Korea’s Early Covid-19 Response
Findings and Implications
Bibliographic Data
| ID | 15470414 |
|---|---|
| Authors | Shin-Kue Ryu (0000-0002-6687-4566, Idaho State University), Soon-Gwan Chung (Sunchon National University, corresponding author) |
| Year | 2021 |
| Volume | 18 |
| Issue | 16 |
| Pages | 8316-8316 |
| Publication date | 2021-08-05 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph18168316 |
| PMID | 34444066 |
| OpenAlex | W3187250343 |
| Language | EN |
| Citations received | 3 |
| References cited | 24 |
South Korea was a hotspot of the COVID-19 pandemic with confirmed infections quickly surpassing 10,000 people. However, the country quickly responded and contained additional infections with minimal costs of lives. Hence, the question, "what did they do differently?" Building on empirical fingerprints from over 1507 pages of South Korean government press briefings on their public sector response between 31 January 2020 and 1 July 2020, we capture the sufficiency-based mechanism in operation with two key findings. First, mechanisms matter in pandemic containment, i.e., sequence, complementary activities, and systematic settings are consequential to the witnessed outcome. Second, central government-led efforts were effective and in parts necessary to deal with invisible and rapidly spreading infections beyond a single jurisdictional boundary. These findings lead to a timely discussion on whether pandemics should be treated in the same scholarly limelight as other natural disasters
2019-20 coronavirus outbreak · Coronavirus disease 2019 (COVID-19 · Development economics · Economic growth · Economics · Geography · Government (linguistics · Limelight · Natural disaster · Outbreak · Pandemic · Political science · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Disaster Management and Resilience · Engineering · Medicine · Virology
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| Citations per year | 0.75 |
|---|---|
| Citation span | 2022 - 2025 (4) |
| Highly cited | No |