COVID-19 PATIENTS ANALYSIS AND RISK PREDICTION BASED ON LIFESTYLE DISEASES THROUGH INDIAN DATASET

Abstract

A Novel Coronavirus disease (COVID-19) is a transferable virus triggered by a recently revealed coronavirus. World Health Organization (WHO) declared it as pandemic worldwide. COVID-19 was originated from Wuhan, a city of China and spared over the more than 190 countries over the word. The USA, Spain, Italy, France even India and every country suffered a lot by this epidemic. The indications of COVID-19 are Fever, Cough, Shortness of breath or trouble in breathing, Chills, Repeated shaking with chills, Muscle torment, Headache, Sore throat which is normal as any formal flue which each individual feel during season transition. In this article, the statistical analysis like chi-square analysis, age-wise and diseases-wise classification of recovered and deceased patients are performed and also the different types of Machine Learning models like Multiple linear regression, Naive Bayes Classifier, and Multilayer Perceptron Classifier are proposed for formal analysis and risk prediction of patients with different age group and individuals having lifestyle-based diseases with COVID-19. The dataset used for this study downloaded from covid19india.org, available in .csv format which included travel history of patients, relation with any existing COVID-19 patient, and record of any lifestylebased diseases like diabetes, hypertension, respiratory problem, etc.