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CSOC 2020: Applied Informatics and Cybernetics in Intelligent Systems pp 177–190Cite as

CollaborativeHealth: Smart Technologies to Surveil Outbreaks of Infectious Diseases Through Direct and Indirect Citizen Participation

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1226))

Abstract

Early warning systems are essential to mitigate the consequences of outbreaks of infectious diseases, which causes millions of deaths every year. Surveillance systems collect data on epidemic-prone diseases to trigger prompt public health interventions. In recent years, these systems have improved significantly thanks to infodemiology, a recent research field that promotes the use of health-data collected from the Internet. However, early warning systems can be improved regarding the interpretability and confidentiality of the compiled evidences. In addition, they still rely heavily on human intervention to distinguish among confident and non-confident evidences. To solve these concerns we present CollaborativeHealth, an infodemiology platform that compiles evidence from (1) social networks, (2) public reports, and (3) voluntary citizen participation; and makes use of deep-learning technologies to extract knowledge regarding infectious diseases, their symptoms, or poor environment conditions what promote the propagation of these diseases. Finally, all the compiled evidence is available to health-professionals in real-time through a configurable dashboard. The validation of CollaborativeHealth was performed with a real use-case about monitoring infectious disease cases related to Zika, Dengue, Chikungunya, and Influenza in Ecuador.

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Acknowledgments

This work is being funded by CDTI and the European Regional Development Fund (FEDER/ERDF) through project CollaborativeHealth IDI-20180989.

Author information

Authors and Affiliations

  1. Facultad de Ciencias Matemáticas y Fí­sicas, Universidad de Guayaquil, Cdla. Universitaria Salvador Allende, Guayaquil, Ecuador

    Óscar Apolinario-Arzube

  2. VIAMATICA S.A., Edif. San Francisco 300, Córdova y Av. 9 de Octubre, 090313, Guayaquil, Ecuador

    Óscar Apolinario-Arzube, Harry Luna-Aveiga & José Jacinto Medina-Moreira

  3. Computer Science Department, Universidad Carlos III de Madrid, Madrid, Spain

    José Antonio Garcí­a-Dí­az & Rafael Valencia-Garcia

  4. Facultad de Informática, Universidad de Murcia, Campus de Espinardo, 30100, Murcia, Spain

    Sheila Pinto & Juan Miguel Gómez-Berbis

  5. DANTIA Tecnologí­a S.L., Parque Empresarial de Jerez 10, Calle de la Agricultura, 11407, Jerez de la Frontera, Cádiz, Spain

    José Ignacio Estrade-Cabrera

Authors
  1. Óscar Apolinario-Arzube
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  2. José Antonio Garcí­a-Dí­az
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  3. Sheila Pinto
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  4. Harry Luna-Aveiga
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  5. José Jacinto Medina-Moreira
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  6. Juan Miguel Gómez-Berbis
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  7. Rafael Valencia-Garcia
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  8. José Ignacio Estrade-Cabrera
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Corresponding author

Correspondence to José Antonio Garcí­a-Dí­az .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Apolinario-Arzube, Ó. et al. (2020). CollaborativeHealth: Smart Technologies to Surveil Outbreaks of Infectious Diseases Through Direct and Indirect Citizen Participation. In: Silhavy, R. (eds) Applied Informatics and Cybernetics in Intelligent Systems. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1226. Springer, Cham. https://doi.org/10.1007/978-3-030-51974-2_15

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