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Assessment of Social Distancing for Controlling COVID-19 in Korea: An Age-Structured Modeling Approach

Yongin Choi, James Slghee Kim, Heejin Choi, Hyojung Lee and Chang Hyeong Lee
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Yongin Choi: Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
James Slghee Kim: Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
Heejin Choi: Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
Hyojung Lee: Busan Center for Medical Mathematics, National Institute of Mathematical Sciences, Daejeon 34047, Korea
Chang Hyeong Lee: Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea

IJERPH, 2020, vol. 17, issue 20, 1-16

Abstract: The outbreak of the novel coronavirus disease 2019 (COVID-19) occurred all over the world between 2019 and 2020. The first case of COVID-19 was reported in December 2019 in Wuhan, China. Since then, there have been more than 21 million incidences and 761 thousand casualties worldwide as of 16 August 2020. One of the epidemiological characteristics of COVID-19 is that its symptoms and fatality rates vary with the ages of the infected individuals. This study aims at assessing the impact of social distancing on the reduction of COVID-19 infected cases by constructing a mathematical model and using epidemiological data of incidences in Korea. We developed an age-structured mathematical model for describing the age-dependent dynamics of the spread of COVID-19 in Korea. We estimated the model parameters and computed the reproduction number using the actual epidemiological data reported from 1 February to 15 June 2020. We then divided the data into seven distinct periods depending on the intensity of social distancing implemented by the Korean government. By using a contact matrix to describe the contact patterns between ages, we investigated the potential effect of social distancing under various scenarios. We discovered that when the intensity of social distancing is reduced, the number of COVID-19 cases increases; the number of incidences among the age groups of people 60 and above increases significantly more than that of the age groups below the age of 60. This significant increase among the elderly groups poses a severe threat to public health because the incidence of severe cases and fatality rates of the elderly group are much higher than those of the younger groups. Therefore, it is necessary to maintain strict social distancing rules to reduce infected cases.

Keywords: COVID-19; mathematical modeling; age-structured model; social distancing; transmission rate; contact matrix (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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