(SARS-CoV-2) COVID 19: Vigilancia genómica y evaluación del impacto en la población hablante de lengua indígena en México

(SARS-CoV-2) COVID 19: Genomic surveillance and impact assessment on the indigenous language-speaking population in Mexico

Carlos Medel-Ramírez, Hilario Medel-López and Jennifer Lara-Mérida

MPRA Paper from University Library of Munich, Germany

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.

Keywords: (SARS-CoV-2) COVID-19; Genomic surveillance; data mining techniques; mutations of COVID-19 (SARS-CoV-2) (search for similar items in EconPapers)
JEL-codes: C02 C19 C38 C45 C60 C80 C87 C88 I19 O54 (search for similar items in EconPapers)
Date: 2021-11-28
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