Abstract
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.
Keywords: dynamic graph model, transportation, COVID-19, SARS-CoV-2
Supplementary Materials
Transportation, germs, culture: a dynamic graph model of COVID-19 outbreak
Acknowledgements
This study was supported by the National Key R&D Program of China (Nos. 2018YFC0910400, 2017YFC0907500, and 2018ZX10302205), the National Natural Science Foundation of China (Nos. 61702406, 3161372, 31701739 and 8191101420), the “World-Class Universities and the Characteristic Development Guidance Funds for the Central Universities”, Xi’an Jiaotong University Basic Research and Profession Grant (No. xtr022019003), and Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01).
Author Contributions
K.Y. conceived of and designed the study. X.Y. and T.X. implemented the code. X.Y. and P.J. collected and analyzed the data. K.Y., X.Y., H.X., L.Z., L.G. interpreted the results. X.Y. produced the figures. K.Y., X.Y. and L.G. drafted the Article. All authors contributed to the writing of the final version of the Article.
Compliance with Ethics Guidelines
The authors Xiaofei Yang, Tun Xu, Peng Jia, Han Xia, Li Guo, Lei Zhang and Kai Ye declare that they have no conflict of interests.
All procedures performed in studies were in accordance with the ethical standards of the institution or practice at which the studies were conducted, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Footnotes
Author summary
We designed a dynamic graph model for a glance of the dynamic under the COVID-19 pandemic by considering a transportation model as the center. We illustrated that the asymptomatic transmission is the dominating factor contributing to the outbreak and city lockdown is the most effective way to halt virus spread. In addition, the external medical aids are able to effectively reduce the fatality rate when the city medical system is overwhelmed.
Code Availability
References
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Supplementary Materials
Transportation, germs, culture: a dynamic graph model of COVID-19 outbreak