat transmission observed in other outbreaks across Europe. The measures implemented were not sufficient to stop the epidemic: however, targeted interventions such as depopulation campaigns, reinforcement of physical barriers and increased biosecurity measures have prevented local spillover to domestic pigs and partially hindered the advance of the disease. In addition, the shown seasonality of the disease, likely can enhance control measures. The ongoing studies of the local wild boar populations and the evolution the epidemic along with the lessons learned so far will improve the efficiency and effectiveness of efforts to limit and ultimately eradicate the disease.
{"title":"Measuring transboundary disease spread - ASF in wild boars straddling Piedmont and Liguria","authors":"Nicoletta Vitale , Paola Barzanti , Ines Crescio Maria , Rosanna Desiato , Lisa Guardone , Valeria Listorti , Walter Martelli , Cristiana Maurella , Barbara Moroni , Rosaria Possidente , Francesca Rossi , Giuseppe Ru","doi":"10.1016/j.mran.2024.100329","DOIUrl":"10.1016/j.mran.2024.100329","url":null,"abstract":"<div><div>The aim of this paper is to describe the impact, dynamics and risk factors of the incursion of the African Swine Fever (ASF) virus detected in early 2022 in the wild boar population straddling Piedmont and Liguria, 24 months after its emergence.</div><div>A study area of 4,162.2 km<sup>2</sup>s, comprising 234 municipalities in Liguria and Piedmont (north-western Italy), along with an external buffer zone, was considered. The epidemiological units were wild boars tested for ASF using real-time PCR between late December 2021 and December 31, 2023. The data were obtained from passive and active surveillance. Conventional methodologies were applied in the analysis of time series of tests, cases, or prevalence rates of positive animals. Maps were used to visualise and compare the monitoring activities, the location of cases and municipal standardised prevalence ratios. Clustering of high and low trends was studied by semester using a space-time permutation model. Risk factors analysis was based on multivariate Poisson regression modelling.</div><div>Over the 2-year study period, the epidemic's spread was closely monitored by testing 10,412 wild boars (25 % of them from passive surveillance). Probability of disease detection was 10.9 times higher among found dead animals compared with animals tested in active surveillance. Difficulties in carcass searching led to heterogeneities in surveillance sensitivity achieved locally and inherent uncertainties. A total of 1,165 wild boars that tested positive for ASF have been detected in 125 municipalities across three provinces. The outbreak has expanded over time and exhibited an increasing trend, with an epidemic doubling time of 10.7 months. There was seasonality, with an increasing trend from summer to spring. Prevalence rates followed the same temporal pattern. Significant low and high clusters respectively indicated endemic episodes in the interior areas of virus circulation and an ongoing invasion of surrounding regions.</div><div>The characteristics of this outbreak align with the cycle of wild boar habitat transmission observed in other outbreaks across Europe. The measures implemented were not sufficient to stop the epidemic: however, targeted interventions such as depopulation campaigns, reinforcement of physical barriers and increased biosecurity measures have prevented local spillover to domestic pigs and partially hindered the advance of the disease. In addition, the shown seasonality of the disease, likely can enhance control measures. The ongoing studies of the local wild boar populations and the evolution the epidemic along with the lessons learned so far will improve the efficiency and effectiveness of efforts to limit and ultimately eradicate the disease.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100329"},"PeriodicalIF":3.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658933","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}
Pub Date : 2024-11-08DOI: 10.1016/j.mran.2024.100327
Thanh Tran , Van Huu Dat , Vu Nhat Phuong , Tran Hoang Cam Tu , Do Vinh Duong , Ho Huu Loc
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.
{"title":"Assessing urban street food safety among youth: The impact of road dust on potential microbial contamination risks to student health","authors":"Thanh Tran , Van Huu Dat , Vu Nhat Phuong , Tran Hoang Cam Tu , Do Vinh Duong , 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":"2024-11-08","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}
Pub Date : 2024-11-04DOI: 10.1016/j.mran.2024.100328
Elli Amanatidou , J. Andrew Hudson , Johanna Jackson , Victoria Cohen , Svetlozara Chobanova , Marianne James , Andy Axon
The Food and Agriculture Organization (FAO) promote risk categorization approaches to assist understanding the public health risk associated with imported foods such as cheeses. A risk categorization should use information from the imported food, importer and exporting country profile to establish risk associated with imported foods. The first step involves assessing the product characteristics whilst step two is intended to consider country specific controls.
In this paper, we describe the first step in the development of a risk ranking approach using product characteristics to rank cheeses based on microbiological risk. The approach is applied to sixty types that may be commonly traded, based on an assessment of UK data on cheese imports. It uses risk factors of milk pasteurization, ripening method, and predicted pathogen growth in the finished cheese. Each risk factor was scored, and the total used to rank the cheeses with respect to the likelihood of them containing viable pathogens at the border, dependent on initial pathogen presence and potential for subsequent growth. The possible range of scores was 0 to 6. After scoring, none scored 0 or 1, and 13 scored 6.
