Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK; MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, USA.
Environ Res. 2021 Feb;193:110355. doi: 10.1016/j.envres.2020.110355. Epub 2020 Oct 28.
It is unknown if COVID-19 will exhibit seasonal pattern as other diseases e.g., seasonal influenza. Similarly, some environmental factors (e.g., temperature, humidity) have been shown to be associated with transmission of SARS-CoV and MERS-CoV, but global data on their association with COVID-19 are scarce.
To examine the association between climatic factors and COVID-19.
We used multilevel mixed-effects (two-level random-intercepts) negative binomial regression models to examine the association between 7- and 14-day-lagged temperature, humidity (relative and absolute), wind speed and UV index and COVID-19 cases, adjusting for Gross Domestic Products, Global Health Security Index, cloud cover (%), precipitation (mm), sea-level air-pressure (mb), and daytime length. The effects estimates are reported as adjusted rate ratio (aRR) and their corresponding 95% confidence interval (CI).
Data from 206 countries/regions (until April 20, 2020) with ≥100 reported cases showed no association between COVID-19 cases and 7-day-lagged temperature, relative humidity, UV index, and wind speed, after adjusting for potential confounders, but a positive association with 14-day-lagged temperature and a negative association with 14-day-lagged wind speed. Compared to an absolute humidity of <5 g/m, an absolute humidity of 5-10 g/m was associated with a 23% (95% CI: 6-42%) higher rate of COVID-19 cases, while absolute humidity >10 g/m did not have a significant effect. These findings were robust in the 14-day-lagged analysis.
Our results of higher COVID-19 cases (through April 20) at absolute humidity of 5-10 g/m may be suggestive of a 'sweet point' for viral transmission, however only controlled laboratory experiments can decisively prove it.
目前尚不清楚 COVID-19 是否会呈现出季节性模式，就像其他疾病（例如季节性流感）一样。同样，一些环境因素（例如温度、湿度）已被证明与 SARS-CoV 和 MERS-CoV 的传播有关，但关于它们与 COVID-19 之间关联的全球数据却很少。
研究气候因素与 COVID-19 之间的关系。
我们使用多水平混合效应（两级随机截距）负二项回归模型，在调整国内生产总值、全球卫生安全指数、云量（%）、降水量（mm）、海平面气压（mb）和白天长度后，研究了 7 天和 14 天滞后的温度、湿度（相对湿度和绝对湿度）、风速和紫外线指数与 COVID-19 病例之间的关系。效应估计值以调整后的比率比（aRR）及其相应的 95%置信区间（CI）报告。
截至 2020 年 4 月 20 日，从 206 个国家/地区（报告的病例数≥100 例）获得的数据显示，在调整潜在混杂因素后，COVID-19 病例与 7 天滞后的温度、相对湿度、紫外线指数和风速之间没有关联，但与 14 天滞后的温度呈正相关，与 14 天滞后的风速呈负相关。与绝对湿度<5g/m 相比，绝对湿度为 5-10g/m 时 COVID-19 病例的发生率高 23%（95%CI：6-42%），而绝对湿度>10g/m 时则没有显著影响。这些发现在前 14 天滞后分析中是稳健的。
我们的结果表明，4 月 20 日前（COVID-19 病例）在绝对湿度为 5-10g/m 时更高，这可能表明病毒传播存在“甜蜜点”，但只有对照实验室实验才能确定。
