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


Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
17 07 2020
Historique:
received: 29 05 2020
revised: 16 06 2020
accepted: 19 06 2020
entrez: 26 7 2020
pubmed: 28 7 2020
medline: 22 8 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 32709027
pii: ijerph17145173
doi: 10.3390/ijerph17145173
pmc: PMC7400260
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

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pubmed: 31119031
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pubmed: 32173574

Auteurs

Carlos E Galván-Tejada (CE)

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.

Laura A Zanella-Calzada (LA)

LORIA (INRIA, CNRS, Université de Lorraine), Campus Scientifique BP 239, 54506 Nancy, France.

Karen E Villagrana-Bañuelos (KE)

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.

Arturo Moreno-Báez (A)

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.

Huizilopoztli Luna-García (H)

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.

Jose María Celaya-Padilla (JM)

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.

Jorge Issac Galván-Tejada (JI)

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.

Hamurabi Gamboa-Rosales (H)

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Zac, Mexico.

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Classifications MeSH