Author: Shengjie Lai; Isaac Bogoch; Nick Ruktanonchai; Alexander Watts; Xin Lu; Weizhong Yang; Hongjie Yu; Kamran Khan; Andrew J Tatem
Title: Assessing spread risk of Wuhan novel coronavirus within and beyond China, January-April 2020: a travel network-based modelling study Document date: 2020_2_5
ID: iat80b4l_35
Snippet: Addtionally, based on monthly air passenger travel statistics and time series of public and school holidays in 91 countries from 2010 to 2018 (Supplementary Note), we found the seasonal pattens of domestic and international population movements across years were highly consistent with the timing and duration of public and school holidays in different countries (Supplementary Figure S10 and S11) . Moreover, we also found similar spatial patterns i.....
Document: Addtionally, based on monthly air passenger travel statistics and time series of public and school holidays in 91 countries from 2010 to 2018 (Supplementary Note), we found the seasonal pattens of domestic and international population movements across years were highly consistent with the timing and duration of public and school holidays in different countries (Supplementary Figure S10 and S11) . Moreover, we also found similar spatial patterns in the risks of Chinese cities importing the virus from Wuhan via population movements estimated by both the Baidu data in 2014 and 2015, and the more recent data covering the top 50 ranked destinations in 2020, (Figure 1a and Supplementary Figure S12) , highlighting the value of using historical data to rapidly assess present day risks.
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