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Population flow drives spatio-temporal distribution of COVID-19 in China 期刊论文
NATURE, 2020
作者:  Fernandez, Diego Carlos;  Komal, Ruchi;  Langel, Jennifer;  Ma, Jun;  Duy, Phan Q.;  Penzo, Mario A.;  Zhao, Haiqing;  Hattar, Samer
收藏  |  浏览/下载:85/0  |  提交时间:2020/07/03

Sudden, large-scale and diffuse human migration can amplify localized outbreaks of disease into widespread epidemics(1-4). Rapid and accurate tracking of aggregate population flows may therefore be epidemiologically informative. Here we use 11,478,484 counts of mobile phone data from individuals leaving or transiting through the prefecture of Wuhan between 1 January and 24 January 2020 as they moved to 296 prefectures throughout mainland China. First, we document the efficacy of quarantine in ceasing movement. Second, we show that the distribution of population outflow from Wuhan accurately predicts the relative frequency and geographical distribution of infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until 19 February 2020, across mainland China. Third, we develop a spatio-temporal '  risk source'  model that leverages population flow data (which operationalize the risk that emanates from epidemic epicentres) not only to forecast the distribution of confirmed cases, but also to identify regions that have a high risk of transmission at an early stage. Fourth, we use this risk source model to statistically derive the geographical spread of COVID-19 and the growth pattern based on the population outflow from Wuhan  the model yields a benchmark trend and an index for assessing the risk of community transmission of COVID-19 over time for different locations. This approach can be used by policy-makers in any nation with available data to make rapid and accurate risk assessments and to plan the allocation of limited resources ahead of ongoing outbreaks.


Modelling of population flows in China enables the forecasting of the distribution of confirmed cases of COVID-19 and the identification of areas at high risk of SARS-CoV-2 transmission at an early stage.


  
Assessing spatiotemporal variation of heat waves during 1961-2016 across mainland China 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2019
作者:  Guo, Enliang;  Wang, Yongfang;  Bao, Yulong
收藏  |  浏览/下载:20/0  |  提交时间:2020/02/17
change point  climate indices  excess heat factors  Koppen climate classifications  mainland China  
Evaluating the accuracy of MSWEP V2.1 and its performance for drought monitoring over mainland China 期刊论文
ATMOSPHERIC RESEARCH, 2019, 226: 17-31
作者:  Xu, Zhengguang;  Wu, Zhiyong;  He, Hai;  Wu, Xiaotao;  Zhou, Jianhong;  Zhang, Yuliang;  Guo, Xiao
收藏  |  浏览/下载:25/0  |  提交时间:2019/11/27
Multi-Source Weighted-Ensemble Precipitation  Drought monitoring  Standardized Precipitation Index  Mainland China  
A regional frequency analysis of precipitation extremes in Mainland China with fuzzy c-means and L-moments approaches 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2017, 37
作者:  Wang, Zhaoli;  Zeng, Zhaoyang;  Lai, Chengguang;  Lin, Wenxin;  Wu, Xushu;  Chen, Xiaohong
收藏  |  浏览/下载:15/0  |  提交时间:2019/04/09
precipitation extremes  regional frequency analysis  L-moments method  fuzzy c-means  Generalized Extreme Value distribution  Mainland China