Evolution of COVID-19 patients in Mexico city using markov chains

Ricardo C. Villarreal-Calva, Ponciano J. Escamilla-Ambrosio, Abraham Rodríguez-Mota, Juan M. Ramírez-Cortés

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

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Resumen

In this work a Markov process model has been conceived using public data from patients that have experienced symptoms associated with the COVID-19 disease. The data published by the health system of Mexico City was used to fit the model with seven different states. The probabilities of death or recovery at every state are calculated to understand the severity of the novel disease compared to other respiratory diseases. The model provides information to asses the risk of staying at a hospital in Mexico City for patients with respiratory illnesses either positive or negative to SARS-COV-2 virus.

Idioma originalInglés
Título de la publicación alojadaTelematics and Computing - 9th International Congress, WITCOM 2020, Proceedings
EditoresMiguel Félix Mata-Rivera, Roberto Zagal-Flores, Cristian Barria-Huidobro
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas309-318
Número de páginas10
ISBN (versión impresa)9783030625535
DOI
EstadoPublicada - 2020
Evento9th International Congress on Telematics and Computing, WITCOM 2020 - Puerto Vallarta, México
Duración: 2 nov. 20206 nov. 2020

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen1280
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

Conferencia9th International Congress on Telematics and Computing, WITCOM 2020
País/TerritorioMéxico
CiudadPuerto Vallarta
Período2/11/206/11/20

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