Here, evidence refers to data and data analysis data is observational as typical of a pandemic data analysis compares different measures for public health and economic outcomes, and it can be mathematical, descriptive, or statistical. Notably, this statement is in line with the general framework of Epidemiology and Evidence-Based Medicine. As repeatedly stated by the Swedish public health agency, the de facto administrator for handling the pandemic, the decision-making was based on evidence ( Irwin, 2020 Lindström, 2020, 2021 Sayers 2020) see also CNN interview on 17 April with the former state epidemiologist Johan Giesecke (1995–2005) ( CNN, 2020). The two periods represent two waves of the pandemic progression in the Nordic countries, each completing a cycle of rising, plateau, and decline and base for public health outcomes such as COVID-19 deaths.Ī major controversy about the Swedish strategy of dealing with COVID-19 concerns how the decision-making was made. During the early period of the pandemic, the two strategies led to obvious different results for instance, the COVID-19 mortality per 100,000 individuals in Sweden versus the other Nordic countries is 58.15 versus 7.34 between March 2020 and August 2020 and 69.71 versus 13.40 between September 2020 and February 2021. On the other hand, the other Nordic countries, i.e., Denmark, Finland, and Norway, were representative of the common strategies, emphasizing the suppression of transmission and taking invasive measures ( Erica, 2021 Lindström, 2020, 2021). Sweden was representative of those strategies, emphasizing the mitigation of transmission and taking stepwise mild measures ( Erica, 2021 Kavaliunas, Ocaya, Mumper, Lindfeldt, & Kyhlstedt, 2020 Ludvigsson, 2020). Since the World Health Organization declared the coronavirus disease 2019 (COVID-19) as a pandemic on 11 March 2020, countries around the globe have adopted different strategies of combating the transmission of COVID-19 while alleviating its negative impact on public health and the economy. In conclusion, a timely longitudinal analysis should be part of the decision-making process for containing the current pandemic or a future one. These pieces of statistical evidence were not studied in the mathematical and descriptive analyses but could play an important role in the decision-making at the second wave. We found that the early Swedish measure had a long-term and significant effect on general mortality and COVID-19 mortality and a certain mitigating effect on unemployment in Sweden during the first wave here, the effect was measured by an increase of general deaths, COVID-19 deaths or unemployed persons under Swedish measure relative to the measures adopted by the other Nordic countries. The linear regressions based on the Poisson distribution and the binomial distribution are employed for the analysis. The design is longitudinal observational study. In this article, using data available during the first wave, we conduct longitudinal analysis to investigate the consequence of the shred of evidence in the Swedish decision-making for the first wave, where the study period is between January 2020 and August 2020. Due to the dubious interpretations of these analyses, a mild measure was adopted in Sweden upon the arrival of the second wave, leading to a surge of poor public health outcomes compared to the other Nordic countries (Denmark, Norway, and Finland). The mathematical analysis aimed to model the condition for herd immunity while the descriptive analysis compared different measures without adjustment of population differences and updating pandemic situations. However, when more data became available, the decision-making stood on mathematical and descriptive analyses. During the earliest period of the pandemic, the Swedish decision-making was based on subjective perspective. A controversy about the Swedish strategy of dealing with COVID-19 during the early period is how decision-making was based on evidence, which refers to data and data analysis.
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