ArticleAnnals of medicine2021
A multi-stage SEIR(D) model of the COVID-19 epidemic in Korea.
Article in Annals of medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gauging the Impact of Artificial Intelligence and Mathematical Modeling in Response to the COVID-19 Pandemic: A Systematic Review.BioMed research international · 2022Pooled it
- Mathematical models to characterize the early phase of the COVID-19 pandemic in New Mexico, USA.Mathematical biosciences and engineering : MBE · 2025Article
- Integrating socio-psychological factors in the SEIR model optimized by a genetic algorithm for COVID-19 trend analysis.Scientific reports · 2024Article
- Immune Characteristic Genes and Neutrophil Immune Transformation Studies in Severe COVID-19.Microorganisms · 2024Article
- The relationship between compartment models and their stochastic counterparts: A comparative study with examples of the COVID-19 epidemic modeling.Journal of biomedical research · 2024Article
- Seesaw Effect Between COVID-19 and Influenza From 2020 to 2023 in World Health Organization Regions: Correlation Analysis.JMIR public health and surveillance · 2023Article
- Predicting the transmission dynamics of novel coronavirus infection in Shanxi province after the implementation of the "Class B infectious disease Class B management" policy.Frontiers in public health · 2023Article
- Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature.Yonsei medical journal · 2023Review
- Epidemiological characteristics and transmission dynamics of the COVID-19 outbreak in Hohhot, China: a time-varying SQEIAHR model analysis.Frontiers in public health · 2023Article
- Measuring the impact of social-distancing, testing, and undetected asymptomatic cases on the diffusion of COVID-19.PloS one · 2022Article
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Abstract
backgroundThis paper uses a SEIR(D) model to analyse the time-varying transmission dynamics of the COVID-19 epidemic in Korea throughout its multiple stages of development. This multi-stage estimation of the model parameters offers a better model fit compared to the whole period analysis and shows how the COVID-19's infection patterns change over time, primarily depending on the effectiveness of the public health authority's non-pharmaceutical interventions (NPIs).
methodsThis paper uses the SEIR(D) compartment model to simulate and estimate the parameters for three distinctive stages of the COVID-19 epidemic in Korea, using a manually compiled COVID-19 epidemic dataset for the period between 18 February 2020 and 08 February 2021. The paper identifies three major stages of the COVID-19 epidemic, conducts multi-stage estimations of the SEIR(D) model parameters, and carefully infers context-dependent meaning of the estimation results to help better understand the unique patterns of the transmission of the novel coronavirus (SARS-CoV-2) in each stage.
resultsThe original SIR compartment model may produce a poor and even misleading estimation result if it is used to cover the entire period of the epidemic. However, if we use the model carefully in distinctive stages of the COVID-19 epidemic, we can find useful insights into the nature of the transmission of the novel coronavirus and the relative effectiveness of the government's non-pharmaceutical interventions over time.Key messagesIdentifies three distinctive waves of the COVID-19 epidemic in Korea.Conducts multi-stage estimations of the COVID-19 transmission dynamics using SEIR(D) epidemic models.The transmission dynamics of the COVID-19 vary over time, primarily depending on the relative effectiveness of the government's non-pharmaceutical interventions (NPIs).The SEIR(D) epidemic model is useful and informative, but only when it is used carefully to account for the presence of multiple waves and context-dependent infection patterns in each wave.
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