Using Mobile Data for Understanding Population Movement and Disease Transmission during Covid-19 Outbreak in the Nordics
Mansour, Osama LU ; Kajtazi, Miranda LU
and Ghazawneh, Ahmad
(2022)
55th Annual Hawaii International Conference on System Sciences, HICSS 2022
p.7151-7160
- 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... (More)
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.
(Less)
- author
- Mansour, Osama
LU
; Kajtazi, Miranda
LU
and Ghazawneh, Ahmad
- organization
- publishing date
- 2022
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022
- editor
- Bui, Tung X.
- pages
- 10 pages
- publisher
- IEEE Computer Society
- conference name
- 55th Annual Hawaii International Conference on System Sciences, HICSS 2022
- conference location
- Virtual, Online, United States
- conference dates
- 2022-01-03 - 2022-01-07
- external identifiers
-
- scopus:85152243408
- ISBN
- 9780998133157
- language
- English
- LU publication?
- yes
- id
- 534b1401-7184-4080-9e7a-b7e92945b004
- date added to LUP
- 2023-07-21 14:47:36
- date last changed
- 2023-09-12 15:07:19
@inproceedings{534b1401-7184-4080-9e7a-b7e92945b004,
abstract = {{<p>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.</p>}},
author = {{Mansour, Osama and Kajtazi, Miranda and Ghazawneh, Ahmad}},
booktitle = {{Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022}},
editor = {{Bui, Tung X.}},
isbn = {{9780998133157}},
language = {{eng}},
pages = {{7151--7160}},
publisher = {{IEEE Computer Society}},
title = {{Using Mobile Data for Understanding Population Movement and Disease Transmission during Covid-19 Outbreak in the Nordics}},
year = {{2022}},
}