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.
Int J Environ Res Public Health. 2022 Mar 25;19(7):3917. doi: 10.3390/ijerph19073917.
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.
灾害会破坏通讯渠道、基础设施，并使医疗系统不堪重负。这为监测工具、数据收集系统和信息共享平台的功能带来了独特的挑战。世界卫生组织（WHO）的卫生应急和灾害风险管理（Health-EDRM）框架强调了从个人、社区和全球层面适当收集、解释和利用数据的必要性。新冠疫情危机改变了人们对危害和风险的看法。危害和风险不再被视为线性事件，而是一种持续存在的风险，具有连锁和复合风险，影响到面临复杂风险的社区，如与气候相关的灾害或城市发展。新冠疫情的大规模破坏表明，灾害数据必须超越事件的死亡率和频率进行发展，以涵盖对社区生计的影响，区分不同人群。这包括相对经济损失和心理社会损害。新冠疫情为我们提供了一个全球机会，可以审查科学界如何对数据进行分类，以及如何选择可比指标，为基于证据的弹性建设和应急准备提供信息。需要转向微观数据和区域信息共享，以便为风险缓解和备灾制定适合社区层面的干预措施。实时数据共享、开放治理、跨组织和跨平台合作不仅对于卫生应急和生物危害控制是必要的，对于所有自然灾害和人为灾害也是必要的。
