---
_id: '9253'
abstract:
- lang: eng
  text: In March 2020, the Austrian government introduced a widespread lock-down in
    response to the COVID-19 pandemic. Based on subjective impressions and anecdotal
    evidence, Austrian public and private life came to a sudden halt. Here we assess
    the effect of the lock-down quantitatively for all regions in Austria and present
    an analysis of daily changes of human mobility throughout Austria using near-real-time
    anonymized mobile phone data. We describe an efficient data aggregation pipeline
    and analyze the mobility by quantifying mobile-phone traffic at specific point
    of interests (POIs), analyzing individual trajectories and investigating the cluster
    structure of the origin-destination graph. We found a reduction of commuters at
    Viennese metro stations of over 80% and the number of devices with a radius of
    gyration of less than 500 m almost doubled. The results of studying crowd-movement
    behavior highlight considerable changes in the structure of mobility networks,
    revealed by a higher modularity and an increase from 12 to 20 detected communities.
    We demonstrate the relevance of mobility data for epidemiological studies by showing
    a significant correlation of the outflow from the town of Ischgl (an early COVID-19
    hotspot) and the reported COVID-19 cases with an 8-day time lag. This research
    indicates that mobile phone usage data permits the moment-by-moment quantification
    of mobility behavior for a whole country. We emphasize the need to improve the
    availability of such data in anonymized form to empower rapid response to combat
    COVID-19 and future pandemics.
article_processing_charge: No
arxiv: 1
author:
- first_name: Georg
  full_name: Heiler, Georg
  last_name: Heiler
- first_name: Tobias
  full_name: Reisch, Tobias
  last_name: Reisch
- first_name: Jan
  full_name: Hurt, Jan
  last_name: Hurt
- first_name: Mohammad
  full_name: Forghani, Mohammad
  last_name: Forghani
- first_name: Aida
  full_name: Omani, Aida
  last_name: Omani
- first_name: Allan
  full_name: Hanbury, Allan
  last_name: Hanbury
- first_name: Farid
  full_name: Karimipour, Farid
  id: 2A2BCDC4-CF62-11E9-BE5E-3B1EE6697425
  last_name: Karimipour
  orcid: 0000-0001-6746-4174
citation:
  ama: 'Heiler G, Reisch T, Hurt J, et al. Country-wide mobility changes observed
    using mobile phone data during COVID-19 pandemic. In: <i>2020 IEEE International
    Conference on Big Data</i>. IEEE; 2021:3123-3132. doi:<a href="https://doi.org/10.1109/bigdata50022.2020.9378374">10.1109/bigdata50022.2020.9378374</a>'
  apa: 'Heiler, G., Reisch, T., Hurt, J., Forghani, M., Omani, A., Hanbury, A., &#38;
    Karimipour, F. (2021). Country-wide mobility changes observed using mobile phone
    data during COVID-19 pandemic. In <i>2020 IEEE International Conference on Big
    Data</i> (pp. 3123–3132). Atlanta, GA, United States: IEEE. <a href="https://doi.org/10.1109/bigdata50022.2020.9378374">https://doi.org/10.1109/bigdata50022.2020.9378374</a>'
  chicago: Heiler, Georg, Tobias Reisch, Jan Hurt, Mohammad Forghani, Aida Omani,
    Allan Hanbury, and Farid Karimipour. “Country-Wide Mobility Changes Observed Using
    Mobile Phone Data during COVID-19 Pandemic.” In <i>2020 IEEE International Conference
    on Big Data</i>, 3123–32. IEEE, 2021. <a href="https://doi.org/10.1109/bigdata50022.2020.9378374">https://doi.org/10.1109/bigdata50022.2020.9378374</a>.
  ieee: G. Heiler <i>et al.</i>, “Country-wide mobility changes observed using mobile
    phone data during COVID-19 pandemic,” in <i>2020 IEEE International Conference
    on Big Data</i>, Atlanta, GA, United States, 2021, pp. 3123–3132.
  ista: 'Heiler G, Reisch T, Hurt J, Forghani M, Omani A, Hanbury A, Karimipour F.
    2021. Country-wide mobility changes observed using mobile phone data during COVID-19
    pandemic. 2020 IEEE International Conference on Big Data. Big Data: International
    Conference on Big Data, 3123–3132.'
  mla: Heiler, Georg, et al. “Country-Wide Mobility Changes Observed Using Mobile
    Phone Data during COVID-19 Pandemic.” <i>2020 IEEE International Conference on
    Big Data</i>, IEEE, 2021, pp. 3123–32, doi:<a href="https://doi.org/10.1109/bigdata50022.2020.9378374">10.1109/bigdata50022.2020.9378374</a>.
  short: G. Heiler, T. Reisch, J. Hurt, M. Forghani, A. Omani, A. Hanbury, F. Karimipour,
    in:, 2020 IEEE International Conference on Big Data, IEEE, 2021, pp. 3123–3132.
conference:
  end_date: 2020-12-13
  location: Atlanta, GA, United States
  name: 'Big Data: International Conference on Big Data'
  start_date: 2020-12-10
date_created: 2021-03-21T11:34:07Z
date_published: 2021-03-19T00:00:00Z
date_updated: 2023-08-07T14:00:13Z
day: '19'
department:
- _id: HeEd
doi: 10.1109/bigdata50022.2020.9378374
external_id:
  arxiv:
  - '2008.10064'
  isi:
  - '000662554703032'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2008.10064
month: '03'
oa: 1
oa_version: Preprint
page: 3123-3132
publication: 2020 IEEE International Conference on Big Data
publication_identifier:
  isbn:
  - '9781728162515'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Country-wide mobility changes observed using mobile phone data during COVID-19
  pandemic
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2021'
...