Dynamic models for CoVID-19 and data analysis
- Nian Shao,
- Min Zhong,
- Yue Yan,
- Hanshuang Pan,
- Jin Cheng,
- Wenbin Chen
Abstract
In this letter, two time delay dynamic models, TDD-NCP model and
Fudan-CCDC model, are introduced to track the data of COVID-19. The
TDD-NCP model is developed recently by Cheng's group group in Fudan and
SUFE. The TDD-NCP model introduced the time delay process into the
differential equations to describe the latent period of the epidemic.
The Fudan-CDCC model is established when Wenbin Chen suggested to
determine the kernel functions in the TDD-NCP model by the public data
from CDCC. By the public data of the cumulative confirmed cases in
different regions in China and different countries, these models can
clearly illustrate that the containment of the epidemic highly depends
on early and effective isolations.02 Mar 2020Submitted to Mathematical Methods in the Applied Sciences 03 Mar 2020Submission Checks Completed
03 Mar 2020Assigned to Editor
03 Mar 2020Editorial Decision: Accept