Statistical Estimation of Effects of Implemented Government Policies on COVID-19 Situation in South Korea

Gyujin Heo, Catherine Apio, Kyulhee Han, Taewan Goo, Hye Won Chung, Taehyun Kim, Hakyong Kim, Yeonghyeon Ko, Doeun Lee, Jisun Lim and Taesung Park
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Gyujin Heo: Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea
Catherine Apio: Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea
Kyulhee Han: Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea
Taewan Goo: Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea
Hye Won Chung: Department of Chemistry, Seoul National University, Seoul 08826, Korea
Taehyun Kim: Department of Statistics, Seoul National University, Seoul 08826, Korea
Hakyong Kim: Department of Industrial Engineering, Seoul National University, Seoul 08826, Korea
Yeonghyeon Ko: Department of Statistics, Seoul National University, Seoul 08826, Korea
Doeun Lee: Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea
Jisun Lim: The Research Institute of Basic Sciences, Seoul National University, Seoul 08826, Korea
Taesung Park: Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea

IJERPH, 2021, vol. 18, issue 4, 1-11

Abstract: Since the outbreak of novel SARS-COV-2, each country has implemented diverse policies to mitigate and suppress the spread of the virus. However, no systematic evaluation of these policies in their alleviation of the pandemic has been done. We investigate the impact of five indices derived from 12 policies in the Oxford COVID-19 Government Response Tracker dataset and the Korean government’s index, which is the social distancing level implemented by the Korean government in response to the changing pandemic situation. We employed segmented Poisson model for this analysis. In conclusion, health and the Korean government indices are most consistently effective (with negative coefficients), while the restriction and stringency indexes are mainly effective with lagging (1~10 days), as intuitively daily confirmed cases of a given day is affected by the policies implemented days before, which shows that a period of time is required before the impact of some policies can be observed. The health index demonstrates the importance of public information campaign, testing policy and contact tracing, while the government index shows the importance of social distancing guidelines in mitigating the spread of the virus. These results imply the important roles of these polices in mitigation of the spread of COVID-19 disease.

Keywords: SARS-COV-2; COVID-19; pandemic; policies; indices; stringency index; lagging; segmented Poisson model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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