Citizen mobility and the growth of infections during the COVID-19 pandemic with the effects of government restrictions in Western Europe

Sarim, M., Zhao, Q. and Bailey, N. (2021) Citizen mobility and the growth of infections during the COVID-19 pandemic with the effects of government restrictions in Western Europe. In: Shaw, S.-L. and Sui, D. (eds.) Mapping COVID-19 in Space and Time: Understanding the Spatial and Temporal Dynamics of a Global Pandemic. Series: Human dynamics in smart cities. Springer: Cham, pp. 279-294. ISBN 9783030728076 (doi: 10.1007/978-3-030-72808-3_14)

Abstract

Mobility restrictions have been imposed by many countries in order to curb the spread the novel coronavirus disease. These vary in overall severity but also in the details of which kinds of activity and hence mobility has been permitted or restricted. This study uses the Oxford COVID-19 Government Response Tracker to measure the severity of restrictions on mobility in eight Western European countries but adds additional understanding on the nature of restrictions by combining this with mobility data from Google on different activities. The countries were classified into three categories based on the observed changes in mobility patterns, reflecting differences in the approach rather than severity. The paper then assesses the relationships between mobility patterns and the spread of the virus by looking at the growth rate ratio. The time lag for the highest correlation was observed to be in the range of 14–20 days in most cases. In some countries, however, there is no correlation between mobility in parks and spread of disease, suggesting this activity is relatively safe with appropriate social distancing. These findings support the use of social distancing measures in order to limit the spread of COVID-19 and could also be helpful in case of any future outbreaks of similar infectious diseases.

• Item Type: Book Sections
• Keywords: SARS-CoV-2, growth of infections, Google community mobility reports, government restrictions.
• Status: Published
• Glasgow Author(s) Enlighten ID: Zhao, Dr Qunshan and Bailey, Professor Nick
• Authors: Sarim, M., Zhao, Q., and Bailey, N.
• College/School: College of Social Sciences > School of Social and Political Sciences > Urban Studies
• Publisher: Springer
• ISBN: 9783030728076
• Published Online: 15 July 2021
• Copyright Holders: Copyright © 2021 The Authors
• First Published: First published in Mapping COVID-19 in Space and Time: Understanding the Spatial and Temporal Dynamics of a Global Pandemic: 279-294
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
190698		Urban Big Data Research Centre	Nick Bailey	Economic and Social Research Council (ESRC)	ES/L011921/1	S&PS - Urban Big Data
304042		UBDC Centre Transition	Nick Bailey	Economic and Social Research Council (ESRC)	ES/S007105/1	S&PS - Administration