Multiparametric computer simulation estimating the hidden variables of the S.A.R.S.-cov-2 pandemic for the optimal exit strategy

The work shows the outputs of a numerical model for the S.A.R.S.-cov-2 infection. The model is finalized to obtain both the hidden variables of the infection such as the degree of immunization, the number of asymptomatic, degree of lethality and its dependence by the density of infected people, the number of low, mild and severe infections, the evaluation of the effects of the lock-down and re-opening at different degree of social distancing as well as the effect of the use of antiviral drugs as a function of their efficacy against the S.A.R.S.-cov-2. The optimized strategy to stop the S.A.R.S.-cov-2 is formulated.