  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.
