{"title":"流感传播的模拟:模型开发、参数估计和缓解策略","authors":"S. Andradóttir, Wenchi Chiu, D. Goldsman, M. Lee","doi":"10.1080/19488300.2014.880093","DOIUrl":null,"url":null,"abstract":"Simulation models for disease propagation have been widely used over the last several years. Such models allow one to study and evaluate the potential impacts of various government intervention policies. However, due to the lack of common guidelines, researchers have built simulation models separately and often in isolation, resulting in the repeated re-invention of the wheel. This paper provides a broad review of disease propagation simulation models. We discuss methods for generating susceptible populations, the choice of influenza transmission parameters, and various mitigation strategies. Our aim is to provide the information needed for researchers, practitioners, and decision makers to build simulation models for influenza propagation in particular (and disease propagation in general), and to use these models to better understand diseases, analyze people's behaviors, and identify appropriate intervention strategies.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"4 1","pages":"27 - 48"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2014.880093","citationCount":"8","resultStr":"{\"title\":\"Simulation of influenza propagation: Model development, parameter estimation, and mitigation strategies\",\"authors\":\"S. Andradóttir, Wenchi Chiu, D. Goldsman, M. Lee\",\"doi\":\"10.1080/19488300.2014.880093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Simulation models for disease propagation have been widely used over the last several years. Such models allow one to study and evaluate the potential impacts of various government intervention policies. However, due to the lack of common guidelines, researchers have built simulation models separately and often in isolation, resulting in the repeated re-invention of the wheel. This paper provides a broad review of disease propagation simulation models. We discuss methods for generating susceptible populations, the choice of influenza transmission parameters, and various mitigation strategies. Our aim is to provide the information needed for researchers, practitioners, and decision makers to build simulation models for influenza propagation in particular (and disease propagation in general), and to use these models to better understand diseases, analyze people's behaviors, and identify appropriate intervention strategies.\",\"PeriodicalId\":89563,\"journal\":{\"name\":\"IIE transactions on healthcare systems engineering\",\"volume\":\"4 1\",\"pages\":\"27 - 48\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/19488300.2014.880093\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IIE transactions on healthcare systems engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/19488300.2014.880093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IIE transactions on healthcare systems engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19488300.2014.880093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simulation of influenza propagation: Model development, parameter estimation, and mitigation strategies
Simulation models for disease propagation have been widely used over the last several years. Such models allow one to study and evaluate the potential impacts of various government intervention policies. However, due to the lack of common guidelines, researchers have built simulation models separately and often in isolation, resulting in the repeated re-invention of the wheel. This paper provides a broad review of disease propagation simulation models. We discuss methods for generating susceptible populations, the choice of influenza transmission parameters, and various mitigation strategies. Our aim is to provide the information needed for researchers, practitioners, and decision makers to build simulation models for influenza propagation in particular (and disease propagation in general), and to use these models to better understand diseases, analyze people's behaviors, and identify appropriate intervention strategies.