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Application of Pandemic Intelligence in Dynamic Data in Taiwan

Author

Listed:
  • Tzu-Yin Chang

    (National Science and Technology Center for Disaster Reduction, New Taipei 23143, Taiwan)

  • Wen-Ray Su

    (National Science and Technology Center for Disaster Reduction, New Taipei 23143, Taiwan)

  • Hongey Chen

    (National Science and Technology Center for Disaster Reduction, New Taipei 23143, Taiwan)

  • Ming-Wey Huang

    (National Science and Technology Center for Disaster Reduction, New Taipei 23143, Taiwan)

  • Lu-Yen A. Chen

    (Institute of Clinical Nursing, School of Nursing, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan)

Abstract

Taiwan was successful in containing the spread of the novel coronavirus (COVID-19) in 2020. One major factor in this success was the compilation and provision of comprehensive information about the pandemic. The present study proposes a pandemic intelligence system that provides data on the number of epidemic prevention professionals in each county and city, as well as daily confirmed cases, the demographics of the confirmed cases, and available resources (negative-pressure room beds and artificial ventilation apparatuses) in hospitals. Furthermore, the system provides the location of pharmacies selling masks and their current inventories, as well as the distribution of crowds at popular tourist destinations and social-distance monitoring. The most frequently used map layer in the thematic map of the pandemic is that of crowd distribution during the study period from March 2020 until the end of the same year. The case study used in this investigation for applying the system is represented by the 4-day weekend for Tomb-Sweeping Day of 2020. Through the real-time analysis of dynamic data and the integration of intelligence, the system offers a clear insight into changes in relevant information and, thus, enables the preemptive deployment of control measures by the county/city governments regarding pandemic management.

Suggested Citation

  • Tzu-Yin Chang & Wen-Ray Su & Hongey Chen & Ming-Wey Huang & Lu-Yen A. Chen, 2021. "Application of Pandemic Intelligence in Dynamic Data in Taiwan," IJERPH, MDPI, vol. 18(18), pages 1-13, September.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:18:p:9925-:d:639950
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    References listed on IDEAS

    as
    1. Sophia Chen & Ms. Deniz O Igan & Mr. Nicola Pierri & Mr. Andrea F Presbitero, 2020. "Tracking the Economic Impact of COVID-19 and Mitigation Policies in Europe and the United States," IMF Working Papers 2020/125, International Monetary Fund.
    2. Uxue Alfonso Viguria & Núria Casamitjana, 2021. "Early Interventions and Impact of COVID-19 in Spain," IJERPH, MDPI, vol. 18(8), pages 1-15, April.
    3. Felix Beierle & Johannes Schobel & Carsten Vogel & Johannes Allgaier & Lena Mulansky & Fabian Haug & Julian Haug & Winfried Schlee & Marc Holfelder & Michael Stach & Marc Schickler & Harald Baumeister, 2021. "Corona Health—A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(14), pages 1-19, July.
    Full references (including those not matched with items on IDEAS)

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