Evidence map›Paper›PMID 32907661›Full record

ArticleDisaster medicine and public health preparedness2022

Assessing Socioeconomic Vulnerabilities Related to COVID-19 Risk in India: A State-Level Analysis.

Praveen Kumar Pathak, Yadawendra Singh, Sandhya R Mahapatro, Niharika Tripathi, Jyoti Jee

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Article in Disaster medicine and public health preparedness, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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9citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Praveen Kumar PathakDepartment of Geography, Faculty of Natural Sciences, Jamia Millia Islamia (Central University), New Delhi, India.ORCID 0000-0003-1571-7859
Yadawendra SinghDepartment of Economics, Chandradhari Mithila College, Lalit Narayan Mithila University, Darbhanga, Bihar, India.
Sandhya R MahapatroA.N. Sinha Institute of Social Studies, Patna, Bihar, India.
Niharika TripathiICMR-National Institute of Medical Statistics, New Delhi110029, India.
Jyoti JeePost-Graduate Department of Geography, Veer Kunwar Singh University, Ara, Bihar, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThere 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.

methodsUsing 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.

resultsThere 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.

conclusionsThis 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.

Indexed as

COVID-19HumansIndiaPandemicsSocioeconomic FactorsVulnerable Populationsepidemiologic methodsgeographic mappingpandemicspolicy makingpublic health

Identifiers

PMID32907661
PMCPMC7711356

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