{"id":11961,"date":"2020-03-31T14:17:00","date_gmt":"2020-03-31T14:17:00","guid":{"rendered":"https:\/\/cit.upc.edu\/covid-19-model-matematic\/"},"modified":"2022-11-07T10:54:06","modified_gmt":"2022-11-07T10:54:06","slug":"covid-19-modelo-matematico","status":"publish","type":"post","link":"https:\/\/cit.upc.edu\/es\/covid-19-modelo-matematico\/","title":{"rendered":"COVID-19 Modelos matem\u00e1ticos y de gesti\u00f3n de datos en emergencias de salud p\u00fablica"},"content":{"rendered":"\n

31-03-2020<\/p>\n\n\n\n

Varios grupos y centros de investigaci\u00f3n de la UPC trabajan en proyectos sobre gesti\u00f3n de grandes vol\u00famenes de datos y modelizaci\u00f3n matem\u00e1tica para avanzar en la investigaci\u00f3n en la emergencia sanitaria causada por la pandemia de la COVID-19.<\/strong><\/p>\n\n\n\n

\"\"<\/figure><\/div>\n\n\n\n

Un modelo matem\u00e1tico para hacer un seguimiento de la epidemia<\/strong><\/p>\n\n\n\n

El grupo de investigaci\u00f3n de Biolog\u00eda Computacional y Sistemas Complejos (BIOCOM-SC)<\/a>, especializado en epidemiolog\u00eda matem\u00e1tica, junto con el Instituto de Investigaci\u00f3n Germans Trias i Pujol (IGTP) est\u00e1n trabajando en el an\u00e1lisis de datos sobre la incidencia del COVID-19 y han desarrollado un modelo matem\u00e1tico que permite cuantificar la situaci\u00f3n, as\u00ed como la predicci\u00f3n de los siguientes 3 d\u00edas.<\/p>\n\n\n\n

El centro ofrece un documento divulgativo<\/a> para entender la din\u00e1mica epidemiol\u00f3gica, informes peri\u00f3dicos<\/a> que eval\u00faan la situaci\u00f3n y hace predicciones a corto plazo en Catalu\u00f1a, en Espa\u00f1a y en la Uni\u00f3n Europea, un resumen diario de la situaci\u00f3n<\/a> en las otras comunidades aut\u00f3nomas y otros pa\u00edses de la UE, as\u00ed como predicciones del d\u00edas previos<\/a>.<\/p>\n\n\n\n

La UPC impulsa la plataforma GoData y apoya la OMS<\/strong><\/p>\n\n\n\n

La UPC est\u00e1 dando soporte t\u00e9cnico, con la colaboraci\u00f3n de los departamentos de Ingenier\u00eda Telem\u00e1tica y de Arquitectura de Computadores, a la Organizaci\u00f3n Mundial de la Salud (OMS) para la aplicaci\u00f3n en Catalu\u00f1a del software GoData<\/strong>, una herramienta de investigaci\u00f3n de brotes para recoger datos de campo durante emergencias de salud p\u00fablica del COVID-19.<\/p>\n\n\n\n

La UPC y la spin-off Alteraid<\/a>, surgida de la UPC, impulsan la plataforma GoData.cat, que da soporte a la instalaci\u00f3n del software de la OMS y ofrece un servidor de pruebas para hacer test y formaci\u00f3n de la aplicaci\u00f3n.<\/p>\n\n\n\n

Es una herramienta multiling\u00fce y flexible, con m\u00faltiples funciones para la importaci\u00f3n y exportaci\u00f3n de datos, esto permite obtener informaci\u00f3n para hacer un seguimiento de la incidencia del COVID-19 y poder adaptar la respuesta de las instituciones sanitarias en los diferentes escenarios.<\/p>\n\n\n\n

Un modelo para estimar el n\u00famero real de casos de COVID-19 por cada comunidad aut\u00f3noma<\/strong><\/p>\n\n\n\n

Un equipo de matem\u00e1ticos y estad\u00edsticos de la UPC, de la Humboldt-Universit\u00e4t zu Berlin y de la UAB est\u00e1 desarrollando un modelo para estimar el n\u00famero real de nuevos casos diarios de personas infectadas por COVID-19, ante la imposibilidad de tener este dato directamente en toda la poblaci\u00f3n dado que muchos de los casos son leves o asintom\u00e1ticos. Los datos oficiales se basan en n\u00fameros que reflejan aquellos casos m\u00e1s graves y, por tanto, se desconocen aquellos otros casos que tambi\u00e9n contribuyen a la expansi\u00f3n de la pandemia.<\/p>\n\n\n\n

Investigadores del Departamento de Matem\u00e1ticas de la UAB desarrollaron en 2016 un m\u00e9todo para el an\u00e1lisis de datos subrepresentadas en las estad\u00edsticas (Under-reported data analysis with INAR-hidden Markov chains<\/a>). El m\u00e9todo permite hacer una estimaci\u00f3n precisa del n\u00famero de casos que no se registran oficialmente, con diversas aplicaciones en salud p\u00fablica, como el seguimiento del n\u00famero de casos reales de infecciones por el virus del papiloma humano (VPH), de botulismo y tambi\u00e9n de casos reales de mujeres maltratadas.<\/p>\n\n\n\n

Ahora, los investigadores de la UAB, con la colaboraci\u00f3n del Departamento de Ciencias de la Computaci\u00f3n de la UPC<\/strong>, de la Humboldt-Universit\u00e4t zu Berlin<\/a> y del Centro de Investigaci\u00f3n Matem\u00e1tica<\/a>, est\u00e1n aplicando este m\u00e9todo para actualizar diariamente la situaci\u00f3n de COVID-19 y, en particular, cuantificar los casos no reportados en el registro oficial de la enfermedad en Espa\u00f1a. Los resultados permiten dar una imagen m\u00e1s realista de la pandemia en tiempo real, as\u00ed como estimar con mayor precisi\u00f3n datos fundamentales como las tasas de mortalidad reales o el n\u00famero b\u00e1sico de reproducci\u00f3n, necesarias para que los profesionales y los pol\u00edticos puedan tomar decisiones. El an\u00e1lisis est\u00e1 pensado para ser f\u00e1cilmente reproducible con datos de otros pa\u00edses.<\/p>\n\n\n\n

Por parte de la UPC, el investigador Argimiro Arratia<\/a>, del Laboratorio de Algor\u00edtmica Relacional, Complejidad y Aprendizaje (LARCA)<\/a>, participa en el dise\u00f1o y la programaci\u00f3n de modelos epid\u00e9micos a los que se les introduce como input las series de casos de infecci\u00f3n reconstruidas de acuerdo con el modelo matem\u00e1tico desarrollado por el equipo de la UAB. Adem\u00e1s, el investigador colabora en la recolecci\u00f3n de datos, el tratamiento de estas y la automatizaci\u00f3n de todo el proceso de ejecuci\u00f3n de las simulaciones y an\u00e1lisis de datos.<\/p>\n\n\n\n

<\/div>\n","protected":false},"excerpt":{"rendered":"

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