Applied Ecology and Environmental Sciences
ISSN (Print): 2328-3912 ISSN (Online): 2328-3920 Website: Editor-in-chief: Alejandro González Medina
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Applied Ecology and Environmental Sciences. 2021, 9(2), 177-185
DOI: 10.12691/aees-9-2-9
Open AccessArticle

Analyzing the Effect of Environmental and Demographic Factors on COVID-19 Spread in India Using Statistical Methods: A Case Study

Veena Ghuriani1, and Jyotsna Talreja Wassan1,

1Department of Computer Science, Maitreyi College, University of Delhi, India

Pub. Date: January 15, 2021

Cite this paper:
Veena Ghuriani and Jyotsna Talreja Wassan. Analyzing the Effect of Environmental and Demographic Factors on COVID-19 Spread in India Using Statistical Methods: A Case Study. Applied Ecology and Environmental Sciences. 2021; 9(2):177-185. doi: 10.12691/aees-9-2-9


The study focuses on analyzing the factors associated with novel coronavirus (COVID-19) which is reported as a pandemic by the World Health Organization (WHO) using the statistical methods. The main objective of this work is twofold: i) predicting the spread of coronavirus across regions by analyzing the growth rate, death rate, and recovery rate in different states of INDIA and ii) correlating the coronavirus and environmental metadata conditions. This study aims to analyze how environmental metadata such as temperature, humidity and AQI and population demographics can affect the COVID-19 cases across INDIA, a land of natural variety. The study considers COVID-19 cases, recovery, and deaths in March-July 2020 along with the data collected regarding environmental conditions of temperature, humidity, and air quality. The role of environmental data in spreading of COVID-19 in the highly populated country INDIA has potential of being studied for making policies to curb COVID-19. In this paper, we propose use of statistical methods of Spearman correlation and Linear regression to conduct different analyses related to the coronavirus. Our results indicate that varied temperatures, high humidity, and the air quality could serve as drivers for COVID-19 transmission and recoveries. For example, a high correlation of 0.98 was observed between humidity and COVID spread in southern Indian regions of Karnataka and West Bengal with tropical semi-arid steppe climate. Recovery rate found to be related to the environmental conditions such as air quality. Additionally, the population density proved to be one of the major factors affecting COVID-19 spread in INDIA with rural and urban populations. Keeping this in viewpoint, prevention measures accordingly be adopted in Indian States and Union territories for reducing the COVID-19 spread and prepare INDIA as medically and socially a better country amidst this global pandemic.

COVID-19 temperature humidity regression analysis spearman correlation

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