Implementación de un sistema de vigilancia sindrómica veterinario
Fecha
2018-06-24
Autores
Pino Llanes, Junior
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Editor
Universidad Central “Marta Abreu” de Las Villas
Resumen
La vigilancia sindrómica es una estrategia de investigación donde un equipo de un departamento de salud, asistido por un sistema automático de adquisición de alertas estadísticas, monitorea los indicadores de una enfermedad en tiempo real, o cerca del tiempo real, para detectar brotes de enfermedades antes de ser detectada por métodos tradicionales. Una de las principales estrategias que se usa en la vigilancia sindrómica es la predicción de series de tiempo basada en datos históricos. El objetivo principal de este trabajo de diploma es la implementación de una aplicación computacional que funcione como sistema de vigilancia sindrómica, basada en modelos ARIMA. Se obtuvo como resultado dicha aplicación, desarrollada en el lenguaje de programación Java usando potencialidades también del lenguaje de programación R, validando estadísticamente las predicciones obtenidas por la misma.
Syndromic surveillance is a research strategy where a team of a health department, assisted by an automatic system for acquiring statistical alerts, monitors the indicators of a disease in real time, or near real time, to detect outbreaks of diseases before to be detected by traditional methods. One of the main strategies used in syndromic surveillance is the prediction of time series based on historical data. The main objective of this diploma work is the implementation of a computational application that functions as a syndromic surveillance system, based on ARIMA models. This application was obtained as a result, developed in the Java programming language using potentials also from the programming language R, statistically validating the predictions obtained by it.
Syndromic surveillance is a research strategy where a team of a health department, assisted by an automatic system for acquiring statistical alerts, monitors the indicators of a disease in real time, or near real time, to detect outbreaks of diseases before to be detected by traditional methods. One of the main strategies used in syndromic surveillance is the prediction of time series based on historical data. The main objective of this diploma work is the implementation of a computational application that functions as a syndromic surveillance system, based on ARIMA models. This application was obtained as a result, developed in the Java programming language using potentials also from the programming language R, statistically validating the predictions obtained by it.
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Palabras clave
Vigilancia Sindrómica, Enfermedad, Modelos ARIMA, Syndromic Surveillance, Disease, Arima Models