Transportation, germs, culture: a dynamic graph model of COVID-19 outbreak.

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 simula

SUBMITTER: Yang X 

PROVIDER: S-EPMC7479740 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature