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

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Toshaniwali Bhargav, Toran Verma

Toshaniwali Bhargav and Toran Verma. Data Analysis, Modeling and Forecasting of COVID-19 using Machine Learning. International Journal of Computer Applications 183(11):39-46, June 2021. BibTeX

	author = {Toshaniwali Bhargav and Toran Verma},
	title = {Data Analysis, Modeling and Forecasting of COVID-19 using Machine Learning},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2021},
	volume = {183},
	number = {11},
	month = {Jun},
	year = {2021},
	issn = {0975-8887},
	pages = {39-46},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2021921425},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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