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10.3390/ijerph17103356 http://scihub22266oqcxt.onion/10.3390/ijerph17103356 32408602!7277792!32408602     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Environ+Res+Public+Health 2020 ; 17 (10): ä Nephropedia Template TP {{tp|p=32408602|t=2020. The Predictive Capacity of Air Travel Patterns During the Global Spread of the COVID-19 Pandemic: Risk, Uncertainty and Randomness |pdf=|usr=}}{{32408602}} gab.com Text The Predictive Capacity of Air Travel Patterns During the Global Spread of the COVID-19 Pandemic: Risk, Uncertainty and Randomness JO: Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32408602 #FOAvip Air travel has a decisive role in the spread of infectious diseases at the global level. We present a methodology applied during the early stages of the COVID-19 pandemic that uses detailed aviation data at the final destination level in order to measure the risk of the disease spreading outside China. The approach proved to be successful in terms of identifying countries with a high risk of infected travellers and as a tool to monitor the evolution of the pandemic in different countries. The high number of undetected or asymptomatic cases of COVID-19, however, limits the capacity of the approach to model the full dynamics. As a result, the risk for countries with a low number of passengers from Hubei province appeared as low. Globalization and international aviation connectivity allow travel times that are much shorter than the incubation period of infectious diseases, a fact that raises the question of how to react in a potential new pandemic. Twit Text FOAVip The Predictive Capacity of Air Travel Patterns During the Global Spread of the COVID-19 Pandemic: Risk, Uncertainty and Randomness ????Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32408602 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32408602 #FOAvip English Wikipedia <ref>{{Cite pmid|32408602}}</ref> The Predictive Capacity of Air Travel Patterns During the Global Spread of the COVID-19 Pandemic: Risk, Uncertainty and Randomness #MMPMID32408602 Christidis P; Christodoulou A Int J Environ Res Public Health 2020[May]; 17 (10): ä PMID32408602show ga Air travel has a decisive role in the spread of infectious diseases at the global level. We present a methodology applied during the early stages of the COVID-19 pandemic that uses detailed aviation data at the final destination level in order to measure the risk of the disease spreading outside China. The approach proved to be successful in terms of identifying countries with a high risk of infected travellers and as a tool to monitor the evolution of the pandemic in different countries. The high number of undetected or asymptomatic cases of COVID-19, however, limits the capacity of the approach to model the full dynamics. As a result, the risk for countries with a low number of passengers from Hubei province appeared as low. Globalization and international aviation connectivity allow travel times that are much shorter than the incubation period of infectious diseases, a fact that raises the question of how to react in a potential new pandemic. |*Air Travel[MESH] |*Coronavirus[MESH] |*Pandemics[MESH] |Aviation/*statistics & numerical data[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology/transmission[MESH] |Global Health[MESH] |Humans[MESH] |Pneumonia, Viral/*epidemiology/transmission[MESH] |Risk Assessment[MESH] |SARS-CoV-2[MESH] |Spatial Analysis[MESH]The Predictive Capacity of Air Travel Patterns During the Global Sprea(epmc).pdf DeepDyve Pubget Overpricing