ABSTRACT
[This corrects the article DOI: 10.1093/ofid/ofab350.].
ABSTRACT
OBJECTIVES: To analyze the relationship between traffic inflow and COVID-19 prevalence in South Korea for formulating prevention policies for novel infections. METHODS: We evaluated traffic inflow and new COVID-19 cases in 8 regions of Korea from January 1, 2020, to January 31, 2021. The toll collection system (TCS) traffic volume for 2019-2020 and traffic inflow trends were analyzed using independent samples t-test and nonlinear regression, respectively. The association between TCS traffic volume and new COVID-19 cases by city was analyzed using correlation analysis. RESULTS: Traffic inflow volume in 2020 decreased 3.7% from 2019. The TCS traffic inflow trend in the 8 provinces decreased during the first COVID-19 wave, gradually increased until the second wave, decreased after the second wave, and showed a sharp decrease in the third wave. There was a positive correlation between the traffic inflow volume and new cases in Busan-Gyeongnam and Jeonbuk, but not in Daegu-Gyeongbuk or Gangwon. CONCLUSIONS: A decrease in new COVID-19 cases in the regions was associated with increased traffic inflow volume. Therefore, the Korean government can establish preventive social distancing policies by identifying increases or decreases in traffic volume. These policies will also need to consider the distribution of vaccines in each area.
Subject(s)
COVID-19 , Cities , Humans , Prevalence , Republic of Korea/epidemiology , SARS-CoV-2ABSTRACT
To identify the temporal change in the possible risk of superspreading events, we estimated the overdispersion parameter in 2 different periods of the coronavirus disease 2019 pandemic. We determined that the possible risk of superspreading events was reduced 90% during the second epidemic period in South Korea.
ABSTRACT
BACKGROUND: After relaxing social distancing measures, South Korea experienced a resurgent second epidemic wave of coronavirus disease 2019 (COVID-19). In this study, we aimed to identify the transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and assess the impact of COVID-19 case finding and contact tracing in each epidemic wave. METHODS: We collected data on COVID-19 cases published by local public health authorities in South Korea and divided the study into two epidemic periods (19 January-19 April 2020 for the first epidemic wave and 20 April-11 August 2020 for the second epidemic wave). To identify changes in the transmissibility of SARS-CoV-2, the daily effective reproductive number (Rt) was estimated using the illness onset of the cases. Furthermore, to identify the characteristics of each epidemic wave, frequencies of cluster types were measured, and age-specific transmission probability matrices and serial intervals were estimated. The proportion of asymptomatic cases and cases with unknown sources of infection were also estimated to assess the changes of infections identified as cases in each wave. RESULTS: In early May 2020, within 2-weeks of a relaxation in strict social distancing measures, Rt increased rapidly from 0.2 to 1.8 within a week and was around 1 until early July 2020. In both epidemic waves, the most frequent cluster types were religious-related activities and transmissions among the same age were more common. Furthermore, children were rarely infectors or infectees, and the mean serial intervals were similar (~ 3 days) in both waves. The proportion of asymptomatic cases at presentation increased from 22% (in the first wave) to 27% (in the second wave), while the cases with unknown sources of infection were similar in both waves (22 and 24%, respectively). CONCLUSIONS: Our study shows that relaxing social distancing measures was associated with increased SARS-CoV-2 transmission despite rigorous case findings in South Korea. Along with social distancing measures, the enhanced contact tracing including asymptomatic cases could be an efficient approach to control further epidemic waves.