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We present the gaussian temporal evolution of Corona Virus, the temporal average constant K_{temporal average constant} = K_t. The K_t 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 [1], and, we found 52 countries have a definite trend towards an experimental gaussian profile. As a result, we found K_t = K_{52 countries} = (35 ± 5) days - average & standard deviation-. We also calculate using an experimental gaussian got in the reference [1], the temporal evolution for the world, the constant K_world. We found K_world = K_{w =} (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 [1]. The main conclusion from this short communication is that the standard deviation found -K_t = (35 ± 5)days-, is very, 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. [1]. 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.

Reference
Johns Hopkins University of Medicine -Coronavirus Resource Center-: DAYLY CASES histograms retrieved from https://coronavirus.jhu.edu/map.html. Last access on April 20, 2020.

Note: The paper was submitted for Congress appreciation on April 14, 2020 and has been accepted for presentation, proceedings publication by iLSET, and publication at the journal, IJonEST.

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