COVID-19: A demographic analysis of the trend in Indian cases

Original Article

Author Details : Rohan S. Kulkarni*

Volume : 5, Issue : 4, Year : 2020

Article Page : 216-222

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This paper provides a comprehensive overview of COVID-19 related deaths within India over the first eight months of 2020 for two different Kaggle data sets. Analyzing first data set provided by the Kaggle for the period included Indian Nationality, states, and counts for total cases, deaths, and cured demonstrated that the states are statistically significant in a regression model.
Furthermore, the second Kaggle data set provided by the Kaggle for the period for age, gender, nationality, and all states in the country, I drew conclusions concerning correlations between COVID-19 deaths and the four factor categories and found that the overall logistics regression model was statistically significant. I concluded that within the first eight months of 2020, the both sexes are affected equally by the virus while age and states of residence play important roles in life and death due to the virus. Higher urban populated states with higher GDP creation have seen highest virus related deaths and may explain the forced avoidance of social distancing effect.

Keywords: COVID19, GDP, India demographic analysis, Urban population.

How to cite : Kulkarni R S, COVID-19: A demographic analysis of the trend in Indian cases. IP Indian J Immunol Respir Med 2020;5(4):216-222

Copyright © 2020 by author(s) and IP Indian J Immunol Respir Med. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License (

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