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认知准备

Epistemic preparedness.

作者信息

Anderson Warwick, Lancaster Kari, van Wichelen Sonja, Abimbola Seye, Ankeny Rachel A, Engelmann Lukas, Fearnley Lyle, Giles-Vernick Tamara, Hegarty Benjamin, Jephcott Freya L, Ludovice Nicolo P, Roitman Janet, Steere-Williams Jacob, Stoove Mark, Viaña John Noel, Waldby Catherine, Yang Rachel

机构信息

School of Social and Political Sciences and Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia

Centre for Health Equity, The University of Melbourne, Melbourne, Victoria, Australia.

出版信息

BMJ Glob Health. 2025 Jun 22;10(6):e018719. doi: 10.1136/bmjgh-2024-018719.

DOI:10.1136/bmjgh-2024-018719
PMID:40550575
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12184354/
Abstract

Preparedness strategies for emergent infectious diseases have focused on microbial surveillance, medical stockpiling and healthcare infrastructure resilience. But what does it mean to be or cognitively prepared for the next disease outbreak? Taking stock of lessons for data practices and statistical modelling in the wake of COVID-19, we propose a reconceptualising of preparedness in global health, focusing on ecological and sociological configurations or framings rather than resorting to reductive 'crisis technologies'. We address three problem areas: data collection and sharing, outbreak modelling and the spatiotemporal structuring of analysis and intervention. We take these as illustrative of troubling effects of conceptual inflexibility. We inquire into alternative data practices and more complex epidemiological framings. This refiguring of our cognitive toolkit implies working through colonial legacies and national limitations embedded in governance of epidemiological reasoning. Epistemic preparedness-focusing on a more diverse, equitable and inclusive stocktaking as much as stockpiling-provides a reliable foundation for future disease outbreak management.

摘要

突发传染病的防范策略一直聚焦于微生物监测、医疗储备和医疗保健基础设施的恢复能力。但对于下一次疾病爆发,具备认知准备意味着什么呢?在新冠疫情之后总结数据实践和统计建模的经验教训,我们提议重新构想全球卫生防范,关注生态和社会结构或框架,而非诉诸简化的“危机技术”。我们探讨三个问题领域:数据收集与共享、疫情建模以及分析与干预的时空结构。我们将这些视为概念僵化带来的不良影响的例证。我们探究替代数据实践和更复杂的流行病学框架。这种对我们认知工具包的重新塑造意味着要克服流行病学推理治理中所固有的殖民遗产和国家局限性。认知准备——不仅关注储备,还注重更具多样性、公平性和包容性的评估——为未来疾病爆发管理提供了可靠基础。

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本文引用的文献

1
A pandemic of metrics.指标大流行。
Med Anthropol Q. 2024 Jun;38(2):149-163. doi: 10.1111/maq.12842. Epub 2024 Feb 28.
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The new pandemic treaty: Are we in safer hands? Probably not.新的大流行条约:我们能更安心吗?可能不会。
BMJ. 2024 Feb 22;384:q477. doi: 10.1136/bmj.q477.
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FAIR, ethical, and coordinated data sharing for COVID-19 response: a scoping review and cross-sectional survey of COVID-19 data sharing platforms and registries.公平、合乎道德且协调一致的数据共享以应对 COVID-19:对 COVID-19 数据共享平台和注册中心的范围界定审查和横断面调查。
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Uncomfortable science: How mathematical models, and consensus, come to be in public policy.令人不适的科学:数学模型和共识是如何成为公共政策的。
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Endemic fatalism and why it will not resolve COVID-19.地方性宿命论及其为何无法解决新冠疫情
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Expertise from the humanities and social sciences is essential for governmental responses to COVID-19.人文社会科学方面的专业知识对于政府应对新冠疫情至关重要。
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