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气象因素对新冠疫情的影响:南美洲八个受疫情严重影响地区的研究。

Meteorological impact on the COVID-19 pandemic: A study across eight severely affected regions in South America.

机构信息

Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, PR China.

Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.

出版信息

Sci Total Environ. 2020 Nov 20;744:140881. doi: 10.1016/j.scitotenv.2020.140881. Epub 2020 Jul 11.

Abstract

The role of meteorological factors in the transmission of the COVID-19 still needs to be determined. In this study, the daily new cases of the eight severely affected regions in four countries of South America and their corresponding meteorological data (average temperature, maximum temperature, minimum temperature, average wind speed, visibility, absolute humidity) were collected. Daily number of confirmed and incubative cases, as well as time-dependent reproductive number (R) was calculated to indicate the transmission of the diseases in the population. Spearman's correlation coefficients were assessed to show the correlation between meteorological factors and daily confirmed cases, daily incubative cases, as well as Rt. In particular, the results showed that there was a highly significant correlation between daily incubative cases and absolute humidity throughout the selected regions. Multiple linear regression model further confirmed the negative correlation between absolute humidity and incubative cases. The absolute humidity is predicted to show a decreasing trend in the coming months from the meteorological data of recent three years. Our results suggest the necessity of continuous controlling policy in these areas and some other complementary strategies to mitigate the contagious rate of the COVID-19.

摘要

气象因素在 COVID-19 传播中的作用仍需确定。在这项研究中,我们收集了南美洲四个国家八个受灾严重地区的每日新增病例及其相应的气象数据(平均温度、最高温度、最低温度、平均风速、能见度、绝对湿度)。我们计算了每日确诊病例和潜伏期病例的数量以及时变繁殖数(Rt),以指示疾病在人群中的传播。Spearman 相关系数用于显示气象因素与每日确诊病例、每日潜伏期病例以及 Rt 之间的相关性。特别是,结果表明,在选定的地区,每日潜伏期病例与绝对湿度之间存在高度显著的相关性。多元线性回归模型进一步证实了绝对湿度与潜伏期病例之间的负相关关系。根据最近三年的气象数据,绝对湿度预计在未来几个月将呈下降趋势。我们的研究结果表明,这些地区有必要继续采取控制政策,并采取其他一些补充策略来降低 COVID-19 的传播率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/7352107/c492d60518cd/ga1_lrg.jpg

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