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A Data-informed Public Health Policy-Makers Platform

Author

Listed:
  • Dario Brdarić

    (Department for Disinfection, Disinsection and Deratization, Institute of Public Health for the Osijek Baranya County, 31000 Osijek, Croatia
    Department of Public Health, Humanities and Social Sciences in Biomedicine, Faculty of Dental Medicine and Health, J. J. Strossmayer University of Osijek, 31000 Osijek, Croatia)

  • Senka Samardžić

    (Department for Disinfection, Disinsection and Deratization, Institute of Public Health for the Osijek Baranya County, 31000 Osijek, Croatia)

  • Ivana Mihin Huskić

    (Department for Disinfection, Disinsection and Deratization, Institute of Public Health for the Osijek Baranya County, 31000 Osijek, Croatia)

  • Giorgos Dritsakis

    (Ear Institute, University College London, London WC1E 6BT, UK)

  • Jadran Sessa

    (Dipartimento di Informatica, Università degli Studi di Milano, 20133 Milano, Italy)

  • Mariola Śliwińska-Kowalska

    (Department of Physical Hazard, Nofer Institute of Occupational Medicine, 91-348 Łódź, Poland)

  • Małgorzata Pawlaczyk-Łuszczyńska

    (Department of Physical Hazard, Nofer Institute of Occupational Medicine, 91-348 Łódź, Poland)

  • Ioannis Basdekis

    (Department of Computer Science, City University of London, London EC1V 0HB, UK)

  • George Spanoudakis

    (Department of Computer Science, City University of London, London EC1V 0HB, UK)

Abstract

Hearing loss is a disease exhibiting a growing trend due to a number of factors, including but not limited to the mundane exposure to the noise and ever-increasing size of the older population. In the framework of a public health policymaking process, modeling of the hearing loss disease based on data is a key factor in alleviating the issues related to the disease and in issuing effective public health policies. First, the paper describes the steps of the data-driven policymaking process. Afterward, a scenario along with the part of the proposed platform responsible for supporting policymaking are presented. With the aim of demonstrating the capabilities and usability of the platform for the policy-makers, some initial results of preliminary analytics are presented in the framework of a policy-making process. Ultimately, the utility of the approach is validated throughout the results of the survey which was presented to the health system policy-makers involved in the policy development process in Croatia.

Suggested Citation

  • Dario Brdarić & Senka Samardžić & Ivana Mihin Huskić & Giorgos Dritsakis & Jadran Sessa & Mariola Śliwińska-Kowalska & Małgorzata Pawlaczyk-Łuszczyńska & Ioannis Basdekis & George Spanoudakis, 2020. "A Data-informed Public Health Policy-Makers Platform," IJERPH, MDPI, vol. 17(9), pages 1-17, May.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:3271-:d:355119
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    References listed on IDEAS

    as
    1. Sanjay Basu & Jason Andrews, 2013. "Complexity in Mathematical Models of Public Health Policies: A Guide for Consumers of Models," PLOS Medicine, Public Library of Science, vol. 10(10), pages 1-6, October.
    2. Homer, J.B. & Hirsch, G.B., 2006. "System dynamics modeling for public health: Background and opportunities," American Journal of Public Health, American Public Health Association, vol. 96(3), pages 452-458.
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    Cited by:

    1. Gwanggil Jeon & Abdellah Chehri, 2021. "Computing Techniques for Environmental Research and Public Health," IJERPH, MDPI, vol. 18(18), pages 1-4, September.

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