26447Department of Biostatistics, Peking University First Hospital, Beijing, China.
Department of Epidemiology and Health Statistics, School of Public Health, 379397Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
Inquiry. 2021 Jan-Dec;58:469580211060259. doi: 10.1177/00469580211060259.
Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration-response analyses were performed. An increase of each interquartile range in PM, PM, SO, NO, O, and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29), and 1.26 (1.24-1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM, PM, NO, and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM, PM, NO, may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.
有关环境因素对 COVID-19 传播影响的证据存在差异。本研究旨在探讨中国疫情期间空气污染物和气象因素与确诊 COVID-19 病例之间的关联。从权威电子数据库中提取了 2020 年 1 月 25 日至 2 月 29 日(36 天)期间中国的 COVID-19 确诊病例数、空气污染物浓度和气象因素。使用广义加性混合模型估计了单日滞后和移动平均滞后的关联。在空气污染水平和天气条件差异较大且样本量充足的 5 个选定的中国北方到南方地区进行了区域特异性分析和荟萃分析。进行了非线性浓度-反应分析。滞后 4 天每增加一个四分位距(IQR)的 PM、PM、SO、NO、O 和 CO 浓度分别对应于每日新增病例的 1.40(1.37-1.43)、1.35(1.32-1.37)、1.01(1.00-1.02)、1.08(1.07-1.10)、1.28(1.27-1.29)和 1.26(1.24-1.28)的比值比(OR)。气温、相对湿度和风速每升高 1°C、1%和 1 m/s,OR 分别为 0.97(0.97-0.98)、0.96(0.96-0.97)和 0.94(0.92-0.95)。对 5 个选定地区进行荟萃分析后,PM、PM、NO 和所有气象因素的估计仍具有统计学意义。浓度-反应关系表明,空气污染物浓度较高和气象因素较低与每日新增病例增加有关。较高的空气污染物浓度和较低的温度、相对湿度和风速可能有利于 COVID-19 的传播。控制环境空气污染,特别是 PM、PM、NO,可能是降低 COVID-19 感染风险的重要组成部分。此外,随着中国冬季的到来,气象因素可能在预防方面发挥负面作用。因此,持续实施公共卫生控制措施对于应对另一次可能的大流行至关重要。