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Severity of the Covid-19 Pandemic in India

Katsushi Imai (), Nidhi Kaicker and Raghav Gaiha
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Nidhi Kaicker: School of Business, Public Policy and Social Entrepreneurship, Ambedkar University, INDIA
Raghav Gaiha: Glovbal Development Institute, University of Manchester, UK and Population Studies Centre, University of Pennsylvania, U.S.A.

No DP2020-21, Discussion Paper Series from Research Institute for Economics & Business Administration, Kobe University

Abstract: The main objective of this study is to identify the socio-economic, meteorological and geographical factors associated with the severity of COVID-19 pandemic in India. The severity is measured by the Cumulative Severity Ratio (CSR) - the ratio of the cumulative COVID related deaths to the deaths in a pre-pandemic year -, its first difference and COVID infection cases. We have found significant inter-state heterogeneity in the pandemic development and have contrasted the trends of the COVID-19 severities between Maharashtra which had the largest number of COVID deaths and cases and the other states. Drawing upon random effects models and Tobit models for the weekly and monthly panel datasets of 32 states/union territories, we have found that the factors associated with the COVID severity include income, gender, multi-morbidity, urbanisation, lockdown and unlock phases, weather including temperature and rainfall, and the retail price of wheat. Brief observations from a policy perspective are made towards the end.

Keywords: Covid-19; Cumulative severity ratio; Daily severity ratio; Random-Effects model; India; Maharashtra (search for similar items in EconPapers)
JEL-codes: C23 I18 N35 O10 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2020-08, Revised 2021-03
New Economics Papers: this item is included in nep-hea
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Downloads: (external link) First version, 2020 (application/pdf)

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Journal Article: Severity of the COVID‐19 pandemic in India (2021) Downloads
Working Paper: Severity of the COVID-19 Pandemic in India (2020) Downloads
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