Impact of temperature on the dynamics of the COVID-19 outbreak in China
Impact of temperature on the dynamics of the COVID-19 outbreak in China
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DOI：
10.1016/j.scitotenv.2020.138890
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发表时间：
2020-08-01
影响因子：
9.8
通讯作者：
Xi, Shuhua
中科院分区：
文献类型：
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作者：
Shi, Peng;Dong, Yinqiao;Xi, Shuhua
2019年底，新冠肺炎疫情在中国武汉爆发，并于2020年3月发展成为全球大流行。温度对中国新冠肺炎疫情动态的影响尚不清楚。采集2020年1月20日至2月29日中国内地31个省区的日确诊病例和日平均气温数据。采用局部加权回归和平滑散点图（黄土）、分布滞后非线性模型（DLNMs）和随机效应荟萃分析来检验COVID-19日确诊病例率与温度条件的关系。每日新增病例数在2月12日达到高峰，随后开始下降。日确诊病例数与气温呈双相关系（10℃时出现高峰），低于10℃和高于10℃时日发病数均呈下降趋势。随着气温升高，COVID-19的总体流行强度略有下降，相对危险度（RR）为0.96 （95% CI: 0.93, 0.99）。通过对中国大陆28个省份的随机效应meta分析，我们证实了研究期间温度与RR之间的统计学显著相关（系数= -0.0100,95% CI: -0.0125, -0.0074）。湖北省（除武汉外）和武汉市的DLNMs表现出相似的温度变化规律。此外，采用经气候因素调整的改良易感暴露-感染-恢复（M-SEIR）模型，完整表征了气候对COVID-19流行动态的影响。
A COVID-19 outbreak emerged in Wuhan, China at the end of 2019 and developed into a global pandemic during March 2020. The effects of temperature on the dynamics of the COVID-19 epidemic in China are unknown. Data on COVID-19 daily confirmed cases and daily mean temperatures were collected from 31 provincial-level regions in mainland China between Jan. 20 and Feb. 29, 2020. Locally weighted regression and smoothing scatterplot (LOESS), distributed lag nonlinear models (DLNMs), and random-effects meta-analysis were used to examine the relationship between daily confirmed cases rate of COVID-19 and temperature conditions. The daily number of new cases peaked on Feb. 12, and then decreased. The daily confirmed cases rate of COVID-19 had a biphasic relationship with temperature (with a peak at 10 degrees C), and the daily incidence of COVID-19 decreased at values below and above these values. The overall epidemic intensity of COVID-19 reduced slightly following days with higher temperatures with a relative risk (RR) was 0.96 (95% CI: 0.93, 0.99). A random-effect meta-analysis including 28 provinces in mainland China, we confirmed the statistically significant association between temperature and RR during the study period (Coefficient = -0.0100, 95% CI: -0.0125, -0.0074). The DLNMs in Hubei Province (outside of Wuhan) and Wuhan showed similar patterns of temperature. Additionally, a modified susceptible-exposed-infectious-recovered (M-SEIR) model, with adjustment for climatic factors, was used to provide a complete characterization of the impact of climate on the dynamics of the COVID-19 epidemic.