hig.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Dynamics of COVID-19 progression and the long-term influences of measures on pandemic outcomes
Suntar Research Institute, Singapore, Singapore.
Karolinska institutet.
Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för elektroteknik, matematik och naturvetenskap, Matematik.
2022 (engelsk)Inngår i: Emerging Themes in Epidemiology, E-ISSN 1742-7622, Vol. 19, artikkel-id 10Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The pandemic progression is a dynamic process, in which measures yield outcomes, and outcomes in turn influence subsequent measures and outcomes. Due to the dynamics of pandemic progression, it is challenging to analyse the long-term influence of an individual measure in the sequence on pandemic outcomes. To demonstrate the problem and find solutions, in this article, we study the first wave of the pandemic—probably the most dynamic period—in the Nordic countries and analyse the influences of the Swedish measures relative to the measures adopted by its neighbouring countries on COVID-19 mortality, general mortality, COVID-19 incidence, and unemployment. The design is a longitudinal observational study. The linear regressions based on the Poisson distribution or the binomial distribution are employed for the analysis. To show that analysis can be timely conducted, we use table data available during the first wave. We found that the early Swedish measure had a long-term and significant causal effect on public health outcomes and a certain degree of long-term mitigating causal effect on unemployment during the first wave, where the effect was measured by an increase of these outcomes under the Swedish measures relative to the measures adopted by the other Nordic countries. This information from the first wave has not been provided by available analyses but could have played an important role in combating the second wave. In conclusion, analysis based on table data may provide timely information about the dynamic progression of a pandemic and the long-term influence of an individual measure in the sequence on pandemic outcomes.

sted, utgiver, år, opplag, sider
BMC , 2022. Vol. 19, artikkel-id 10
HSV kategori
Identifikatorer
URN: urn:nbn:se:hig:diva-40641DOI: 10.1186/s12982-022-00119-6ISI: 000901527600001PubMedID: 36550573Scopus ID: 2-s2.0-85144894966OAI: oai:DiVA.org:hig-40641DiVA, id: diva2:1722502
Forskningsfinansiär
Swedish Research Council, 2019-02913University of GävleTilgjengelig fra: 2022-12-29 Laget: 2022-12-29 Sist oppdatert: 2023-10-17bibliografisk kontrollert

Open Access i DiVA

fulltext(1206 kB)83 nedlastinger
Filinformasjon
Fil FULLTEXT01.pdfFilstørrelse 1206 kBChecksum SHA-512
3f3fb603f0fd0034e80c1b6a1032443278df82cffa3bd7fcc8c4dabaaace7d30ce87bd27610299f32c005f2bafe9a50d71b95b4ecad150bdf93b7eaa65dc8398
Type fulltextMimetype application/pdf

Andre lenker

Forlagets fulltekstPubMedScopus

Person

Wang, Xiaoqin

Søk i DiVA

Av forfatter/redaktør
Wang, Xiaoqin
Av organisasjonen
I samme tidsskrift
Emerging Themes in Epidemiology

Søk utenfor DiVA

GoogleGoogle Scholar
Totalt: 83 nedlastinger
Antall nedlastinger er summen av alle nedlastinger av alle fulltekster. Det kan for eksempel være tidligere versjoner som er ikke lenger tilgjengelige

doi
pubmed
urn-nbn

Altmetric

doi
pubmed
urn-nbn
Totalt: 331 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf