A modeling study of the effect of social distancing policies on the early spread of coronavirus disease 2019: a case of South Korea

Abstract

The social distancing policy is an effective way to prevent the spread of infectious diseases in the initial phase of their outbreak when medical evidence to support a particular course of treatment is deficient. While studies on the coronavirus disease 2019 (COVID-19) have mainly focused on the effects of specific measures (e.g., school and workplace closures and restrictions on movement), few investigated the characteristics of epidemic trends in response to the intensity of the policy and the amount of time required for policy measures to take effect. This study employs the SIRD (susceptible, infected, recovered, and deceased) model to analyze the COVID-19 epidemic trend according to the intensity of the social distancing policy in South Korea. The model reveals that the reproduction number began at 5.58 and fluctuated between 0.14 and 1.72 during the study period in accordance with different policy intensities. At the beginning of the social distancing policy, restrictions on public facility use were likely to have been effective in preventing the spread of COVID-19. When the intervention was relaxed, the transmission potential increased significantly. According to the reproduction number, social distancing policies prove to be effective after 13-19 days of implementation; however, as the pandemic progressed, this period extended from 13-14 to 18-19 days for the same effect. This suggests that governments need to consider not only the intensity of the social distancing policy, but also people's low responsiveness as the pandemic remains prevalent over time. It is also recommended they take preemptive action to ensure sufficient time for the policy to achieve its stated goal.

Keywords: C63; I18; Z18.

Fig. 1

Spread of COVID-19 and adaptive social distancing policies. Note The color intensity shows policy strength (Levels 1–5) at each phase (Phases 1–5)

Fig. 2

Analytical process

Fig. 3

COVID-19 S-R trend

Fig. 4

Social distancing policy phases and epidemic trend. Note The policy strength (Levels 1–5) at each phase (Phases 1–5) and epidemic trends (0–7th) are differentiated by the color intensity

Fig. 5

COVID-19 prediction trends for infected cases. Note The policy strength (Levels 1–5) at each phase (Phases 1–5) and epidemic trends (0–7th) are differentiated by the color intensity