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.