Effective Control of COVID-19 in South Korea: Cross-Sectional Study of Epidemiological Data

Abstract

Background South Korea is one of the few countries that has succeeded in flattening the curve of new COVID-19 cases and avoiding a second outbreak by implementing multiple strategies, ranging from an individual level to the population level. Objective We aim to discuss the unique strategies and epidemiological characteristics of COVID-19 in South Korea and present a summary of policies implemented by the Korean government during the COVID-19 pandemic. Methods We designed a cross-sectional study of epidemiological data published by the Korea Centers for Disease Control and Prevention on October 1, 2020. We analyzed detailed epidemiological information of COVID-19 cases, including the number of confirmed cases and resulting deaths. Results As of October 1, 2020, a total of 23,889 confirmed COVID-19 cases and 415 deaths were reported in South Korea. In this paper, we present data on the epidemiological characteristics and transmission of the disease and discuss how the South Korean government, health care providers, and society responded to the COVID-19 outbreak. Conclusions Understanding the epidemiological characteristics of COVID-19 in South Korea and the government’s successful efforts in managing the spread of the disease can provide important insights to other countries dealing with the ongoing pandemic.

Using the IPcase Index with Inflection Points and the Corresponding Case Numbers to Identify the Impact Hit by COVID-19 in China: An Observation Study

“…The SACOVID variable can be measured by the core area under the CNICs until the IP days. The IP discussed in previous studies [ 9 , 10 , 11 , 12 , 13 ] verified the effective control of COVID-19. However, the applications and determination of the IP days on SACOVID were not described in detail (such as providing an MP4 video and the original data to illustrate the approach in a study).…”

“…The provinces of Yunnan, Sichuan, and Tianjin are the top three entities with the most aberrant patterns, with IP days of 5, 51, and 119, respectively, suggesting that the irregular response patterns are worthy of further investigation using person-fit statistics in reporting and analyzing data [ 51 , 52 , 53 ]. The most model-data-fit areas were Anhui, Hunan, and Henan, with IP days of 12, 11, and 12, respectively, including Hubei (and Wuhan) with 18 IP days, similar to South Korea, which has successfully maintained a flat infection curve [ 13 ]. However, the IP-determination scheme is scientifically and appropriately suitable as a test of effective control of COVID-19, compared to the eyeball method used in a previous study [ 13 ].…”

“…However, the applications and determination of the IP days on SACOVID were not described in detail (such as providing an MP4 video and the original data to illustrate the approach in a study). South Korea, for example, is one of the few countries in the world to have strongly maintained a flat infection curve for more than 50 days, but no such approach was proposed to determine the IP when extended to a further 50 days in the previous study [ 13 ].…”

“…Several researchers [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ] have proposed using mathematical models to predict the number of COVID-19 cases, and the others investigated the IP [ 9 , 10 , 11 , 12 , 13 ]. None of the researchers properly used the IP days to compare the SACOVID capabilities in the effective control of COVID-19 because of the difficulties in evaluating IP days [ 10 ].…”

A cross-country core strategy comparison in China, Japan, Singapore and South Korea during the early COVID-19 pandemic

“…Furthermore, to sample collection coupled with fast and aggressive testing, drive-through and walk-through screening stations were introduced for allowed early detection of confirmed cases in communities [ 11 ]. With these stations in place, even asymptomatic patients did not miss diagnosed, making Korea’s COVID-19 statistics more reliable [ 12 ]. In this way, Korea has substantially slowed down the spread of the virus.…”