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A Three-Stage Periodic Model: An Initial Analysis of Government Preventive Measures against COVID-19 Epidemics
Dalarna University, School of Technology and Business Studies, Information Systems.
Dalarna University, School of Technology and Business Studies, Information Systems.ORCID iD: 0000-0003-4812-4988
Dalarna University, School of Technology and Business Studies, Information Systems.ORCID iD: 0000-0003-3681-8173
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2020 (English)In: ACM International Conference Proceeding Series, ACM Digital Library, 2020, p. 26-31Conference paper, Published paper (Refereed)
Abstract [en]

In early spring 2020, Covid-19 was categorized as a pandemic and has since infected several millions of people in many countries and claimed hundreds of thousands of lives. Various strict strategies and prevention measures, such as curfews and lockdowns of cities or entire countries, have been enforced by governments to mitigate the spread of the virus. While the results of the aforementioned enforced measures deemed promising for some countries, the same could not be said about others. This paper serves as an initial analysis of the effect of government enforced strategies and safety measures on the transmission of Covid-19. We propose a three-stage periodic model: The rise stage, plateau stage, and decline stage, to describe the changes of the spread of Covid-19. The results show a positive and constructive answer to our proposed three-stage model. © 2020 ACM.

Place, publisher, year, edition, pages
ACM Digital Library, 2020. p. 26-31
Keywords [en]
Big Data Analysis, Classifier, COVID-19 epidemic, Curve fitting, Big data, Viruses, Periodic models, Prevention measures, Preventive measures, Safety measures, Stage models, Public policy
National Category
Computer and Information Sciences
Research subject
Research Profiles 2009-2020, Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-35502DOI: 10.1145/3422713.3422744Scopus ID: 2-s2.0-85095864410ISBN: 9781450387859 (print)OAI: oai:DiVA.org:du-35502DiVA, id: diva2:1504301
Conference
3rd International Conference on Big Data Technologies, ICBDT 2020, 18 September 2020 through 20 September 2020
Available from: 2020-11-27 Created: 2020-11-27 Last updated: 2021-11-12Bibliographically approved

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Barakat, SerenaNyberg, Roger G.Song, William Wei

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf