中文版 | English
Title

Modelling the Mobility Changes Caused by Perceived Risk and Policy Efficiency

Author
Corresponding AuthorYang, Lili
Publication Years
2022-08-01
DOI
Source Title
EISSN
2220-9964
Volume11Issue:8
Abstract
In many countries, governments have implemented non-pharmaceutical techniques to limit COVID-19 transmission. Restricting human mobility is one of the most common interventions, including lockdown, travel restrictions, working from home, etc. However, due to the strong transmission ability of the virus variants, further rounds of interventions, including a strict lockdown, are not considered as effective as expected. The paper aims to understand how the lockdown policy and pandemics changed human mobility in the real scenario. Here we focus on understanding the mobility changes caused by compliance with restrictions and risk perceptions, using a mobility index from the Google report during three strict lockdown periods in Leeds, the largest city in the county of West Yorkshire, England, from March 2020 to March 2021. The research uses time-varying z-scores and Principal Component Analysis (PCA) to simulate how local people dynamically process and perceive health risks based on multi-dimensional daily COVID-19 reports first. Further modelling highlights exponentially increasing policy non-compliance through the duration of lockdown, probably attributable to factors such as mental anxiety and economic pressures. Finally, the proposed nonlinear regression model examines the mobility changes caused by the population's dynamic risk perceptions and lockdown duration. The case study model in Leeds shows a good fit to the empirical mobility data and indicates that the third lockdown policy took effect much slower than the first. At the same time, the negative impact of the epidemic on population mobility decayed by 40% in the third lockdown period in contrast with the first lockdown. The risk perception estimation methods could reflect that the local population became increasingly accustomed to the COVID-19 situation, and local people rationally evaluated the risks of COVID in the third lockdown period. The results demonstrate that simulated risk perceptions and policy decay could explain urban mobility behaviour during lockdown periods, which could be a reference for future decision-making processes.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
First ; Corresponding
Funding Project
Shenzhen Science and Technology Special Project of the Epidemic[JSGG20220301090202005]
WOS Research Area
Computer Science ; Physical Geography ; Remote Sensing
WOS Subject
Computer Science, Information Systems ; Geography, Physical ; Remote Sensing
WOS Accession No
WOS:000845690600001
Publisher
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/394104
DepartmentDepartment of Statistics and Data Science
Affiliation
1.Southern Univ Sci & Technol, Dept Stat & Data Sci, Shenzhen 518055, Peoples R China
2.Univ Leeds, Inst Transport Studies, Leeds LS2 9JT, W Yorkshire, England
First Author AffilicationDepartment of Statistics and Data Science
Corresponding Author AffilicationDepartment of Statistics and Data Science
First Author's First AffilicationDepartment of Statistics and Data Science
Recommended Citation
GB/T 7714
Wu, Sijin,Grant-Muller, Susan,Yang, Lili. Modelling the Mobility Changes Caused by Perceived Risk and Policy Efficiency[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2022,11(8).
APA
Wu, Sijin,Grant-Muller, Susan,&Yang, Lili.(2022).Modelling the Mobility Changes Caused by Perceived Risk and Policy Efficiency.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,11(8).
MLA
Wu, Sijin,et al."Modelling the Mobility Changes Caused by Perceived Risk and Policy Efficiency".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 11.8(2022).
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