Visualization and machine learning for forecasting of COVID-19 in Senegal
This work addresses the need for accurate COVID-19 forecasting in Senegal to inform public health decisions, but it appears incremental as it applies existing methods to new data.
The authors tackled the problem of forecasting COVID-19 cases in Senegal using visualization and machine learning techniques, predicting inflection points and possible ending times for the pandemic.
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.