Development of New Stringency Indices for Nonpharmacological Social Distancing Policies Implemented in Korea During the COVID-19 Pandemic: Random Forest Approach

Abstract

Background In the absence of an effective treatment method or vaccine, the outbreak of the COVID-19 pandemic elicited a wide range of unprecedented restriction policies aimed at mitigating and suppressing the spread of the SARS-CoV-2 virus. These policies and their Stringency Index (SI) of more than 160 countries were systematically recorded in the Oxford COVID-19 Government Response Tracker (OxCGRT) data set. The SI is a summary measure of the overall strictness of these policies. However, the OxCGRT SI may not fully reflect the stringency levels of the restriction policies implemented in Korea. Korea implemented 33 COVID-19 restriction policies targeting 4 areas: public facilities, public events, social gatherings, and religious gatherings. Objective This study aims to develop new Korea Stringency Indices (KSIs) that reflect the stringency levels of Korea’s restriction policies better and to determine which government-implemented policies were most effective in managing the COVID-19 pandemic in Korea. Methods The random forest method was used to calculate the new KSIs using feature importance values and determine their effectiveness in managing daily COVID-19 confirmed cases. Five analysis periods were considered, including November 01, 2020, to January 20, 2021 (Period 1), January 20, 2021, to June 27, 2021 (Period 2), November 01, 2020, to June 27, 2021 (Period 3), June 27, 2021, to November 01, 2021 (Period 4), and November 01, 2021, to April 24, 2022 (Period 5). Results Among the KSIs, public facilities in period 4, public events in period 2, religious gatherings in periods 1 and 3, and social gatherings in period 5 had the highest importance. Among the public facilities, policies associated with operation hour restrictions in cinemas, restaurants, PC rooms, indoor sports facilities, karaoke, coffee shops, night entertainment facilities, and baths or saunas had the highest importance across all analysis periods. Strong positive correlations were observed between daily confirmed cases and public facilities, religious gatherings, and public events in period 1 of the pandemic. From then, weaker and negative correlations were observed in the remaining analysis periods. The comparison with the OxCGRT SI showed that the SI had a relatively lower feature importance and correlation with daily confirmed cases than the proposed KSIs, making KSIs more effective than SI. Conclusions Restriction policies targeting public facilities were the most effective among the policies analyzed. In addition, different periods call for the enforcement of different policies given their effectiveness varies during the pandemic.

Forecasting the spread of COVID-19 based on policy, vaccination, and Omicron data

“…Differing from previous studies, SI, VR, and OR were used as predictor variables. These variables were rarely considered in forecasting studies, despite their evidence that they are related to the epidemic trend 31 – 33 . In addition, to the best of our knowledge no study has simultaneously analyzed both the effects of prediction models and predictor variables across multiple regions.…”

K-Track-Covid: interactive web-based dashboard for analyzing geographical and temporal spread of COVID-19 in South Korea

“…This extension will enable a comprehensive analysis of disease spread and containment strategies across diverse geographic and demographic contexts. Moreover, by integrating real patient data with the enactment of regional policies, mainly through metrics like the Korea Stringency Index (KSI) (30), the dashboard can provide detailed insights into the effectiveness of various public health strategies. Such analysis is pivotal for refining pandemic preparedness and response, enabling the development of targeted, evidence-based policies.…”