ArticleJournal of Korean medical science2020
Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020.
Article in Journal of Korean medical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature.Yonsei medical journal · 2023Review
- Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea.International journal of environmental research and public health · 2021Article
- Year-Long Trend in Glycated Hemoglobin Levels in Patients with Type 2 Diabetes during the COVID-19 Pandemic.Endocrinology and metabolism (Seoul, Korea) · 2021Article
- Risk Assessment of Importation and Local Transmission of COVID-19 in South Korea: Statistical Modeling Approach.JMIR public health and surveillance · 2021Article
- Towards Telemedicine Adoption in Korea: 10 Practical Recommendations for Physicians.Journal of Korean medical science · 2021Review
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3 authors.
Funding
Abstract
backgroundThe novel coronavirus (coronavirus disease 2019 [COVID-19]) outbreak began in China in December last year, and confirmed cases began occurring in Korea in mid-February 2020. Since the end of February, the rate of infection has increased greatly due to mass (herd) infection within religious groups and nursing homes in the Daegu and Gyeongbuk regions. This mass infection has increased the number of infected people more rapidly than was initially expected; the epidemic model based on existing studies had predicted a much lower infection rate and faster recovery.
methodsThe present study evaluated rapid infection spread by mass infection in Korea and the high mortality rate for the elderly and those with underlying diseases through the Susceptible-Exposed-Infected-Recovered-Dead (SEIRD) model.
resultsThe present study demonstrated early infection peak occurrence (-6.3 days for Daegu and -5.3 days for Gyeongbuk) and slow recovery trend (= -1,486.6 persons for Daegu and -223.7 persons for Gyeongbuk) between the actual and the epidemic model for a mass infection region compared to a normal infection region.
conclusionThe analysis of the time difference between infection and recovery can help predict the epidemic peak due to mass (or normal) infection and can also be used as a time index to prepare medical resources.
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