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Vandana Tamrakar, Jawaharlal Nehru University
Ankita Srivastava, National Institute of Urban Affairs, New Delhi
Mukesh Parmar, Jawaharlal Nehru University
Sudheer Kumar Shukla, Jawaharlal Nehru University
Shewli Shabnam, Department of Higher Education, Govt. of West Bengal
Bandita Boro, Jawaharlal Nehru University
Apala Saha, Centre for the Study of Regional Development, Jawaharlal Nehru University, New Delhi
Benjamin Debbabrma, Jawaharlal Nehru University
Nandita Saikia, International Institute for Population Sciences (IIPS)
The present study examines the association between India's socioeconomic and demographic characteristics and COVID-19 infection ratio at the district level. We used crowdsourced district-level data on COVID-19 from March 14, 2020, to October 31, 2020. We identified hotspot and cold spot districts for COVID-19 cases and infection ratio. We have also carried out regression analysis to highlight the district level demographic, socioeconomic, household infrastructure facilities, and health-related correlates of the COVID-19 infection ratio. The results about 80 percent infected cases and 61 percent deaths were observed in nine states (Delhi, Gujarat, West Bengal, Uttar Pradesh, Andhra Pradesh, Maharashtra, Karnataka, Tamil Nadu, and Telangana). There is a positive yet poor spatial clustering in the COVID-19 IR over neighboring districts. Regression analysis demonstrated that percent of 15-59 aged population, district population density, percent of the urban population, district-level testing ratio, and percent of stunted children were significantly and positively associated with the COVID-19 infection ratio. With an increasing percentage of literacy, there is a lower infection ratio in Indian districts. The COVID-19 infection ratio was more rampant in districts with a higher working-age population, higher population density, a higher urban population, a higher testing ratio, and a higher level of stunted children.
Keywords: COVID-19, Population geography