Evidence map›Paper›PMID 32923304›Full record

ArticleCureus2020

Epidemiological Differences of COVID-19 Over the World.

Abida Sayed, Krishna Teja Challa, Sateesh Arja

Abstract read
In one paragraph

Article in Cureus, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Influence of Resilience on Burnout Syndrome of Faculty Professors.International journal of environmental research and public health · 2022
    Article
  5. 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

3 authors.

Abida SayedDepartment of Medicine and Research, Avalon University School of Medicine, Willemstad, CUW.
Krishna Teja ChallaDepartment of Medicine and Research, Avalon University School of Medicine, Willemstad, CUW.
Sateesh ArjaMedicine/Clinical Skills, Avalon University School of Medicine, Willemstad, CUW.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Coronavirus disease 2019 (COVID-19), originally, from Wuhan, China, has now spread to most countries across the globe and devastated global healthcare systems. The impact of this disease has, however, shown baffling variations in prevalence in different regions of the world. The aim of this short review is to identify differential national COVID-19 prevalence of COVID-19, as well as to suggest these epidemiological differences.  Methods A review of studies was conducted using PubMed and Google Scholar search engines. Search tactics were centered on COVID-19 ("COVID-19" AND "coronavirus") and BCG vaccination ("BCG vaccination" OR "Bacillus Calmette-Guérin" OR "vaccine") Results It is found that national prevalence differences may be linked with BCG childhood immunization history. A statistically insignificant difference was observed in COVID-19 prevalence when comparing countries with a BGC policy and countries without it (P> 0.05). This inconclusivity suggests the influence of confounders in this study. Conclusions National differences in COVID-19 cases can be attributable to immunologic regulations, such as BCG vaccination protocols. Caution should be taken in establishing a correlation between COVID-19 prevalence and BCG vaccination, partly due to the weak quality of statistical data on COVID-19 related to poor testing rates in countries with BCG vaccination policy. Nonetheless, the analysis of the epidemiological aspects of COVID-19 will shed light on future efforts towards effective control and prevention.

Indexed as

bacillus calmette guerin vaccinebcg vaccinecoronaviruscovid-19

Identifiers

PMID32923304
PMCPMC7482990

What OpenQuestion holds

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LicenceCC BY
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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.