Evidence map›Paper›PMID 36788813›Full record

ArticlePeerJ2023

Disparities in COVID-19 incidence and fatality rates at high-altitude.

Bilal Ahmed Abbasi, Neha Chanana, Tsering Palmo, Qadar Pasha

Abstract read
In one paragraph

Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bilal Ahmed AbbasiCSIR-Institute of Genomics and Integrative Biology, Genomics and Molecular Medicine, Delhi, India.
Neha ChananaCSIR-Institute of Genomics and Integrative Biology, Genomics and Molecular Medicine, Delhi, India.
Tsering PalmoCSIR-Institute of Genomics and Integrative Biology, Genomics and Molecular Medicine, Delhi, India.
Qadar PashaCSIR-Institute of Genomics and Integrative Biology, Genomics and Molecular Medicine, Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: SARS-CoV-2 has affected every demography disproportionately, including even the native highland populations. Hypobaric-hypoxic settings at high-altitude (HA, >2,500 masl) present an extreme environment that impacts the survival of permanent residents, possibly including SARS-CoV-2. Conflicting hypotheses have been presented for COVID-19 incidence and fatality at HA. Objectives: To evaluate protection or risk against COVID-19 incidence and fatality in humans under hypobaric-hypoxic environment of high-altitude (>2,501 masl). Methods: Global COVID-19 data of March 2020-21, employed from official websites of the Indian Government, John Hopkins University, and Worldometer were clustered into 6 altitude categories. Clinical cofactors and comorbidities data were evaluated with COVID-19 incidence and fatality. Extensive comparisons and correlations using several statistical tools estimated the risk and protection. Results: Of relevance, data analyses revealed four distinct responses, namely, partial risk, total risk, partial protection, and total protection from COVID-19 at high-altitude indicating a mixed baggage and complexity of the infection. Surprisingly, it included the countries within the same geographic region. Moreover, body mass index, hypertension, and diabetes correlated significantly with COVID-19 incidence and fatality rate ( Conclusions: Varied patterns of protection and risk against COVID-19 incidence and fatality were observed among the high-altitude populations. It is though premature to generalize COVID-19 effects on any particular demography without further extensive studies.

Indexed as

COVID-19Diabetes MellitusAltitudeHumansHypoxiaIncidenceSARS-CoV-2CofactorsComorbiditiesCOVID-19High-altitudeProtectionRisk

Identifiers

PMID36788813
PMCPMC9922493

What OpenQuestion holds

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Registered trials

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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.