Center for Innovation Strategy and Policy, KAIST, South Korea.
Department of Smart Car Engineering, Doowon Technical University, South Korea.
Environ Res. 2022 Jan;203:111810. doi: 10.1016/j.envres.2021.111810. Epub 2021 Jul 31.
With a recent surge of the new severe acute respiratory syndrome-coronavirus 2 (SARS-Cov-2, COVID-19) in South Korea, this study attempts to investigate the effects of environmental conditions such as air pollutants (PM) and meteorological covariate (Temperature) on COVID-19 transmission in Seoul. To account for unobserved heterogeneity in the daily confirmed cases of COVID-19 across 25 contiguous districts within Seoul, we adopt a full Bayesian hierarchical approach for the generalized linear mixed models. A formal statistical analysis suggests that there exists a positive correlation between a 7-day lagged effect of PM concentration and the number of confirmed COVID-19 cases, which implies an elevated risk of the infectious disease. Conversely, temperature has shown a negative correlation with the number of COVID-19 cases, leading to reduction in relative risks. In addition, we clarify that the random fluctuation in the relative risks of COVID-19 mainly originates from temporal aspects, whereas no significant evidence of variability in relative risks is observed in terms of spatial alignment of the 25 districts. Nevertheless, this study provides empirical evidence using model-based formal assessments regarding COVID-19 infection risks in 25 districts of Seoul from a different perspective.
随着韩国新的严重急性呼吸系统综合症冠状病毒 2（SARS-Cov-2，COVID-19）的爆发，本研究试图调查环境条件（如空气污染物（PM）和气象协变量（温度））对首尔 COVID-19 传播的影响。为了说明在首尔 25 个连续区的 COVID-19 每日确诊病例中存在未观察到的异质性，我们采用广义线性混合模型的全贝叶斯分层方法。正式的统计分析表明，PM 浓度的 7 天滞后效应与确诊 COVID-19 病例数之间存在正相关关系，这意味着传染病的风险增加。相反，温度与 COVID-19 病例数呈负相关，导致相对风险降低。此外，我们澄清指出，COVID-19 相对风险的随机波动主要源于时间方面，而在 25 个区的空间排列方面，没有观察到相对风险变化的显著证据。然而，本研究从不同的角度使用基于模型的正式评估为首尔 25 个区的 COVID-19 感染风险提供了经验证据。
