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

Bibliographic Data

ID15465674
AuthorsEmily Ying Yang Chan (0000-0002-8854-5093, Chinese University of Hong Kong, corresponding author), Debarati Guha‐sapir (0000-0002-2735-6707, Johns Hopkins University), Debarati Guha-Sapir (UCLouvain), Caroline Dubois (0000-0002-8810-4159, Chinese University of Hong Kong), Rajib Shaw (0000-0003-3153-1800, Keio University Shonan Fujisawa), C S Wong (0000-0002-4694-0976, Chinese University of Hong Kong)
Year2022
Volume19
Issue7
Pages3917-3917
Publication date2022-03-25
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph19073917
PMID35409599
OpenAlexW4221083388
LanguageEN
Citations received2
References cited6

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

Business · Community resilience · Data sharing · Economic growth · Economics · Emergency management · Environmental health · Environmental planning · Environmental resource management · Geography · Livelihood · Natural disaster · Natural hazard · Political science · Preparedness · Resilience (materials science · Risk analysis (engineering · Computer Science · Disaster Response and Management · Environmental Science · Food Security and Health in Diverse Populations · Medicine · Viral Infections and Outbreaks Research

  • Living in a pandemic

    Open Access•Elena Mondino, Anna Scolobig et al.•International Journal of Disaster…•2023

  • An empirical study of the effect of a flooding event caused by extreme rainfall on preventive behaviors against Covid-19

    Open Access•Chengcheng Liu, Qibin Lu et al.•Frontiers in Public Health•2022

  • Sociodemographic Predictors of Health Risk Perception, Attitude and Behavior Practices Associated with Health-Emergency Disaster Risk Management for Biological Hazards

    Open Access•Emily Ying Yang Chan, Zhe Huang et al.•International Journal of…•2020

  • Population Adherence to Infection Control Behaviors during Hong Kong’s First and Third Covid-19 Waves

    Open Access•Emily Ying Yang Chan, Jean H Kim et al.•International Journal of…•2021

Citations per year0.5
Citation span2022 - 2023 (2)
Highly citedNo

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