Lao-bing Zhang, Chen Bin, L. Liang, Yuanzheng Ge, X. Qiu
{"title":"An approach to model the interventions of unconventional emergency","authors":"Lao-bing Zhang, Chen Bin, L. Liang, Yuanzheng Ge, X. Qiu","doi":"10.1109/SOLI.2013.6611485","DOIUrl":null,"url":null,"abstract":"Aim at preventing, or controlling if prevention is not possible, the spread of disease. We model several types of commonly-used government interventions in order to quantify this research. Finally we computationally tested the models using an artificial campus. The results show: 1) Campus pandemics extinguish even without intervention 2) Small scale inoculation programs are ineffectual, but large scale inoculation programs will bring non-linear increases in benefits 3) Identifying and isolating the infectious and their `strong social group' quickly dramatically lowers spread 4)Isolation Plus Close Public-space Intervention will decrease the peak value and the last time. This study can support quantitative experimentation and prediction of infectious diseases within predefined areas, and assessment of intervention strategies.","PeriodicalId":147180,"journal":{"name":"Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOLI.2013.6611485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Aim at preventing, or controlling if prevention is not possible, the spread of disease. We model several types of commonly-used government interventions in order to quantify this research. Finally we computationally tested the models using an artificial campus. The results show: 1) Campus pandemics extinguish even without intervention 2) Small scale inoculation programs are ineffectual, but large scale inoculation programs will bring non-linear increases in benefits 3) Identifying and isolating the infectious and their `strong social group' quickly dramatically lowers spread 4)Isolation Plus Close Public-space Intervention will decrease the peak value and the last time. This study can support quantitative experimentation and prediction of infectious diseases within predefined areas, and assessment of intervention strategies.