Department of Applied Mathematics, Kyung Hee University, Yongin 17104, Korea.
Int J Environ Res Public Health. 2022 Mar 29;19(7):4056. doi: 10.3390/ijerph19074056.
The characteristics of COVID-19 have evolved at an accelerated rate over the last two years since the first SARS-CoV-2 case was discovered in December 2019. This evolution is due to the complex interplay among virus, humans, vaccines, and environments, which makes the elucidation of the clinical and epidemiological characteristics of COVID-19 essential to assess ongoing policy responses. In this study, we carry out an extensive retrospective analysis on infection clusters of COVID-19 in South Korea from January 2020 to September 2021 and uncover important clinical and social factors associated with age and regional patterns through the sophisticated large-scale epidemiological investigation using the data provided by the Korea Disease Control and Prevention Agency (KDCA). Epidemiological data of COVID-19 include daily confirmed cases, gender, age, city of residence, date of symptom onset, date of diagnosis, and route of infection. We divide the time span into six major periods based on the characteristics of COVID-19 according to various events such as the rise of new variants, vaccine rollout, change of social distancing levels, and other intervention measures. We explore key features of COVID-19 such as the relationship among unlinked, asymptomatic, and confirmed cases, serial intervals, infector-infectee interactions, and age/region-specific variations. Our results highlight the significant impact of temporal evolution of interventions implemented in South Korea on the characteristics of COVID-19 transmission, in particular, that of a high level of vaccination coverage in the senior-aged group on the dramatic reduction of confirmed cases.
自 2019 年 12 月首次发现 SARS-CoV-2 病例以来，过去两年中 COVID-19 的特征已加速演变。这种演变是由于病毒、人类、疫苗和环境之间的复杂相互作用所致，因此阐明 COVID-19 的临床和流行病学特征对于评估当前的政策应对至关重要。在这项研究中，我们对 2020 年 1 月至 2021 年 9 月期间韩国 COVID-19 的感染群进行了广泛的回顾性分析，并通过利用韩国疾病控制与预防局（KDCA）提供的数据进行复杂的大规模流行病学调查，揭示了与年龄和地区模式相关的重要临床和社会因素。COVID-19 的流行病学数据包括每日确诊病例、性别、年龄、居住城市、症状出现日期、诊断日期和感染途径。我们根据 COVID-19 的各种特征，例如新变体的出现、疫苗接种的推出、社交距离水平的变化以及其他干预措施，将时间跨度分为六个主要阶段。我们探讨了 COVID-19 的关键特征，例如未关联、无症状和确诊病例之间的关系、序列间隔、感染者-感染者之间的相互作用以及年龄/地区特定的变化。我们的结果强调了韩国实施的干预措施的时间演变对 COVID-19 传播特征的重大影响，特别是高疫苗接种率对老年人群确诊病例的大幅减少的影响。
