Roberto Condoleo , Rachel A. Taylor , Robin R.L. Simons , Paul Gale , Ziad Mezher , Helen Roberts
{"title":"对外来动物病原体进入欧盟成员国的风险进行排名的半定量模型","authors":"Roberto Condoleo , Rachel A. Taylor , Robin R.L. Simons , Paul Gale , Ziad Mezher , Helen Roberts","doi":"10.1016/j.mran.2021.100175","DOIUrl":null,"url":null,"abstract":"<div><p>Risk ranking tools to prioritize the impact of exotic animal diseases in a country or area are useful to assist risk managers in optimizing the allocation of available resources for the prevention and control of infectious diseases. Although several such tools have already been developed, few focus on the probability of entry of an exotic pathogen into a territory and even fewer are able to rank multiple pathogens at the same time. We developed a semi-quantitative multi-criteria model to estimate the probability of incursion of an exotic pathogen into a European country and use Italy as a case study. We consider the import of 37 animal diseases of importance to Italy, based on OIE notification guidelines, and determine a disease status around the world based on current country-level reporting to the OIE. We identify seven possible pathways for the introduction of a pathogen and for each of them we determine a scoring system to assess for each disease the probability of introduction via each pathway. These scores, alongside the disease status, are used to calculate an overall risk score for each pathogen. The results indicate that the risk of incursion of <em>Echinococcus multilocularis</em>, African swine fever virus, <em>Trichinella</em> spp., lumpy skin disease and foot and mouth disease virus are ranked the highest. Additional analyses identified that the disease ranking is sensitive to the relative importance of the pathways of entry and also the impact of potential mitigation measures. The model is designed to be periodically updated with new data as they become available, e.g. global disease prevalence and trade volume. Therefore, it can be used by official authorities on a regular basis to obtain up-to-date results and consequentially strengthen surveillance towards those pathogens with the highest probability of entry.</p></div>","PeriodicalId":48593,"journal":{"name":"Microbial Risk Analysis","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.mran.2021.100175","citationCount":"4","resultStr":"{\"title\":\"A semi-quantitative model for ranking the risk of incursion of exotic animal pathogens into a European Union Member State\",\"authors\":\"Roberto Condoleo , Rachel A. Taylor , Robin R.L. Simons , Paul Gale , Ziad Mezher , Helen Roberts\",\"doi\":\"10.1016/j.mran.2021.100175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Risk ranking tools to prioritize the impact of exotic animal diseases in a country or area are useful to assist risk managers in optimizing the allocation of available resources for the prevention and control of infectious diseases. Although several such tools have already been developed, few focus on the probability of entry of an exotic pathogen into a territory and even fewer are able to rank multiple pathogens at the same time. We developed a semi-quantitative multi-criteria model to estimate the probability of incursion of an exotic pathogen into a European country and use Italy as a case study. We consider the import of 37 animal diseases of importance to Italy, based on OIE notification guidelines, and determine a disease status around the world based on current country-level reporting to the OIE. We identify seven possible pathways for the introduction of a pathogen and for each of them we determine a scoring system to assess for each disease the probability of introduction via each pathway. These scores, alongside the disease status, are used to calculate an overall risk score for each pathogen. The results indicate that the risk of incursion of <em>Echinococcus multilocularis</em>, African swine fever virus, <em>Trichinella</em> spp., lumpy skin disease and foot and mouth disease virus are ranked the highest. Additional analyses identified that the disease ranking is sensitive to the relative importance of the pathways of entry and also the impact of potential mitigation measures. The model is designed to be periodically updated with new data as they become available, e.g. global disease prevalence and trade volume. Therefore, it can be used by official authorities on a regular basis to obtain up-to-date results and consequentially strengthen surveillance towards those pathogens with the highest probability of entry.</p></div>\",\"PeriodicalId\":48593,\"journal\":{\"name\":\"Microbial Risk Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.mran.2021.100175\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microbial Risk Analysis\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352352221000177\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microbial Risk Analysis","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352352221000177","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
A semi-quantitative model for ranking the risk of incursion of exotic animal pathogens into a European Union Member State
Risk ranking tools to prioritize the impact of exotic animal diseases in a country or area are useful to assist risk managers in optimizing the allocation of available resources for the prevention and control of infectious diseases. Although several such tools have already been developed, few focus on the probability of entry of an exotic pathogen into a territory and even fewer are able to rank multiple pathogens at the same time. We developed a semi-quantitative multi-criteria model to estimate the probability of incursion of an exotic pathogen into a European country and use Italy as a case study. We consider the import of 37 animal diseases of importance to Italy, based on OIE notification guidelines, and determine a disease status around the world based on current country-level reporting to the OIE. We identify seven possible pathways for the introduction of a pathogen and for each of them we determine a scoring system to assess for each disease the probability of introduction via each pathway. These scores, alongside the disease status, are used to calculate an overall risk score for each pathogen. The results indicate that the risk of incursion of Echinococcus multilocularis, African swine fever virus, Trichinella spp., lumpy skin disease and foot and mouth disease virus are ranked the highest. Additional analyses identified that the disease ranking is sensitive to the relative importance of the pathways of entry and also the impact of potential mitigation measures. The model is designed to be periodically updated with new data as they become available, e.g. global disease prevalence and trade volume. Therefore, it can be used by official authorities on a regular basis to obtain up-to-date results and consequentially strengthen surveillance towards those pathogens with the highest probability of entry.
期刊介绍:
The journal Microbial Risk Analysis accepts articles dealing with the study of risk analysis applied to microbial hazards. Manuscripts should at least cover any of the components of risk assessment (risk characterization, exposure assessment, etc.), risk management and/or risk communication in any microbiology field (clinical, environmental, food, veterinary, etc.). This journal also accepts article dealing with predictive microbiology, quantitative microbial ecology, mathematical modeling, risk studies applied to microbial ecology, quantitative microbiology for epidemiological studies, statistical methods applied to microbiology, and laws and regulatory policies aimed at lessening the risk of microbial hazards. Work focusing on risk studies of viruses, parasites, microbial toxins, antimicrobial resistant organisms, genetically modified organisms (GMOs), and recombinant DNA products are also acceptable.