Modelling the downhill of the Sars-Cov-2 in Italy and a universal forecast of the epidemic in the world

In a previous article [1] we have described the temporal evolution of the Sars-Cov-2 in Italy in the time window February 24-April 1 As we can see in [1] a generalized logistic equation captures both the peaks of the total infected and the deaths In this article our goal is to study the missing peak, i e the currently infected one (or total currently positive) After the April 7 the large increase in the number of swabs meant that the logistical behavior of the infected curve no longer worked So we decided to generalize the model, introducing new parameters Moreover, we adopt a similar approach used in [1] (for the estimation of deaths) in order to evaluate the recoveries In this way, introducing a simple conservation law, we define a model with 4 populations: total infected, currently positives, recoveries and deaths Therefore, we propose an alternative method to a classical SIRD model for the evaluation of the Sars-Cov-2 epidemic However, the method is general and thus applicable to other diseases Finally we study the behavior of the ratio infected over swabs for Italy, Germany and USA, and we show as studying this parameter we recover the generalized Logistic model used in [1] for these three countries We think that this trend could be useful for a future epidemic of this coronavirus