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Countrywide population movement monitoring using mobile devices generated (big) data during the COVID-19 crisis.
Szocska, Miklos; Pollner, Peter; Schiszler, Istvan; Joo, Tamas; Palicz, Tamas; McKee, Martin; Asztalos, Aron; Bencze, Laszlo; Kapronczay, Mor; Petrecz, Peter; Toth, Benedek; Szabo, Adam; Weninger, Attila; Ader, Krisztian; Bacskai, Peter; Karaszi, Peter; Terplan, Gyozo; Tuboly, Gabor; Sohonyai, Adam; Szoke, Jozsef; Toth, Adam; Gaal, Peter.
  • Szocska M; Digital Health and Data Utilisation Team, Health Services Management Training Centre, Faculty of Health and Public Administration, Semmelweis University, Budapest, Hungary.
  • Pollner P; Digital Health and Data Utilisation Team, Health Services Management Training Centre, Faculty of Health and Public Administration, Semmelweis University, Budapest, Hungary.
  • Schiszler I; MTA-ELTE Statistical and Biological Physics Research Group, Eotvos Lorand Research Network (ELKH), Department of Biological Physics, Eotvos Lorand University, Budapest, Hungary.
  • Joo T; Digital Health and Data Utilisation Team, Health Services Management Training Centre, Faculty of Health and Public Administration, Semmelweis University, Budapest, Hungary.
  • Palicz T; Digital Health and Data Utilisation Team, Health Services Management Training Centre, Faculty of Health and Public Administration, Semmelweis University, Budapest, Hungary.
  • McKee M; Hungarian Health Management Association, Budapest, Hungary.
  • Asztalos A; Digital Health and Data Utilisation Team, Health Services Management Training Centre, Faculty of Health and Public Administration, Semmelweis University, Budapest, Hungary.
  • Bencze L; Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom.
  • Kapronczay M; Magyar Telekom Nyrt, Budapest, Hungary.
  • Petrecz P; Magyar Telekom Nyrt, Budapest, Hungary.
  • Toth B; Magyar Telekom Nyrt, Budapest, Hungary.
  • Szabo A; Magyar Telekom Nyrt, Budapest, Hungary.
  • Weninger A; Magyar Telekom Nyrt, Budapest, Hungary.
  • Ader K; Magyar Telekom Nyrt, Budapest, Hungary.
  • Bacskai P; Magyar Telekom Nyrt, Budapest, Hungary.
  • Karaszi P; Telenor Magyarorszag Zrt, Budapest, Hungary.
  • Terplan G; Telenor Magyarorszag Zrt, Budapest, Hungary.
  • Tuboly G; Telenor Magyarorszag Zrt, Budapest, Hungary.
  • Sohonyai A; Telenor Magyarorszag Zrt, Budapest, Hungary.
  • Szoke J; Telenor Magyarorszag Zrt, Budapest, Hungary.
  • Toth A; Vodafone Hungary, Budapest, Hungary.
  • Gaal P; Vodafone Hungary, Budapest, Hungary.
Sci Rep ; 11(1): 5943, 2021 03 15.
Article in English | MEDLINE | ID: covidwho-1135693
ABSTRACT
Mobile phones have been used to monitor mobility changes during the COVID-19 pandemic but surprisingly few studies addressed in detail the implementation of practical applications involving whole populations. We report a method of generating a "mobility-index" and a "stay-at-home/resting-index" based on aggregated anonymous Call Detail Records of almost all subscribers in Hungary, which tracks all phones, examining their strengths and weaknesses, comparing it with Community Mobility Reports from Google, limited to smartphone data. The impact of policy changes, such as school closures, could be identified with sufficient granularity to capture a rush to shops prior to imposition of restrictions. Anecdotal reports of large scale movement of Hungarians to holiday homes were confirmed. At the national level, our results correlated well with Google mobility data, but there were some differences at weekends and national holidays, which can be explained by methodological differences. Mobile phones offer a means to analyse population movement but there are several technical and privacy issues. Overcoming these, our method is a practical and inexpensive way forward, achieving high levels of accuracy and resolution, especially where uptake of smartphones is modest, although it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Mobility / Computers, Handheld / Big Data / SARS-CoV-2 / COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Europa Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-81873-6

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Mobility / Computers, Handheld / Big Data / SARS-CoV-2 / COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Europa Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-81873-6