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Evaluating the efficiency of the Swedish government policies to control the spread of Covid-19.
Dalarna University, School of Technology and Business Studies, Microdata Analysis.
Dalarna University, School of Technology and Business Studies, Microdata Analysis.
2020 (English)Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Different public health interventions such as social distancing, quarantine, use of masks in a public place, airport, and public transport restriction, closing of school, college, and shops, or even city lockdown were implemented around the world to control the spread of the highly transmissible virus ‘‘SARS-CoV-2’’, which is responsible for the current pandemic of Covid-19 disease. Like other countries, Sweden also introduced policies like banning public gatherings, commencing distance learning, keeping social distance in public places, suspending flights to and from different countries, closing religious places, banning visits to elderly homes, and many more. This paper examines if such action or recommendations are effective in controlling the spread of Covid-19 disease.The efficiency of these policies at each county in Sweden was evaluated and the effect of temperature on Covid-19 was analyzed using the data from the last week of December 2019 to the last week of September 2020. The statistical inferences were drawn from the multivariate time series model (hhh4) in R. Similarly, QGIS and ggplot2 library in R were used for descriptive analysis.Among all the studied policies, banning the crowd on restaurants and bars, and restricting the number of people for demonstration in Sweden were the most effective methods to reduce the rate of disease spread in almost all the counties. The number of ICU and death cases were low during high temperature in Sweden. The outcome of this study can be useful to implement health policies to manage similar disease outbreaks in the future.

Place, publisher, year, edition, pages
2020.
Keywords [en]
Covid-19, public health intervention, hhh4 model, efficiency.
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:du-35946OAI: oai:DiVA.org:du-35946DiVA, id: diva2:1525218
Available from: 2021-02-03 Created: 2021-02-03 Last updated: 2025-10-09

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CiteExportLink to record
Permanent link

Direct link
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