Evidence map›Paper›PMID 35658732›Full record

ArticleInternational journal of health services : planning, administration, evaluation2022

Are High-Altitude Residents More Susceptible to Covid-19 in India? Findings and Potential Implications for Research and Policy.

Sushmita Chakraborty, Upasak Das, Udayan Rathore, Prasenjit Sarkhel

Abstract read
In one paragraph

Article in International journal of health services : planning, administration, evaluation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Sushmita ChakrabortyIndependent Research, Siliguri, India.
Upasak DasGlobal Development Institute, 5292University of Manchester, Manchester, UK.ORCID 0000-0002-4371-0139
Udayan Rathore65853Oxford Policy Management, New Delhi, India.
Prasenjit SarkhelDepartment of Economics, 30132University of Kalyani, Kalyani, India.ORCID 0000-0001-5486-6959

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we study the incidence of COVID-19 and the associated fatality with altitude using high frequency, district level data from India. To understand the implications of the nationwide lockdown after the outbreak, we use data for about four months- two from the lockdown period starting from March 25 till May 31, 2020 and about two months after unlocking was initiated (June 1-July 26, 2020). The multivariate regression result indicates slower growth in average rate of infection during the lockdown period in hilly regions, the gains of which attenuated after the unlocking was initiated. Despite these early gains, the rate of fatalities is significantly higher during the lockdown period in comparison to the plains. The findings remain robust to multiple alternative specifications and methods including one that accounts for confounding possibilities via unobservable and provides consistent estimates of bias adjusted treatment effects. The evidence supports the need for provisioning of public health services and infrastructure upgradation, especially maintenance of adequate stock of life support devices, in high altitude regions. It also underscores the necessity for strengthening and revising the existing Hill Areas Development Programme and integrating important aspects of public health as part of this policy.

Indexed as

COVID-19AltitudeCommunicable Disease ControlHumansIndiaPolicySARS-CoV-2altitudeCOVID-19fatalityhealth servicesIndia

Identifiers

PMID35658732
PMCPMC9171131

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.