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Analyzing Data on the Spread of COVID-19 using Statistical Tools to Predict the Inflexion Point of the Virus in Italy
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The outbreak of the novel coronavirus COVID-19 had resulted in deaths of over 24,000 people by April 20, 2020. The goal of this paper is to use and apply principles of statistics and machine learning on COVID-19 datasets available online to predict the inflection point of the spread of the virus. The inflection point, for the purpose of this paper, is defined as a point in time in days after the outbreak of the virus at which there is a change in the direction of the rate of spreading of the virus. We are using available libraries to fit the data a logistic function.
Keywords
Coronavirus, Curve-Fitting, Logistic Functions, Inflection Points, Infection Prediction, Python.
Manuscript Received: April 25, 2020; Revised: May 10, 2020; Accepted: May 14, 2020.
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