We consider a compartmental model from which we incorporate a time-dependent health care capacity having a logistic growth. This allows us to take into account the Senegalese authorities response in anticipating the growing number of infected cases. We highlight the importance of anticipation and timing to avoid overwhelming that could impact considerably the treatment of patients and the well-being of health care workers. A condition, depending on the health care capacity and the flux of new hospitalized individuals, to avoid possible overwhelming is provided. We also use machine learning approach to project forward the cumulative number of cases from March 02, 2020, until 1st December, 2020.

In this article, we give visualization and different machine learning technics for two weeks and 40 days ahead forecast based on public data. On July 15, 2020, Senegal reopened its airspace doors, while the number of confirmed cases is still increasing. The population no longer respects hygiene measures, social distancing as at the beginning of the contamination. Negligence or tiredness to always wear the masks? We make forecasting on the inflection point and possible ending time.