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• Epidemiologic features of the second and third waves of the coronavirus disease 2019 (COVID-19) pandemic in South Korea were compared. • Strengthening of social distancing policies was delayed in the third wave compared with the second wave. • The third wave persisted longer than the second wave, and had a higher case fatality rate. • Early public health intervention is important to control the COVID-19 pandemic. To compare epidemiologic features of the second and third waves of the coronavirus disease 2019 (COVID-19) pandemic in South Korea. Nationwide COVID-19 data were collected between 6 May and 30 December 2020. The degree of social activity was estimated using an Internet search trend analysis program for leisure-related keywords, including 'eating-out', 'trip' and 'get directions' (transportation). Demographics, transmission chains, case fatality rates, social activity levels and public health responses were compared between the second (13 August–18 September 2020) and third (4 November 2020–present) waves. In comparison with the second wave, the third wave was characterized by delayed strengthening of social distancing policies (3 vs. 15 days), longer duration (36 vs. >56 days) and a higher case fatality rate (0.91% vs. 1.26%). There were significant differences in transmission chains between the second and third waves (P < 0.01). In comparison with the second wave, the proportion of local clusters (24.8% vs. 45.7%) was lower in the third wave, and personal contact transmission (38.5% vs. 25.9%) and unknown routes of transmission (23.5% vs. 20.8%) were higher in the third wave. Early and timely interventions with strengthened social distancing policies should be implemented to suppress and control the COVID-19 pandemic effectively. [ABSTRACT FROM AUTHOR]

Social distancing is an effective measure to mitigate the spread of novel viral infections in the absence of antiviral agents and insufficient vaccine supplies. Subway utilization density may reflect social activity and the degree of social distancing in the general population.; This study aimed to evaluate the correlations between subway use density and the activity of the influenza epidemic or coronavirus disease 2019 (COVID-19) pandemic using a time-series regression method. The subway use-based social distancing score (S-SDS) was calculated using the weekly ridership of 11 major subway stations. The temporal association of S-SDS with influenza-like illness (ILI) rates or the COVID-19 pandemic activity was analyzed using structural vector autoregressive modeling and the Granger causality (GC) test. During three influenza seasons (2017–2020), the time-series regression presented a significant causality from S-SDS to ILI (p = 0.0484). During the COVID-19 pandemic in January 2020, S-SDS had been suppressed at a level similar to or below the average of the previous four years. In contrast to the ILI rate, there was a negative correlation between COVID-19 activity and S-SDS. GC analysis revealed a negative causal relationship between COVID-19 and S-SDS (p = 0.0098).; S-SDS showed a significant time-series association with the ILI rate but not with COVID-19 activity. When public transportation use is sufficiently suppressed, additional social mobility restrictions are unlikely to significantly affect COVID-19 pandemic activity. It would be more important to strengthen universal mask-wearing and detailed public health measures focused on risk activities, particularly in enclosed spaces. [ABSTRACT FROM AUTHOR]