{"title":"人畜共患病和病媒传播病毒建模。","authors":"Seth D Judson , David W Dowdy","doi":"10.1016/j.coviro.2024.101428","DOIUrl":null,"url":null,"abstract":"<div><p>The 2013–2016 Ebola virus disease epidemic and the coronavirus disease 2019 pandemic galvanized tremendous growth in models for emerging zoonotic and vector-borne viruses. Therefore, we have reviewed the main goals and methods of models to guide scientists and decision-makers. The elements of models for emerging viruses vary across spectrums: from understanding the past to forecasting the future, using data across space and time, and using statistical versus mechanistic methods. Hybrid/ensemble models and artificial intelligence offer new opportunities for modeling. Despite this progress, challenges remain in translating models into actionable decisions, particularly in areas at highest risk for viral disease outbreaks. To address this issue, we must identify gaps in models for specific viruses, strengthen validation, and involve policymakers in model development.</p></div>","PeriodicalId":11082,"journal":{"name":"Current opinion in virology","volume":"67 ","pages":"Article 101428"},"PeriodicalIF":5.7000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling zoonotic and vector-borne viruses\",\"authors\":\"Seth D Judson , David W Dowdy\",\"doi\":\"10.1016/j.coviro.2024.101428\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The 2013–2016 Ebola virus disease epidemic and the coronavirus disease 2019 pandemic galvanized tremendous growth in models for emerging zoonotic and vector-borne viruses. Therefore, we have reviewed the main goals and methods of models to guide scientists and decision-makers. The elements of models for emerging viruses vary across spectrums: from understanding the past to forecasting the future, using data across space and time, and using statistical versus mechanistic methods. Hybrid/ensemble models and artificial intelligence offer new opportunities for modeling. Despite this progress, challenges remain in translating models into actionable decisions, particularly in areas at highest risk for viral disease outbreaks. To address this issue, we must identify gaps in models for specific viruses, strengthen validation, and involve policymakers in model development.</p></div>\",\"PeriodicalId\":11082,\"journal\":{\"name\":\"Current opinion in virology\",\"volume\":\"67 \",\"pages\":\"Article 101428\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current opinion in virology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1879625724000427\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"VIROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in virology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1879625724000427","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"VIROLOGY","Score":null,"Total":0}
The 2013–2016 Ebola virus disease epidemic and the coronavirus disease 2019 pandemic galvanized tremendous growth in models for emerging zoonotic and vector-borne viruses. Therefore, we have reviewed the main goals and methods of models to guide scientists and decision-makers. The elements of models for emerging viruses vary across spectrums: from understanding the past to forecasting the future, using data across space and time, and using statistical versus mechanistic methods. Hybrid/ensemble models and artificial intelligence offer new opportunities for modeling. Despite this progress, challenges remain in translating models into actionable decisions, particularly in areas at highest risk for viral disease outbreaks. To address this issue, we must identify gaps in models for specific viruses, strengthen validation, and involve policymakers in model development.
期刊介绍:
Current Opinion in Virology (COVIRO) is a systematic review journal that aims to provide specialists with a unique and educational platform to keep up to date with the expanding volume of information published in the field of virology. It publishes 6 issues per year covering the following 11 sections, each of which is reviewed once a year: Emerging viruses: interspecies transmission; Viral immunology; Viral pathogenesis; Preventive and therapeutic vaccines; Antiviral strategies; Virus structure and expression; Animal models for viral diseases; Engineering for viral resistance; Viruses and cancer; Virus vector interactions. There is also a section that changes every year to reflect hot topics in the field.