Using international foodborne disease outbreaks and EU Rapid Alert System for Food and Feed (RASFF) notifications as benchmarks, cheese types were assigned one of four qualitative risk levels, from Very Low to High, based on their scores. These qualitative intervals did not align with trade codes, which are not risk-based, as some codes included cheeses from different risk levels. Neither was there a good correlation with Codex cheese classes, although it was noted that some very hard cheeses (e.g., Parmesan) received the lowest risk scores.
When scores were compared with outbreak and RASFF qualitative data there was a good correlation. For example, of those scored, no cheese scoring ≤3 had received a RASFF notification or caused an outbreak. Of the outbreaks associated with cheese types that were scored, 83.3 % of outbreaks implicated cheeses with a score ≥5.
For the sixty cheeses presented here, the data required for scoring were available. However, data may not be available for all cheeses. Where it is necessary to score a cheese that is lacking the necessary data, a read-across approach would be a potential solution, but this would increase associated uncertainty. The use of a standardized approach to risk ranking of cheeses produced consistent risk-based information that can be compared between cheese types but not between two classification systems (Harmonised System and Codex system). This aligns with the fact that neither classification system was designed to correlate with consumer safety.
{"title":"An approach to the microbiological risk ranking of cheeses","authors":"Elli Amanatidou , J. Andrew Hudson , Johanna Jackson , Victoria Cohen , Svetlozara Chobanova , Marianne James , Andy Axon","doi":"10.1016/j.mran.2024.100328","DOIUrl":"10.1016/j.mran.2024.100328","url":null,"abstract":"<div><div>The Food and Agriculture Organization (FAO) promote risk categorization approaches to assist understanding the public health risk associated with imported foods such as cheeses. A risk categorization should use information from the imported food, importer and exporting country profile to establish risk associated with imported foods. The first step involves assessing the product characteristics whilst step two is intended to consider country specific controls.</div><div>In this paper, we describe the first step in the development of a risk ranking approach using product characteristics to rank cheeses based on microbiological risk. The approach is applied to sixty types that may be commonly traded, based on an assessment of UK data on cheese imports. It uses risk factors of milk pasteurization, ripening method, and predicted pathogen growth in the finished cheese. Each risk factor was scored, and the total used to rank the cheeses with respect to the likelihood of them containing viable pathogens at the border, dependent on initial pathogen presence and potential for subsequent growth. The possible range of scores was 0 to 6. After scoring, none scored 0 or 1, and 13 scored 6.</div><div>Using international foodborne disease outbreaks and EU Rapid Alert System for Food and Feed (RASFF) notifications as benchmarks, cheese types were assigned one of four qualitative risk levels, from Very Low to High, based on their scores. These qualitative intervals did not align with trade codes, which are not risk-based, as some codes included cheeses from different risk levels. Neither was there a good correlation with Codex cheese classes, although it was noted that some very hard cheeses (e.g., Parmesan) received the lowest risk scores.</div><div>When scores were compared with outbreak and RASFF qualitative data there was a good correlation. For example, of those scored, no cheese scoring ≤3 had received a RASFF notification or caused an outbreak. Of the outbreaks associated with cheese types that were scored, 83.3 % of outbreaks implicated cheeses with a score ≥5.</div><div>For the sixty cheeses presented here, the data required for scoring were available. However, data may not be available for all cheeses. Where it is necessary to score a cheese that is lacking the necessary data, a read-across approach would be a potential solution, but this would increase associated uncertainty. The use of a standardized approach to risk ranking of cheeses produced consistent risk-based information that can be compared between cheese types but not between two classification systems (Harmonised System and Codex system). This aligns with the fact that neither classification system was designed to correlate with consumer safety.</div></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":"27 ","pages":"Article 100328"},"PeriodicalIF":3.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658926","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}
Pub Date : 2024-10-15DOI: 10.1016/j.mran.2024.100326
Marko E. Popović , Maja Stevanović , Vojin Tadić
After the experience with the COVID-19 pandemic, WHO has issued a warning about the possible causes of future pandemics. One such causative agent is the Dengue virus. Until now, we have had information mostly on biological properties of the Dengue virus and very little information about its chemical and thermodynamic properties. To be better prepared for a potential Dengue pandemic, the goal of this paper is to chemically and thermodynamically characterize the Dengue virus, as well as to describe the biophysical basis of the virus-host interactions of the Dengue virus. To that goal, the empirical formula was determined, as well as biosynthesis reactions and thermodynamic properties of antigen-receptor binding and thermodynamic properties of biosynthesis and multiplication of the Dengue virus. A model was developed of virus-host interactions between the Dengue virus and its host tissues, based on nonequilibrium thermodynamics.
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