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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:88/0  |  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.


  
Variation of intra-crown leaf plasticity of Fagus crenata across its geographical range in Japan 期刊论文
FOREST ECOLOGY AND MANAGEMENT, 2018, 429: 437-448
作者:  Ishii, H. Roaki;  Horikawa, Shin-ichiro;  Noguchi, Yuiko;  Azuma, Wakana
收藏  |  浏览/下载:20/0  |  提交时间:2019/04/09
Acclimation  Geographical variation  Habitat fragmentation  Leaf functional trait  Local adaptation  Distribution range  
Both life-history plasticity and local adaptation will shape range-wide responses to climate warming in the tundra plant Silene acaulis 期刊论文
GLOBAL CHANGE BIOLOGY, 2018, 24 (4) : 1614-1625
作者:  Peterson, Megan L.;  Doak, Daniel F.;  Morris, William F.
收藏  |  浏览/下载:20/0  |  提交时间:2019/04/09
climate change  demographic compensation  geographical distribution  local adaptation  plasticity  
First harvest of Perigord black truffle in the UK as a result of climate change 期刊论文
CLIMATE RESEARCH, 2018, 74 (1) : 67-70
作者:  Thomas, Paul;  Buntgen, Ulf
收藏  |  浏览/下载:16/0  |  提交时间:2019/04/09
Climate change  Truffle cultivation  Ectomycorrhiza fungi  Geographical distribution  Truffle ecology  Tuber melanosporum  Perigord truffle  UK  
Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks 期刊论文
ECOLOGY LETTERS, 2017, 20 (6)
作者:  Staniczenko, Phillip P. A.;  Sivasubramaniam, Prabu;  Suttle, K. Blake;  Pearson, Richard G.
收藏  |  浏览/下载:16/0  |  提交时间:2019/04/09
Bayesian networks  biotic interactions  climate change  community ecology  geographical range  networks  species distribution models  
Climatology of destructive hailstorms in Brazil 期刊论文
ATMOSPHERIC RESEARCH, 2017, 184
作者:  Martins, Jorge A.;  Brand, Veronika S.;  Capucim, Mauricio N.;  Felix, Rafael R.;  Martins, Leila D.;  Freitas, Edmilson D.;  Goncalves, Fabio L. T.;  Hallak, Ricardo;  Silva Dias, Maria A. F.;  Cecil, Daniel J.
收藏  |  浏览/下载:25/0  |  提交时间:2019/04/09
Hail report  Destructive hailstorm  Hail annual cycle  Hail diurnal cycle  Hail geographical distribution