Revue: | Computación y sistemas |
Base de datos: | |
Número de sistema: | 000560672 |
ISSN: | 1405-5546 |
Autores: | Barrón Adame, José Miguel1 Holgado Apaza, Luis Alberto2 Acosta Navarrete, María Susana1 Guzmán Cabrera, Rafael3 Palma Ttito, Luis Beltrán4 Suma Salas, Solinka5 Miranda Castillo, Ralph6 |
Instituciones: | 1Universidad Tecnológica Suroeste de Guanajuato, Guanajuato. México 2Universidad Nacional del Altiplano, Puno. Perú 3Universidad de Guanajuato, México 4Universidad Nacional San Antonio Abad del Cusco, Cusco. Perú 5Universidad Nacional de Huancavelica, Huancavelica. Perú 6Universidad Nacional Amazónica de Madre de Dios, Madre de Dios. Perú |
Año: | 2022 |
Periodo: | Ene-Mar |
Volumen: | 26 |
Número: | 1 |
Paginación: | 399-409 |
País: | México |
Idioma: | Inglés |
Resumen en inglés | In the present paper are analyzed the correlations between the meteorological variables such as maximum temperature, minimum temperature, relative humidity, precipitation with the number of infections by SARS-CoV-2. The data set for the meteorological variables was obtained from web site of the National Service of Meteorology and Hydrology of Peru (SENAMHI), while the number of infections by SARS-CoV-2 was obtained from the denominated data positive by COVID 19 reported in web site by the Ministry of Health from Peru. After the preprocessing and the fusion of the data sets, it was obtained a data subset with 365 registers and 6 columns. To detect the correlations between the meteorological variables and the number of infections by SARS-CoV-2, the Spearman’s rank correlation coefficient was computed. The results show significant correlations between the variables minimum temperature and number of infections by SARS-CoV-2 for a rho=-0.45, p-valor=0.00<0.05; relative humidity and number of infections by SARS-CoV-2 for a rho=-0.24, p-valor=0.00<0.05; precipitation and number of infections by SARS-CoV-2 for a rho=-0.24, p-valor=0.00<0.05. According to the results obtained, we concluded that minimum temperatures facilitate the SARS-CoV-2 transmissibility. |
Keyword: | Data mining, COVID-19, Environmental variables |
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