Impact of (SARS-CoV-2) COVID 19 on the five main indigenous language-speaking areas in Veracruz Mexico: The case of the Huasteco from the Tantoyuca area

Medel-Ramírez, Carlos and Medel-López, Hilario (2020): Impact of (SARS-CoV-2) COVID 19 on the five main indigenous language-speaking areas in Veracruz Mexico: The case of the Huasteco from the Tantoyuca area.

Abstract

The importance of the working document is that it allows the analysis of the information and the status of cases associated with (SARS-CoV-2) COVID-19 as open data at the municipal, state and national level, with a daily record of patients, according to a age, sex, comorbidities, for the condition of (SARS-CoV-2) COVID-19 according to the following characteristics: a) Positive, b) Negative, c) Suspicious. Likewise, it presents information related to the identification of an outpatient and / or hospitalized patient, attending to their medical development, identifying: a) Recovered, b) Deaths and c) Active, in Phase 3 and Phase 4, in the five main population areas speaker of indigenous language in the State of Veracruz - Mexico. The data analysis is carried out through the application of a data mining algorithm, which provides the information, fast and timely, required for the estimation of Medical Care Scenarios of (SARS-CoV-2) COVID-19, as well as for know the impact on the indigenous language speaking population in Veracruz. For this purpose, the following study zones are presented: a) Totonacapan Zone, b) Huasteco from the Tantoyuca Zone, c) Otomi from the Inxhuatlan de Madero Zone, d) Nahuatl from the Zongolica Zone, e) Nahuatl from the Chicontepec Zone, f) Nahualt from the Pajapan Zone and g) Popoluca from the Soteapan Zone. This data article presents the information as of August 1, 2020 corresponding to the Huasteco Area.

• Item Type: MPRA Paper
• Language: English
• Keywords: (SARS-CoV-2) COVID-19, Algorithm (SARS-CoV-2) COVID-19, Mexico, identification of patients, Huasteco Area
• Subjects: C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C80 - General; C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C88 - Other Computer Software; I - Health, Education, and Welfare > I1 - Health > I10 - General; I - Health, Education, and Welfare > I1 - Health > I15 - Health and Economic Development; Z - Other Special Topics > Z0 - General > Z00 - General

References

[1] Demsar J, Curk T, Erjavec A, Gorup C, Hocevar T, Milutinovic M, Mozina M, Polajnar M, Toplak M, Staric A, Stajdohar M, Umek L, Zagar L, Zbontar J, Zitnik M, Zupan B (2013) Orange: Data Mining Toolbox in Python, Journal of Machine Learning Research 14(Aug): 2349−2353. https://dl.acm.org/doi/pdf/10.5555/2567709.2567736

[2] Government of Mexico. Health Secretary. Databases Covid-19 México. https://datos.gob.mx/busca/dataset/informacion-referente-a-casos-covid-19-en-mexico

[3] Software Orange Data Mining version 3.26.1 https://orange.biolab.si

[4] World Health Organization. (2020). Laboratory testing for coronavirus disease (COVID-19) in suspected human cases. Interim guidance. 19 March 2020. Recuperado de: https://www.who.int/publications-detail/laboratory-testing-for-2019-novel-coronavirus-in-suspected-human-cases-20200117

[5] Medel-Ramírez, Carlos and Medel-Lopez, Hilario, Data Mining for the Study of the Epidemic (SARS- CoV-2) COVID-19: Algorithm for the Identification of Patients (SARS-CoV-2) COVID 19 in Mexico (June 3, 2020). Available at SSRN: https://ssrn.com/abstract=3619549 or http://dx.doi.org/10.2139/ssrn.3619549

[6] INEGI, (2010). Catálogo de metadatos geográficos. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad. División política municipal, 1:250000. 2010. Palabras clave: 2010, Área Geoestadística, División, Límite, Municipios. Fecha de publicación: 04-07-2011, del metadato 20-07-2017. Available at : http://www.conabio.gob.mx/informacion/gis/

Reference to a dataset:

[7] Raw data can be retrieved from the Github repository https://github.com/CMedelR/dataCovid19/