Application of Pandemic Intelligence in Dynamic Data in Taiwan

Tzu-Yin Chang, Wen-Ray Su, Hongey Chen, Ming-Wey Huang and Lu-Yen A. Chen
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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

IJERPH, 2021, vol. 18, issue 18, 1-13

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.

Keywords: COVID-19; data integration; dynamic intelligence; pandemic management (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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