Author: Ndiaye, Babacar Mbaye; Balde, Mouhamadou A.M.T.; Seck, Diaraf
Title: Visualization and machine learning for forecasting of COVID-19 in Senegal Cord-id: uh05fuw2 Document date: 2020_8_6
ID: uh05fuw2
Snippet: 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.
Document: 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.
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