Using Mobile Data for Understanding Population Movement and Disease Transmission during Covid-19 Outbreak in the Nordics

Osama Mansour, Miranda Kajtazi, Ahmad Ghazawneh

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

Abstract

This study investigates the use of mobile data to understand patterns of population movements and disease transmission during the Covid-19 outbreak. It also focuses on understanding the implications of using this data for individual privacy. Using a mixed methods approach, we present 10 rich qualitative interviews and 412 survey responses from participants across the Nordics. Our novel results show that the use of mobile data can be characterized by two main categories: validation data and complementary data. We also identify five implications for practice: sharing resources and expertise between health agencies and telecom companies; extended collaboration with multiple network operators; cross-disciplinary collaboration among multiple parties; developing data and privacy guidelines; and developing novel methods and tools to address the trade-off between maintaining individual privacy and obtaining detailed information from mobile data. These implications may inform immediate and future actions to prepare for, mitigate, and control the spread of infectious diseases using mobile data. They also show privacy-driven limitations of mobile data in terms of data accuracy, richness, and scope.

Original languageEnglish
Title of host publicationProceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages7151-7160
Number of pages10
ISBN (Electronic)9780998133157
Publication statusPublished - 2022
Event55th Annual Hawaii International Conference on System Sciences, HICSS 2022 - Virtual, Online, United States
Duration: 2022 Jan 32022 Jan 7

Conference

Conference55th Annual Hawaii International Conference on System Sciences, HICSS 2022
Country/TerritoryUnited States
CityVirtual, Online
Period2022/01/032022/01/07

Subject classification (UKÄ)

  • Computer Science

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