Evaluating the Impact of Vaccination on COVID-19 Pandemic Used a Hierarchical Weighted Contact Network Model
Luo, Tianyi1,2; Cao, Zhidong1,2,3; Zhao, Pengfei1,2,3; Zeng, Daniel Dajun1,2,3; Zhang, Qingpeng4
2021-11
会议名称2021 IEEE International Conference on Intelligence and Security Informatics (ISI)
会议日期2022-11-2-11-3
会议地点线上
摘要

The 2019 Novel Coronavirus Disease (COVID-19) vaccines have been placed significant expectation to end the COVID-19 pandemic sooner. However, issues related to vaccines still need to be resolved urgently, including the vaccination number and range. In this paper, we proposed an epidemic spread model based on the hierarchical weighted network. This model fully considers the heterogeneity of the community social contact network and the epidemiological characteristics of COVID-19 in China, which enables to evaluate the potential impact of vaccine efficacy, vaccination schemes, and mixed interventions on the epidemic. The results show that a mass vaccination can effectively control the epidemic but cannot completely eliminate it. In the case of limited resources, giving vaccination priority to the individuals with high contact intensity in the community is necessary. Joint implementation with non-pharmacological interventions strengthening the control of virus transmission. The results provide insights for decision-makers with effective vaccination plans and prevention and control programs.

DOI10.1109/ISI53945.2021.9624841
收录类别EI
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/48981
专题多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者Cao, Zhidong
作者单位1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
3.Shenzhen Artificial Intelligence and Data Science Institute (Longhua), Shenzhen, China
4.School of Data Science, City University of Hong Kong, Hong Kong SAR, China
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Luo, Tianyi,Cao, Zhidong,Zhao, Pengfei,et al. Evaluating the Impact of Vaccination on COVID-19 Pandemic Used a Hierarchical Weighted Contact Network Model[C],2021.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Evaluating_the_Impac(1062KB)会议论文 开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Luo, Tianyi]的文章
[Cao, Zhidong]的文章
[Zhao, Pengfei]的文章
百度学术
百度学术中相似的文章
[Luo, Tianyi]的文章
[Cao, Zhidong]的文章
[Zhao, Pengfei]的文章
必应学术
必应学术中相似的文章
[Luo, Tianyi]的文章
[Cao, Zhidong]的文章
[Zhao, Pengfei]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Evaluating_the_Impact_of_Vaccination_on_COVID-19_Pandemic_Used_a_Hierarchical_Weighted_Contact_Network_Model.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。