COVID-19 Data Analysis – Predicting Patient Recovery

Authors : Arnela Salkic; Nermina Durmic

Volume/Issue : Volume 5 - 2020, Issue 8 - August

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Scribd :

DOI : 10.38124/IJISRT20AUG180

Aim of this paper is to give insight in Covid 19 data and to try to predict whether individual person will recover from this virus. Furthermore, this paper aims to give some answers how information like the country, the age, and the gender of the patient, the number of cases in their country and whether they’re from or have visited Wuhan can be used to make that prediction. Study uses Novel Corona Virus (COVID-19) epidemiological dataset. Logistic regression model and Random Forest algorithm are used in order to make prediction, and the Chi-Square test of independence is used to determine if there is a significant relationship between two nominal (categorical) variables. Paper reveals that recovery/survival is supposed to depend on the age of the patient, gender and country from which patient come. Information whether the patient is from Wuhan or has visited Wuhan does not affect recovery/survival of patient.

Keywords : Covid 19; Pandemic; Logistic Regression; Random Forest; Chi-Square Test.


Paper Submission Last Date
31 - July - 2022

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