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Data Analysis, Modeling and Forecasting of COVID-19 using Machine Learning

by Toshaniwali Bhargav, Toran Verma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 11
Year of Publication: 2021
Authors: Toshaniwali Bhargav, Toran Verma
10.5120/ijca2021921425

Toshaniwali Bhargav, Toran Verma . Data Analysis, Modeling and Forecasting of COVID-19 using Machine Learning. International Journal of Computer Applications. 183, 11 ( Jun 2021), 39-46. DOI=10.5120/ijca2021921425

@article{ 10.5120/ijca2021921425,
author = { Toshaniwali Bhargav, Toran Verma },
title = { Data Analysis, Modeling and Forecasting of COVID-19 using Machine Learning },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2021 },
volume = { 183 },
number = { 11 },
month = { Jun },
year = { 2021 },
issn = { 0975-8887 },
pages = { 39-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number11/31973-2021921425/ },
doi = { 10.5120/ijca2021921425 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:16:32.035622+05:30
%A Toshaniwali Bhargav
%A Toran Verma
%T Data Analysis, Modeling and Forecasting of COVID-19 using Machine Learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 11
%P 39-46
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this work, we present a global analysis and exploring the World Wide data of Covid-19. SIR Model and Mathematical Curve Fitting Method have been used to predict the future spread of the pandemic in India. Odisha, Madhya Pradesh, and Chhattisgarh three states of INDIA are selected based on the pattern of the disease spread in INDIA. The parameters of the models are estimated by utilizing real-time data. The models predict the ending of the pandemic in these states and estimate the number of people that would be affected under the prevailing conditions. For analyzing and designing this model available datasets have been used. These consist of a record of cases globally from March 21st to June 1st, 2020. Hence we will make two predictions from our model. The first model will analyze the COVID confirmed cases globally. And, the second model fetches real-time data through which we will predict total confirmed cases, total deaths, and total recovery in India. This model proposes the aim for understanding its everyday exponential behaviour along with the prediction of future reach ability of the COVID-2019 across the nations by utilizing real-time. With lockdown continuing even after May 2020, we expect our model to reflect the peak cases either in the month of September or October 2020.

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Index Terms

Computer Science
Information Sciences

Keywords

COVID-19 Data Analysis Modelling Forecasting SIR Mathematical Curve Fitting SARS-CoV-2 WHO Corona Virus

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