Before revision:  We drive two processes to analyze COVID-19 data considering measures , and then forecasting is done for Senegal. We show a comparison between deterministic and two machine learning technics for forecasting .
After revision:  We drive two processes to analyze COVID-19 data considering measures . We associate level of nationwide measure with value of parameters related to the contact rate of the model. Then a parametric solve, with respect to those parameters of measures, shows different possibilities of the evolution of the pandemic. Two machine learning tools are used to forecast the evolution of the pandemic. Finally, we show comparison between deterministic and two machine learning technics for forecasting .