Lessons drawn from China and South Korea for managing COVID-19 epidemic: Insights from a comparative modeling study

ISA Trans. 2022 May:124:164-175. doi: 10.1016/j.isatra.2021.12.004. Epub 2021 Dec 28.

Abstract

We conducted a comparative study of the COVID-19 epidemic in three different settings: mainland China, the Guangdong province of China and South Korea, by formulating two disease transmission dynamics models which incorporate epidemic characteristics and setting-specific interventions, and fitting the models to multi-source data to identify initial and effective reproduction numbers and evaluate effectiveness of interventions. We estimated the initial basic reproduction number for South Korea, the Guangdong province and mainland China as 2.6 (95% confidence interval (CI): (2.5, 2.7)), 3.0 (95%CI: (2.6, 3.3)) and 3.8 (95%CI: (3.5,4.2)), respectively, given a serial interval with mean of 5 days with standard deviation of 3 days. We found that the effective reproduction number for the Guangdong province and mainland China has fallen below the threshold 1 since February 8th and 18th respectively, while the effective reproduction number for South Korea remains high until March 2nd Moreover our model-based analysis shows that the COVID-19 epidemics in South Korean is almost under control with the cumulative confirmed cases tending to be stable as of April 14th. Through sensitivity analysis, we show that a coherent and integrated approach with stringent public health interventions is the key to the success of containing the epidemic in China and especially its provinces outside its epicenter. In comparison, we find that the extremely high detection rate is the key factor determining the success in controlling the COVID-19 epidemics in South Korea. The experience of outbreak control in mainland China and South Korea should be a guiding reference for the rest of the world.

Keywords: COVID-19 epidemic; Comparative study; Mainland china and south korea; Mathematical model; Multi-source data.

MeSH terms

  • Basic Reproduction Number
  • COVID-19* / epidemiology
  • COVID-19* / prevention & control
  • China / epidemiology
  • Epidemics* / prevention & control
  • Humans
  • SARS-CoV-2