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10.1007/s40484-020-0215-4 http://scihub22266oqcxt.onion/10.1007/s40484-020-0215-4 32923014!7479740!32923014     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Quant+Biol 2020 ; 8 (3): 238-244 Nephropedia Template TP {{tp|p=32923014|t=2020. Transportation, germs, culture: a dynamic graph model of COVID-19 outbreak |pdf=|usr=}}{{32923014}} gab.com Text Transportation, germs, culture: a dynamic graph model of COVID-19 outbreak JO: Quant Biol http://www.kidney.de/pget.php?&tw=1&pmid=32923014 #FOAvip BACKGROUND: Various models have been applied to predict the trend of the epidemic since the outbreak of COVID-19. METHODS: In this study, we designed a dynamic graph model, not for precisely predicting the number of infected cases, but for a glance of the dynamics under a public epidemic emergency situation and of different contributing factors. RESULTS: We demonstrated the impact of asymptomatic transmission in this outbreak and showed the effectiveness of city lockdown to halt virus spread within a city. We further illustrated that sudden emergence of a large number of cases could overwhelm the city medical system, and external medical aids are critical to not only containing the further spread of the virus but also reducing fatality. CONCLUSION: Our model simulation showed that highly populated modern cities are particularly vulnerable and lessons learned in China could facilitate other countries to plan the proactive and decisive actions. We shall pay close attention to the asymptomatic transmission being suggested by rapidly accumulating evidence as dramatic changes in quarantine protocol are required to contain SARS-CoV-2 from spreading globally. SUPPLEMENTARY MATERIALS: The supplementary materials can be found online with this article at 10.1007/s40484-020-0215-4. Twit Text FOAVip Transportation, germs, culture: a dynamic graph model of COVID-19 outbreak ????Quant Biol http://www.kidney.de/pget.php?&tw=1&pmid=32923014 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32923014 #FOAvip English Wikipedia <ref>{{Cite pmid|32923014}}</ref> Transportation, germs, culture: a dynamic graph model of COVID-19 outbreak #MMPMID32923014 Yang X; Xu T; Jia P; Xia H; Guo L; Zhang L; Ye K Quant Biol 2020[]; 8 (3): 238-244 PMID32923014show ga BACKGROUND: Various models have been applied to predict the trend of the epidemic since the outbreak of COVID-19. METHODS: In this study, we designed a dynamic graph model, not for precisely predicting the number of infected cases, but for a glance of the dynamics under a public epidemic emergency situation and of different contributing factors. RESULTS: We demonstrated the impact of asymptomatic transmission in this outbreak and showed the effectiveness of city lockdown to halt virus spread within a city. We further illustrated that sudden emergence of a large number of cases could overwhelm the city medical system, and external medical aids are critical to not only containing the further spread of the virus but also reducing fatality. CONCLUSION: Our model simulation showed that highly populated modern cities are particularly vulnerable and lessons learned in China could facilitate other countries to plan the proactive and decisive actions. We shall pay close attention to the asymptomatic transmission being suggested by rapidly accumulating evidence as dramatic changes in quarantine protocol are required to contain SARS-CoV-2 from spreading globally. SUPPLEMENTARY MATERIALS: The supplementary materials can be found online with this article at 10.1007/s40484-020-0215-4. äTransportation, germs, culture: a dynamic graph model of COVID-19 outb(epmc).pdf DeepDyve Pubget Overpricing