Suppr超能文献

未来大流行病中的数据挑战。

The challenges of data in future pandemics.

机构信息

Department of Computer Science, University of Oxford, UK; The Open Data Institute, London, UK.

UKAEA Software Engineering Group, UK; Scottish COVID-19 Response Consortium, UK.

出版信息

Epidemics. 2022 Sep;40:100612. doi: 10.1016/j.epidem.2022.100612. Epub 2022 Jul 20.

Abstract

The use of data has been essential throughout the unfolding COVID-19 pandemic. We have needed it to populate our models, inform our understanding, and shape our responses to the disease. However, data has not always been easy to find and access, it has varied in quality and coverage, been difficult to reuse or repurpose. This paper reviews these and other challenges and recommends steps to develop a data ecosystem better able to deal with future pandemics by better supporting preparedness, prevention, detection and response.

摘要

在整个 COVID-19 大流行期间,数据的使用至关重要。我们需要数据来填充模型、加深理解并为疾病做出反应。然而,数据并不总是容易找到和获取的,其质量和覆盖范围各不相同,难以重复使用或重新利用。本文回顾了这些挑战和其他挑战,并提出了一些建议步骤,以通过更好地支持准备、预防、检测和应对,来开发一个更能应对未来大流行的数据集生态系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5efe/9297658/78a4b0674108/gr1_lrg.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验