The topological entropy mechanism of coronavirus disease 2019 (COVID-19)

The biological principal or its detailed mechanism for the pandemic coronavirus disease 2019 (COVID-19) has been investigated and analyzed from the topological entropy approach. The findings thus obtained have provided very useful clues and information for developing both powerful and safe vaccines against the pandemic COVID-19.

In December 2019, the COVID-19 was also discovered in Wuhan, China. It has since spread to 220 countries worldwide.
Symptoms of COVID-19 are variable, but often include fatigue, breathing difficulties, fever, and cough.
According to the recent report, there are about 13,000,000 confirmed cases in USA alone, of which about 300,000 are confirmed to death.
Meanwhile, as clearly pointed out by the famous American news magazine TIME, the year of 2020 is the most serious disaster year for our earth. And such a statement has also been shown via its Cover Figure  selection.
The virus that causes COVID-19 spreads mainly when an infected person is in close contact with another person. Small droplets and aerosols containing the virus can spread from an infected person's nose and mouth as he breathes, coughs, sneezes, sings, or speaks.
Preventive measures include social distancing, quarantining, ventilation of indoor spaces, covering Open Access Natural Science coughs and sneezes, hand washing, and keeping unwashed hands away from the face. The use of face masks or coverings has been recommended in public settings to minimize the risk of transmissions.
Recently, four intriguing papers were published with the attempt to find the biological mechanism of COVID-19 from the mathematical [1], physical [2], chemical [3] and physiochemical [2] approaches, respectively. In this paper, we are to address such an extremely important topic from a different approach.
In mathematics, the topological entropy of a topological, dynamical system is a nonnegative, extended real number used for measuring the complexity of the system, as formulated below: For more information, see a Wikipedia article at https://en.wikipedia.org/wiki/Topological_entropy, as well as Figure 1 & Figure 2 in the Section 2.

METERIALS AND METHOD
The "Chou's 5-step rules" or "Chou's 5-steps rule" has also been applied because it has been widely and increasingly used by many scientists to study biological sequence analyses .
To develop a really useful predictor for a biological system, one needs to go through the following five steps: 1) select or construct a valid benchmark dataset to train and test the predictor; 2) represent the samples with an effective formulation that can truly reflect their intrinsic correlation with the target to be predicted; 3) introduce or develop a powerful algorithm to conduct the prediction; 4) properly perform cross-validation tests to objectively evaluate the anticipated prediction accuracy; 5) establish a user-friendly web-server for the predictor that is accessible to the public. Papers presented for developing a new sequence-analyzing method or statistical predictor by observing the guidelines of Chou's 5-step rules have the following notable merits: 1) crystal clear in logic development, 2) completely transparent in operation, 3) easily to repeat the reported results by other investigators, 4) with high potential in stimulating other sequence-analyzing methods, and 5) very convenient to be used by the majority of experimental scientists.
Accordingly, the webserver for the current paper has been established as well.

CONCLUSION
The topological entropy and the detailed mechanism therein are very useful for developing extremely powerful and high efficiency vaccines in fighting against the pandemic COVID-19 as well as saving the human beings on this earth.

CONFLICTS OF INTEREST
The authors declare no conflicts of interest regarding the publication of this paper.