(SARS-CoV-2) COVID 19: Genomic surveillance and evaluation of the impact
on the population speaker of indigenous language in Mexico
- URL: http://arxiv.org/abs/2112.01276v1
- Date: Mon, 29 Nov 2021 16:05:13 GMT
- Title: (SARS-CoV-2) COVID 19: Genomic surveillance and evaluation of the impact
on the population speaker of indigenous language in Mexico
- Authors: Medel-Ram\'irez Carlos, Medel-L\'opez Hilario, Lara-M\'erida Jennifer
- Abstract summary: This study analyzes the impact of (SARS-CoV-2) COVID-19 on the indigenous language-speaking population in Mexico.
The data analysis is carried out by means of the design of an algorithm applying data mining techniques and methodology.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The importance of the working document is that it allows the analysis of
information and cases associated with (SARS-CoV-2) COVID-19, based on the daily
information generated by the Government of Mexico through the Secretariat of
Health, responsible for the Epidemiological Surveillance System for Viral
Respiratory Diseases (SVEERV). The information in the SVEERV is disseminated as
open data, and the level of information is displayed at the municipal, state
and national levels. On the other hand, the monitoring of the genomic
surveillance of (SARS-CoV-2) COVID-19, through the identification of variants
and mutations, is registered in the database of the Information System of the
Global Initiative on Sharing All Influenza Data (GISAID) based in Germany.
These two sources of information SVEERV and GISAID provide the information for
the analysis of the impact of (SARS-CoV-2) COVID-19 on the population in
Mexico. The first data source identifies information, at the national level, on
patients according to age, sex, comorbidities and COVID-19 presence
(SARS-CoV-2), among other characteristics. The data analysis is carried out by
means of the design of an algorithm applying data mining techniques and
methodology, to estimate the case fatality rate, positivity index and identify
a typology according to the severity of the infection identified in patients
who present a positive result. for (SARS-CoV-2) COVID-19. From the second data
source, information is obtained worldwide on the new variants and mutations of
COVID-19 (SARS-CoV-2), providing valuable information for timely genomic
surveillance. This study analyzes the impact of (SARS-CoV-2) COVID-19 on the
indigenous language-speaking population, it allows us to provide information,
quickly and in a timely manner, to support the design of public policy on
health.
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