

浏览全部资源
扫码关注微信
1. 国防科技大学系统工程学院,湖南 长沙 410073
2. 国防科技大学北京学科交叉中心,北京 100101
Published Online:2020-03,
Published:20 March 2020
移动端阅览
Liang MA, Mei YANG, Chuan AI, et al. The evaluation of the control measures for COVID-19 based on ACP approach[J]. Chinese journal of intelligent science and technology, 2020, 2(1): 88-98.
Liang MA, Mei YANG, Chuan AI, et al. The evaluation of the control measures for COVID-19 based on ACP approach[J]. Chinese journal of intelligent science and technology, 2020, 2(1): 88-98. DOI: 10.11959/j.issn.2096-6652.202010.
利用信息技术手段对疫情管控措施进行评估,从而指导管控措施的实施,对疫情防控具有理论和现实意义。基于ACP方法和统计数据构建了人工城市计算实验平台,建立了针对具体疫情管控的社区、学校、工厂3类典型场所的人工社会模型,通过计算实验对新型冠状病毒肺炎疫情的管控措施进行评估。结果发现,检验检疫、自我防护管控措施只能够延缓疫情中感染人数峰值的到来,对降低总感染人数的效果不明显,只有经济代价巨大的隔离措施能够显著地抑制疫情的发展。隔离措施的良好效果表明,有效阻断“人-人”传播链是疫情控制的关键环节,因此建议综合采用检验检疫、大数据、人工智能等手段精准筛查病患及潜在感染者。
It is theoretical and practical significance for epidemic prevention and control to evaluate epidemic control measures using information technology so as to guide the implementation of epidemic control measures.Based on ACP approach and statistical data
a platform of computation experiment for artificial city was constructed
from which artificial models were established for three typical places
namely community
school and factory
to support the evaluation of specific epidemic control measures.The control measures of COVID-19 were evaluated through the computational experiments.The results showed that the control measures of quarantine and self-protection could only delay the peak of the number of infected people in the epidemic
but had no obvious effect on reducing the total number of infected people.Only the isolation measure with huge economic cost could significantly inhibit the development of the epidemic.The effect of the isolation measures showed that effectively blocking the “person-to-person”transmission chain was the key to the epidemic control.Therefore
it was recommended to adopt comprehensive means involving inspection and quarantine
big data
artificial intelligence and so on to accurately screen the patients and potential infected people.
中国-世界卫生组织新型冠状病毒肺炎(COVID-19)联合调查组 . 中国-世界卫生组织新型冠状病毒肺炎(COVID-19)联合考察报告 [R ] . 2020 .
The China-WHO Joint Investigation Team on Novel Coronavirus Pneumonia (COVID-19) . China-WHO joint investigation report on novel coronavirus pneumonia (COVID-19) [R ] . 2020 .
WHO . Coronavirus disease 2019(COVID-19)Situation Report–52 [R ] . 2020 .
王飞跃 , 王晓 , 袁勇 , 等 . 社会计算与计算社会:智慧社会的基础与必然 [J ] . 科学通报 , 2015 , 60 ( 5 ): 460 - 469 .
WANG F Y , WANG X , YUAN Y , et al . Social computing and computational societies:the foundation and consequence of smart societies [J ] . Chinese Science Bulletin , 2015 , 60 ( 5 ): 460 - 469 .
WANG F . Toward a paradigm shift in social computing:the ACP approach [J ] . IEEE Intelligent Systems , 2007 , 22 ( 5 ): 65 - 67 .
DUAN W , FAN Z C , ZHANG P , et al . Mathematical and computational approaches to epidemic modeling:a comprehensive review [J ] . Frontiers of Computer Science , 2015 , 9 ( 5 ): 806 - 826 .
SIETTOS C I , RUSSO L . Mathematical modeling of infectious disease dynamics [J ] . Virulence , 2013 , 4 ( 4 ): 295 - 306 .
MAIA J O C D . Some mathematical developments on the epidemic theory formulated by reed and frost [J ] . Human Biology , 1952 , 24 ( 3 ): 167 - 200 .
