Department(s)

Graziadio Business School

Document Type

Article

Version Deposited

Published version

Publication Date

Summer 2024

Keywords

Controlling Pandemic, COVID-19, Localized Policy Measures, Socio-economic, Spatial Autoregressive Regression

Abstract

The COVID-19 pandemic, a black swan event, created an unprecedented global health hazard and disrupted global economic activities. During the first wave of the COVID-19 pandemic, various governments announced lockdowns. India went under lockdown from 25 March 2020 for 21 days. These lockdowns disrupted the social fabric and economic activities. We examined the demographic and socio-economic determinants of COVID-19 infections and deaths across over 400 districts in India. Using statistical methods, we observed that the infection patterns demonstrate localized characteristics across districts. Areas with a larger male population and higher economic activity witnessed higher infection rates. Districts with more agricultural and backward caste populations and inferior latrine facilities experienced significantly higher mortality rates after controlling for infections and other variables, indicating that a higher concentration of economically deprived populations experience higher mortality. Mobility in spatially contiguous locations appears to be a significant determinant of new infections. Our study emphasizes the role of socio-economic factors in explaining the variation across districts. The findings support the need for locally-specific policy and social-distancing measures to control the spread.

Publication Title

Vikalpa

ISSN

02560909

E-ISSN

23953799

Volume

49

Issue

3

First Page

213

Last Page

229

DOI

10.1177/02560909241260234

Comments

Publication can be accessed at this link: https://10.1177/02560909241260234

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