At the end of last year, a new coronavirus(Covid-19) appeared in the Wuhan region of China. Since then , the virus has spread to other Countries, including Europe. We propose the differential equation governing the evolution of the COVID-19. We propose this dynamic equation also for the describing the evolution of the number of infected people by 13 common respiratory viruses , including the COVID-19 . We have compared our theoretical predictions with the real data for Italy and Belgium and, as a benchmarking operation, also with the predictions provided by using the logistic model. We find that are predictions are in good agreement with the real data from the beginning of the appearance of the COVID-19 , which is not the case for the logistic model that applies only to the few last days. By inserting the numerical values of the parameters, obtained by analysing the real data , into the differential equation we found the values of the days where the maximum values of the number of infected people by COVID-19 will be reached in Italy and Belgium .
A new coronavirus, called COVID-19, appeared in the Chinese region of Wuhan at the end of last year; since then the virus spread to other countries, including most of Europe. We propose a differential equation governing the evolution of the COVID-19. This dynamic equation also describes the evolution of the number of infected people for 13 common respiratory viruses ( including the COVID-19 ). We validate our theoretical predictions with experimental data for Italy and Belgium , and compare them with the predictions of the logistic model. We find that our predictions are in good agreement with the real world since the beginning of the appearance of the COVID-19 ; this is not the case for the logistic model that only applies to the last few days. We use our differential equation parametrized with experimental data to make several predictions, such as the date when Italy and Belgium will reach a peak number of COVID-19 infected people .
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