ISSN (Print) - 0012-9976 | ISSN (Online) - 2349-8846

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Investigating Interstate Variations in the COVID-19 Outcomes in India

The variations in COVID-19 infections and deaths reported in Indian states as of 31 March 2021 have been analysed. While the proportion of people living in densely populated areas, per capita net state domestic product, and proportion of aged people explained the variations in COVID-19 infections, in the case of deaths, an additional contributing factor was identified in per capita public health infrastructure. The curious situation of income increasing COVID-19 transmissions and deaths could probably be explained by the considerable proportion of people in some high-income states living in congested slums under extreme poverty with poor access to basic infrastructure, and the high mobility and exposure of some of these states to domestic and international travel footprint, and large migrant population, all resulting in increased risks.

While the COVID-19 pandemic has taken a heavy toll on the world economy and public health, what has caught the attention of epidemiologists and researchers is the vast variation in the incidence of infections and the dramatic variation in the deaths associated with the virus for similar-sized populations. What has surprised most is the tremendous loss of life in developed countries as well, such as the United States (US), the United Kingdom (UK), France, Germany, Spain, and Italy, which are generally known for effective governance, robust public health systems, high literacy, and good public awareness of diseases. Not only was the incidence of COVID-19 (per thousand people) high, but the number of reported deaths per million population were also high in these countries.

Since the pandemic began in December 2019, several studies have been undertaken worldwide to identify the factors that led to the spread of COVID-19 infections and mortality in different countries and regions. Most such studies either used statistical (regression) analysis or machine learning tools to predict the dynamics of the spread of infections and mortality rates. The main factors explored included demographic indicators (population density, ageing population, per capita income, etc), environmental variables (temperature, humidity, ultraviolet radiations, etc), healthcare and infrastructure facilities.

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Published On : 20th Jan, 2024

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