Abstract
There is a paucity of scientific analysis that has examined spatial heterogeneities in the socioeconomic vulnerabilities related to coronavirus disease 2019 (COVID-19) risk and potential mitigation strategies at the sub-national level in India. The present study examined the demographic, socioeconomic, and health system-related vulnerabilities shaping COVID-19 risk across 36 states and union territories in India. Using secondary data from the Ministry of Health and Family Welfare (MoHFW), Government of India; Census of India, 2011; National Family Health Survey, 2015-16; and various rounds of the National Sample Survey, we examined socioeconomic vulnerabilities associated with COVID-19 risk at the sub-national level in India from March 16, 2020, to May 3, 2020. Descriptive statistics, principal component analysis, and the negative binomial regression model were used to examine the predictors of COVID-19 risk in India. There persist substantial heterogeneities in the COVID-19 risk across states and union territories in India. The underlying demographic, socioeconomic, and health infrastructure characteristics drive the vulnerabilities related to COVID-19 in India. This study emphasizes that concerted socially inclusive policy action and sustained livelihood/economic support for the most vulnerable population groups is critical to mitigate the impact of the COVID-19 pandemic in India.
Highlights
There persist substantial heterogeneities in the COVID-19 risk across states and union territories in India
The novel coronavirus disease 2019, referred to as COVID-19, is a global health emergency that has triggered an unprecedented catastrophe with respect to human lives and livelihood, disrupted economic systems cutting across sectors, halted public transportation networks, and restricted social interactions across the globe
Since late December 2019, when early clusters of COVID-19 cases were reported from Wuhan City, Hubei Province of the People’s Republic of China, more than 9.84 million confirmed COVID-19 cases of infection and 495,760 COVID-19 related deaths have been recorded across 216 countries and territories.[2]
Summary
Using secondary data from the Ministry of Health and Family Welfare (MoHFW), Government of India; Census of India, 2011; National Family Health Survey, 2015-16; and various rounds of the National Sample Survey, we examined socioeconomic vulnerabilities associated with COVID-19 risk at the subnational level in India from March 16, 2020, to May 3, 2020. We classified the states and union territories into 3 broad categories (high-, medium-, and low-burden states) based on the number of COVID-19 positive cases seen in each case. We used principal component analysis to compute the “health infrastructure index” based on an array of health systems performance variables such as average population served per hospital, community health center, primary health center, sub-center, doctors, auxiliary nursing midwife, and hospital bed ratio.[47,48] The negative value of the index suggests “high vulnerability,” whereas the positive value of the index indicates “low vulnerability.”. We used principal component analysis to compute the “health infrastructure index” based on an array of health systems performance variables such as average population served per hospital, community health center, primary health center, sub-center, doctors, auxiliary nursing midwife, and hospital bed ratio.[47,48] The negative value of the index suggests “high vulnerability,” whereas the positive value of the index indicates “low vulnerability.” The reliability of the index was assessed using Cronbach’s alpha test.[49]
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