The Constant K and the Gaussian Temporal Evolution for COVID-19

Antonio J. Balloni, Rogério Winter
143 49

Abstract


We present the Gaussian temporal evolution of Corona Virus, the temporal average constant Ktemporalaverage constant = Kt. The Kt and its standard deviation come from the analysis of 52 experimental Gaussian distribution -histogram-. We have analyzed all histograms from 185 countries presented in the reference (Johns Hopkins, 2020), and, we found 52 countries have a definite trend towards an experimental Gaussian profile. As a result, we found Kt = K52 countries = (35 ± 5) days - average & standard deviation-. We also calculate using an experimental Gaussian got in reference (Johns Hopkins, 2020), the temporal evolution for the world, the constant Kworld. We found Kworld = Kw = (47 ± ½) days. Finally, up to this date, 20 April/2020, we have only 52 of 185 countries presenting the trends towards an experimental Gaussian profile (Johns Hopkins, 2020). The main conclusion from this short communication is that the standard deviation found -Kt = (35 ± 5) days-, is very low, which is very good. Therefore, we may conclude the maximum spread of the Corona contamination will occur in a maximum of up to 40 days from the first registered contamination and, in the worst scenario, up to 30 days. Regarding the Brazil peak of contamination, on 10 March/2020, we carried out A PREVISION, and, in that time, we have affirmed by reasoning, the peak in Brazil would be around 10-15 April/2020. Up to this date, there is a confirmation of this prevision. (Johns Hopkins, 2020). For our next prevision, the decrease from contamination must trend to zero among 30-40 days after the peak contamination. These are the most critical situation faced because the real zero takes a while to get to null and, if no personal safety such as social reclusion is adopted, the contamination starts all over. Finally, we have observed the Kw has a shifting in the function of the time and, our finding explains this.


Keywords


Gaussian constant K, COVID-19, Temporal evolution for constant K, Prevision, Trends, Countries, JHU/CRC

Full Text:

PDF

References


The paper was submitted for International Conference on Life Sciences, Engineering and Technology (iLSET)appreciation on April 14, 2020 and has been accepted for presentation, proceedings publication by iLSET, and publication at the journal, IJonEST.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
.