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Challenges of Data Availability and Use in Conducting Health-EDRM Research in a Post-COVID-19 World

Author

Listed:
  • Emily Ying Yang Chan

    (Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response, Hong Kong, China
    Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK
    JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
    GX Foundation, Hong Kong, China)

  • Debarati Guha-Sapir

    (Centre for Research on the Epidemiology of Disasters, Institute of Health and Society, Université Catholique de Louvain, 1200 Brussels, Belgium
    Center for Humanitarian Health, Johns Hopkins University, Baltimore, MD 21205, USA)

  • Caroline Dubois

    (JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
    GX Foundation, Hong Kong, China)

  • Rajib Shaw

    (Graduate School of Media and Governance, Keio University, Fujisawa 252-0882, Japan)

  • Chi Sing Wong

    (Collaborating Centre for Oxford University and CUHK for Disaster and Medical Humanitarian Response, Hong Kong, China
    JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China)

Abstract

Disasters disrupt communication channels, infrastructure, and overburden health systems. This creates unique challenges to the functionality of surveillance tools, data collection systems, and information sharing platforms. The WHO Health Emergency and Disaster Risk Management (Health-EDRM) framework highlights the need for appropriate data collection, data interpretation, and data use from individual, community, and global levels. The COVID-19 crisis has evolved the way hazards and risks are viewed. No longer as a linear event but as a protracted hazard, with cascading and compound risks that affect communities facing complex risks such as climate-related disasters or urban growth. The large-scale disruptions of COVID-19 show that disaster data must evolve beyond mortality and frequency of events, in order to encompass the impact on the livelihood of communities, differentiated between population groups. This includes relative economic losses and psychosocial damage. COVID-19 has created a global opportunity to review how the scientific community classifies data, and how comparable indicators are selected to inform evidence-based resilience building and emergency preparedness. A shift into microlevel data, and regional-level information sharing is necessary to tailor community-level interventions for risk mitigation and disaster preparedness. Real-time data sharing, open governance, cross-organisational, and inter-platform collaboration are necessary not just in Health-EDRM and control of biological hazards, but for all natural hazards and man-made disasters.

Suggested Citation

  • Emily Ying Yang Chan & Debarati Guha-Sapir & Caroline Dubois & Rajib Shaw & Chi Sing Wong, 2022. "Challenges of Data Availability and Use in Conducting Health-EDRM Research in a Post-COVID-19 World," IJERPH, MDPI, vol. 19(7), pages 1-5, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:7:p:3917-:d:779423
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    References listed on IDEAS

    as
    1. Emily Ying Yang Chan & Zhe Huang & Eugene Siu Kai Lo & Kevin Kei Ching Hung & Eliza Lai Yi Wong & Samuel Yeung Shan Wong, 2020. "Sociodemographic Predictors of Health Risk Perception, Attitude and Behavior Practices Associated with Health-Emergency Disaster Risk Management for Biological Hazards: The Case of COVID-19 Pandemic i," IJERPH, MDPI, vol. 17(11), pages 1-18, May.
    2. Emily Ying Yang Chan & Jean H. Kim & Kin-on Kwok & Zhe Huang & Kevin Kei Ching Hung & Eliza Lai Yi Wong & Eric Kam Pui Lee & Samuel Yeung Shan Wong, 2021. "Population Adherence to Infection Control Behaviors during Hong Kong’s First and Third COVID-19 Waves: A Serial Cross-Sectional Study," IJERPH, MDPI, vol. 18(21), pages 1-17, October.
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