汪小帆 , 李翔 , 陈关荣 . 网络科学导论 [M ] . 北京 : 高等教育出版社 , 2012 .
WANG X F , LI X , CHEN G R . Introduction to network science [M ] . Beijing : Higher Education PressPress , 2012 .
CARLEY K M , FRIDSMA D B , CASMAN E , et al . BioWar:scalable agent-based model of bioattacks [J ] . IEEE Transactions on Systems,Man,and Cybernetics - Part A:Systems and Humans , 2006 , 36 ( 2 ): 252 - 265 .
BARRETT C L , BISSET K R , EUBANK S G , et al . EpiSimdemics:an efficient algorithm for simulating the spread of infectious disease over large realistic social networks [C ] // Proceedings of the 2008 ACM/IEEE Conference on Supercomputing . Piscataway:IEEE Press , 2008 :37.
CHAO D L , HALLORAN M E , OBENCHAIN V J , et al . FluTE,a publicly available stochastic influenza epidemic simulation model [J ] . PLoS Computational Biology , 2010 , 6 ( 1 ):e1000656.
段伟 . 基于异质agent的疾病传播建模与计算实验 [D ] . 长沙:国防科学技术大学 , 2014 .
DUAN W . Heterogeneous agent-based modeling and computational experiments of infectious disease transmission [D ] . Changsha:National University of Defense Technology , 2014 .
YANG Z F , ZENG Z Q , WANG K , et al . Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J ] . Journal of Thoracic Disease , 2020 , 12 ( 3 ): 165 - 174 .
WANG X , TANG S Y , CHEN Y , et al . When will be the resumption of work in Wuhan and its surrounding areas during COVID-19 epidemic? a data-driven network modeling analysis [J ] . Scientia Sinica Mathematica , 2020 , 50 : 1 - 10 .
CAI Y , WANG H W , WANG Z Z , et al . Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan,China [J ] . Cell Discovery , 2020 , 6 : 1 - 10 .
Al-QUNESS M A A , EWEES A A , FAN H , et al . Optimization method for forecasting confirmed cases of COVID-19 in China [J ] . Journal of Clinical Medicine , 2020 , 9 ( 3 ):674.
GE Y Z , MENG R Q , CAO Z D , et al . Virtual city:an individual-based digital environment for human mobility and interactive behavior [J ] . Simulation:Transactions of the Society for Modeling and Simulation International , 2014 , 90 ( 8 ): 917 - 935 .
DUAN W , CAO Z D , WANG Y Z , et al . An ACP approach to public health emergency management:using a campus outbreak of H1N1 influenza as a case study [J ] . IEEE Transactions on Systems,Man,and Cybernetics:Systems , 2013 , 43 ( 5 ): 1028 - 1041 .
ZHANG P , CHEN B , MA L , et al . The large scale machine learning in an artificial society:prediction of the Ebola outbreak in Beijing [J ] . Computational Intelligence and Neuroscience , 2015 : 1 - 12 .
葛渊峥 . 基于agent的人工社会框架设计与生成方法 [D ] . 长沙:国防科学技术大学 , 2014 .
GE Y Z . An agent-based framework and generation of an artificial society [D ] . Changsha:National University of Defense Technology , 2014 .
LI Q , GUAN X H , WU P , et al . Early transmission dynamics in Wuhan,China,of Novel coronavirus–infected pneumonia [J ] . New England Journal of Medicine , 2020 .(Accepted)
GUAN W J , NI Z Y , HU Y , et al . Clinical characteristics of 2019 novel coronavirus infection in China [J ] . medRxiv , 2020 .(Accepted).
CHEN B , ZHANG L B , GUO G , et al . KD-ACP:a software framework for social computing in emergency management [J ] . Mathematical Problems in Engineering , 2015 : 1 - 27 .
0
Views
268
下载量
0
CSCD
Publicity Resources
Related Articles
Related Author
Related Institution
京公网安备11010802024621