EGU21-14008, updated on 10 Mar 2021
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Understanding CoVid-19’s chaotic dynamics

Imee Necesito, Donghyun Kim, Junhyeong Lee, Junghyun Eom, Deok-Woo Kim, and Hung Soo Kim
Imee Necesito et al.
  • Center for Hydrology and Ecology, Inha University, Incheon, South Korea

As we move towards the more critical age of technology and learning, understanding the underlying dynamics of events such as the unforeseen and unpredictable pandemics in the ecological system are deemed invaluable and important. In this paper, using acquired observations of daily cases of CoVid-19 in the US, UK and some parts of Asia, Recurrence Quantification Analysis (RQA) and the plots of state space were constructed. In this study, it was found that some countries have shown similar trends in RQA statistics as compared to classic chaotic attractors and functions while others have shown similar state space plots as that of the other countries. The authors believe that the data currently available worldwide does not allow reliable forecast because of the presence of untested asymptomatic cases, therefore construction of the evolution of the CoVid-19 cases signal in the absence of priori knowledge of other factors as well as analysing the RQA statistics can serve as a starting point as well as provide information for the appropriate prediction method for the prevalent CoVid-19 outbreaks.

How to cite: Necesito, I., Kim, D., Lee, J., Eom, J., Kim, D.-W., and Kim, H. S.: Understanding CoVid-19’s chaotic dynamics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14008,, 2021.

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