Evidence map›Paper›PMID 32709027›Full record

ArticleInternational journal of environmental research and public health2020

Demographic and Comorbidities Data Description of Population in Mexico with SARS-CoV-2 Infected Patients(COVID19): An Online Tool Analysis.

Carlos E Galván-Tejada, Laura A Zanella-Calzada, Karen E Villagrana-Bañuelos, Arturo Moreno-Báez, Huizilopoztli Luna-García, Jose María Celaya-Padilla, Jorge Issac Galván-Tejada, Hamurabi Gamboa-Rosales

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. 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
0.2field-weighted citation impact, top 43% of its field
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, 7 citations in OpenAlex.

  1. Article
  2. PandemonCAT: Monitoring the COVID-19 Pandemic in Catalonia, Spain.International journal of environmental research and public health · 2022
    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

8 authors at 2 institutions in 2 countries.

Carlos E Galván-TejadaUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.ORCID 0000-0002-7635-4687
Laura A Zanella-CalzadaLORIA (INRIA, CNRS, Université de Lorraine), Campus Scientifique BP 239, 54506 Nancy, France.ORCID 0000-0002-8049-8077
Karen E Villagrana-BañuelosUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.
Arturo Moreno-BáezUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.
Huizilopoztli Luna-GarcíaUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.ORCID 0000-0001-5714-7482
Jose María Celaya-PadillaUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.ORCID 0000-0001-6847-3777
Jorge Issac Galván-TejadaUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.
Hamurabi Gamboa-RosalesUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.ORCID 0000-0002-9498-6602
Universidad Autónoma de Zacatecas "Francisco García Salinas" · MXCentre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Word Health Organization (WHO) declared in March 2020 that we are facing a pandemic designated as COVID-19, which is the acronym of coronavirus disease 2019, caused by a new virus know as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In Mexico, the first cases of COVID-19, was reported by the Secretary of Health on 28 February 2020. More than sixteen thousand cases and more than fifteen thousand deaths have been reported in Mexico, and it continues to rise; therefore, this article proposes two online visualization tools (a web platform) that allow the analysis of demographic data and comorbidities of the Mexican population. The objective of these tools is to provide graphic information, fast and updated, based on dataset obtained directly from National Governments Health Secretary (Secretaría de Salud, SSA) which is daily refreshed with the information related to SARS-CoV-2. To allow a dynamical update and friendly interface, and approach with R-project, a well-known Open Source language and environment for statistical computing and Shiny package, were implemented. The dataset is loaded automatically from the latest version released by the federal government of Mexico. Users can choose to study particular groups determined by gender, entity, type of result (positive, negative, pending outcome) and comorbidity. The image results are plots that can be instantly interpreted and supported by the text summary. This tool, in addition to being a consultation for the general public, is useful in Public Health to facilitate the visualization of the data, allowing its timely interpretation due to the changing nature of COVID-19, it can even be used for decision-making by leaders, for the benefit of the health of the community.

Indexed as

DemographyInternetBetacoronavirusComorbidityCoronavirus InfectionsCOVID-19HumansMexicoPandemicsPneumonia, ViralPublic HealthSARS-CoV-2comorbidity analysisCOVID-19demographic analysisweb interface development

Identifiers

PMID32709027
PMCPMC7400260
OpenAlexW3042552878

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.