Vol. 1 No. 1 (2020): February
Point of View

Interactive, semi-automatized and open source computational model applied to respiratory viruses surveillance

Felipe Tomás Reyes Zaldívar
Pontificia Universidad Católica de Chile
Bio
Marcela Ferrés
Pontificia Universidad Católica de Chile; Red de Salud UC CHRISTUS.
Pablo Vial
Universidad del Desarrollo
Valeska Vollrath
Clínica Alemana
Rossanna Camponovo
Integramédica - BUPA
Luisa Montecinos
Integramédica - BUPA
Tamara Hirsch
Hospital de Enfermedades Infecciosas Dr. Lucio Córdova
Patricia Valenzuela
Hospital de Enfermedades Infecciosas Dr. Lucio Córdova
Cecilia Perret
Pontificia Universidad Católica de Chile

Published 2020-03-23

How to Cite

1.
Reyes Zaldívar FT, Ferrés M, Vial P, Vollrath V, Camponovo R, Montecinos L, Hirsch T, Valenzuela P, Perret C. Interactive, semi-automatized and open source computational model applied to respiratory viruses surveillance. Rev. Chilena. Infectol. [Internet]. 2020 Mar. 23 [cited 2025 Nov. 19];1(1). Available from: https://revinf.cl/index.php/revinf/article/view/562

Abstract

Acute respiratory infections (ARI) are an important cause of morbidity and mortality worldwide, affecting mainly children and the elderly. They are associated with a high economic burden, increased number of medical visits and hospitalizations. The surveillance of the circulation of respiratory viruses can reduce the health care associated costs, and to optimize the health response. A platform based on R and its package Shiny was designed, to create an interactive and friendly web interface for gathering, analysis and publication of the data. The data from the Chilean metropolitan respiratory viruses surveillance network, available since 2006, was uploaded into the platform. Using this platform, the researcher spends less than 1 minute to upload the data, and the analysis and publication is immediate, available to be seen by any user with a device connected to Internet, who can choose the variables to be displayed. With a very low cost, in a short time, and using the R programming language, it was possible to create a simple, and interactive platform, considerably decreasing the upload and analysis time, and increasing the impact and availability of this surveillance.