Does our collective stringency control the virus? Investigating lockdown effectiveness on community mobility data

Kangcheng Li, Jiangtao Wang, Zhicen Liu, Yunqi Zhang, Zihao Xie

    Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

    1 Citation (Scopus)
    39 Downloads (Pure)

    Abstract

    Facing the global crisis brought by COVID-19, many countries have adopted social distancing or stay-at-home measures to restrict individual mobility to control the virus. Meanwhile, the availability of anonymized and aggregated mobility data provides an opportunity to obtain a deeper understanding of the impact of these measures. In this paper, we utilize an open mobility dataset called Community Mobility Report published by Google on the Internet and other external data sources (e.g., statistics on daily confirmed cases, demographics, etc.) to quantitatively characterize people’s collective responses and model it with a proposed metric called Lockdown Stringency Score (LSS) after the lockdown measures have been taken. Then, by investigating the correlations between LSS and the increase of new confirmed cases across different regions and countries in the world, we explore how people’s collective response in terms of mobility pattern changes affects the control of the virus. The analysis results show that lockdown and social distancing measures do have a positive impact on virus control, and the restriction on different types of Point-of-Interests (PoIs) has different weights (significance) in terms of virus control effectiveness. These results reveal important insights and implication on public health policy making, such as the phased start of the lockdown or reopen of the economy.

    Original languageEnglish
    Title of host publication2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC)
    EditorsW. K. Chan, Bill Claycomb, Hiroki Takakura, Ji-Jiang Yang, Yuuichi Teranishi, Dave Towey, Sergio Segura, Hossain Shahriar, Sorel Reisman, Sheikh Iqbal Ahamed
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages608-617
    Number of pages10
    ISBN (Electronic)9781665424639
    DOIs
    Publication statusPublished - Jul 2021
    Event45th IEEE Annual Computers, Software, and Applications Conference, - Virtual, Online, Spain
    Duration: 12 Jul 202116 Jul 2021
    Conference number: 45

    Publication series

    NameProceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021
    PublisherIEEE
    ISSN (Print)0730-3157

    Conference

    Conference45th IEEE Annual Computers, Software, and Applications Conference,
    Abbreviated titleCOMPSAC 2021
    Country/TerritorySpain
    CityVirtual, Online
    Period12/07/2116/07/21

    Bibliographical note

    © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    Funding Information:
    This work was supported by NSFC (National Natural Science Foundation of China) under Grant No. 61872010.

    Publisher Copyright:
    © 2021 IEEE.

    Keywords

    • COVID-19
    • Effectiveness
    • Lockdown
    • Mobility data

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Software

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