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用于行动的数据——丹麦新冠病毒自动化监测系统的描述及经验教训,2020年1月至2024年6月

Data for action - description of the automated COVID-19 surveillance system in Denmark and lessons learnt, January 2020 to June 2024.

作者信息

Witteveen-Freidl Gudrun, Lauenborg Møller Karina, Voldstedlund Marianne, Gubbels Sophie

机构信息

Department of Data Integration and Analysis, Infectious Disease Preparedness, Statens Serum Institut, Copenhagen, Denmark.

出版信息

Epidemiol Infect. 2025 Mar 14;153:e58. doi: 10.1017/S0950268825000263.

DOI:10.1017/S0950268825000263
PMID:40082077
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12001143/
Abstract

Denmark is one of the leading countries in establishing digital solutions in the health sector. When SARS-CoV-2 arrived in February 2020, a real-time surveillance system could be rapidly built on existing infrastructure, This rapid data integration for COVID-19 surveillance enabled a data-driven response. Here we describe (a) the setup of the automated, real-time surveillance and vaccination monitoring system for COVID-19 in Denmark, including primary stakeholders, data sources, and algorithms, (b) describe outputs for various stakeholders, (c) how outputs were used for action and (d) reflect on challenges and lessons learnt. Outputs were tailored to four main stakeholder groups: four outputs provided direct information to individual citizens, four to complementary systems and researchers, 25 to decision-makers, and 15 informed the public, aiding transparency. Core elements in infrastructure needed for automated surveillance had been in place for more than a decade. The COVID-19 epidemic was a pressure test that allowed us to explore the system's potential and identify challenges for future pandemic preparedness. The system described here constitutes a model for the future infectious disease surveillance in Denmark. With the current pandemic threat posed by avian influenza viruses, lessons learnt from the COVID-19 pandemic remain topical and relevant.

摘要

丹麦是在卫生部门建立数字解决方案的领先国家之一。2020年2月新冠病毒出现时,能够在现有基础设施上迅速建立起实时监测系统。这种用于新冠疫情监测的快速数据整合实现了数据驱动的应对措施。在此,我们描述:(a)丹麦新冠病毒自动化实时监测和疫苗接种监测系统的设置,包括主要利益相关者、数据来源和算法;(b)描述针对不同利益相关者的产出;(c)产出如何用于行动;以及(d)反思挑战和经验教训。产出针对四个主要利益相关者群体进行了定制:四项产出为个体公民提供直接信息,四项为补充系统和研究人员提供信息,25项为决策者提供信息,15项向公众通报情况,有助于提高透明度。自动化监测所需基础设施的核心要素已经存在了十多年。新冠疫情是一次压力测试,使我们能够探索该系统的潜力,并确定未来大流行防范的挑战。这里描述的系统构成了丹麦未来传染病监测的一个模式。鉴于目前禽流感病毒构成的大流行威胁,从新冠疫情中吸取的经验教训仍然具有现实意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3ec/12001143/b1c8bd79a5fb/S0950268825000263_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3ec/12001143/3ae516a212a7/S0950268825000263_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3ec/12001143/b1c8bd79a5fb/S0950268825000263_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3ec/12001143/3ae516a212a7/S0950268825000263_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3ec/12001143/b1c8bd79a5fb/S0950268825000263_fig2.jpg

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