3.8 Article

Dynamics of COVID-19 progression and the long-term influences of measures on pandemic outcomes

Journal

EMERGING THEMES IN EPIDEMIOLOGY
Volume 19, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12982-022-00119-6

Keywords

-

Funding

  1. Swedish Research Council
  2. [2019-02913]

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This article analyzes the long-term influence of Swedish measures on COVID-19 and public health outcomes during the first wave of the pandemic in the Nordic countries. The study finds that Swedish measures had a significant causal effect on public health outcomes and mitigated unemployment to some extent during the first wave. This information could have played a crucial role in combating the second wave.
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.

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