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呼吁将公民科学纳入大流行病的防备和应对工作:不只是数据收集。

A call for citizen science in pandemic preparedness and response: beyond data collection.

机构信息

International Digital Health & AI Research Collaborative (I-DAIR), Geneva, Switzerland

Trivedi School of Biosciences, Ashoka University, Sonepath, Haryana, India.

出版信息

BMJ Glob Health. 2022 Jun;7(6). doi: 10.1136/bmjgh-2022-009389.

Abstract

The COVID-19 pandemic has underlined the need to partner with the community in pandemic preparedness and response in order to enable trust-building among stakeholders, which is key in pandemic management. Citizen science, defined here as a practice of public participation and collaboration in all aspects of scientific research to increase knowledge and build trust with governments and researchers, is a crucial approach to promoting community engagement. By harnessing the potential of digitally enabled citizen science, one could translate data into accessible, comprehensible and actionable outputs at the population level. The application of citizen science in health has grown over the years, but most of these approaches remain at the level of participatory data collection. This narrative review examines citizen science approaches in participatory data generation, modelling and visualisation, and calls for truly participatory and co-creation approaches across all domains of pandemic preparedness and response. Further research is needed to identify approaches that optimally generate short-term and long-term value for communities participating in population health. Feasible, sustainable and contextualised citizen science approaches that meaningfully engage affected communities for the long-term will need to be inclusive of all populations and their cultures, comprehensive of all domains, digitally enabled and viewed as a key component to allow trust-building among the stakeholders. The impact of COVID-19 on people's lives has created an opportune time to advance people's agency in science, particularly in pandemic preparedness and response.

摘要

新冠疫情突出表明,有必要与社区合作,做好大流行防备和应对工作,以便在利益攸关方之间建立信任,这是大流行管理的关键。公民科学在这里被定义为公众参与和协作科学研究的各个方面的实践,以增进政府和研究人员之间的信任,是促进社区参与的关键方法。通过利用数字公民科学的潜力,人们可以将数据转化为在人口层面上易于理解、易于理解和可操作的产出。公民科学在卫生领域的应用多年来一直在增长,但这些方法大多仍停留在参与式数据收集的层面上。这篇叙事性综述考察了公民科学在参与式数据生成、建模和可视化方面的方法,并呼吁在大流行防备和应对的所有领域采用真正的参与式和共同创造方法。需要进一步研究确定哪些方法可以为参与人口健康的社区创造短期和长期的最佳价值。可行、可持续和切合实际的公民科学方法需要长期以来有意义地让受影响的社区参与其中,这些方法要包容所有人群及其文化,全面涵盖所有领域,实现数字化,并被视为建立利益攸关方之间信任的关键组成部分。新冠疫情对人们生活的影响为提高人们在科学,特别是在大流行防备和应对方面的能动性创造了一个契机。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/204a/9237878/64d240062767/bmjgh-2022-009389f01.jpg

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