Department of Health security, Finish Institute for Health and Welfare, Helsinki, Finland.
Department of Public Health, Institute of tropical medicine, Antwerp, Belgium.
BMC Public Health. 2023 Aug 4;23(1):1488. doi: 10.1186/s12889-023-16396-y.
Epidemic Intelligence (EI) encompasses all activities related to early identification, verification, analysis, assessment, and investigation of health threats. It integrates an indicator-based (IBS) component using systematically collected surveillance data, and an event-based component (EBS), using non-official, non-verified, non-structured data from multiple sources. We described current EI practices in Europe by conducting a survey of national Public Health (PH) and Animal Health (AH) agencies. We included generic questions on the structure, mandate and scope of the institute, on the existence and coordination of EI activities, followed by a section where respondents provided a description of EI activities for three diseases out of seven disease models. Out of 81 gatekeeper agencies from 41 countries contacted, 34 agencies (42%) from 26 (63%) different countries responded, out of which, 32 conducted EI activities. Less than half (15/32; 47%) had teams dedicated to EI activities and 56% (18/34) had Standard Operating Procedures (SOPs) in place. On a national level, a combination of IBS and EBS was the most common data source. Most respondents monitored the epidemiological situation in bordering countries, the rest of Europe and the world. EI systems were heterogeneous across countries and diseases. National IBS activities strongly relied on mandatory laboratory-based surveillance systems. The collection, analysis and interpretation of IBS information was performed manually for most disease models. Depending on the disease, some respondents did not have any EBS activity. Most respondents conducted signal assessment manually through expert review. Cross-sectoral collaboration was heterogeneous. More than half of the responding institutes collaborated on various levels (data sharing, communication, etc.) with neighbouring countries and/or international structures, across most disease models. Our findings emphasise a notable engagement in EI activities across PH and AH institutes of Europe, but opportunities exist for better integration, standardisation, and automatization of these efforts. A strong reliance on traditional IBS and laboratory-based surveillance systems, emphasises the key role of in-country laboratories networks. EI activities may benefit particularly from investments in cross-border collaboration, the development of methods that can automatise signal assessment in both IBS and EBS data, as well as further investments in the collection of EBS data beyond scientific literature and mainstream media.
疫情情报学涵盖与早期识别、验证、分析、评估和调查健康威胁相关的所有活动。它整合了基于指标的(IBS)组件,使用系统收集的监测数据,以及基于事件的组件(EBS),使用来自多个来源的非官方、未经核实、非结构化的数据。我们通过对国家公共卫生(PH)和动物健康(AH)机构进行调查,描述了欧洲当前的疫情情报学实践。我们在调查中纳入了关于研究所结构、任务和范围、疫情情报学活动的存在和协调的一般性问题,然后要求受访者就七个疾病模型中的三种疾病描述疫情情报学活动。在联系的 81 个网关机构中,来自 26 个不同国家的 34 个机构(42%)做出了回应,其中 32 个机构开展了疫情情报学活动。不到一半(15/32;47%)的机构有专门从事疫情情报学活动的团队,56%(18/34)有标准作业程序(SOPs)。在国家层面上,IBS 和 EBS 的组合是最常见的数据来源。大多数受访者监测边境国家、欧洲其他地区和世界的流行病学情况。各国的疫情情报学系统各不相同,针对不同疾病也存在差异。国家 IBS 活动严重依赖强制性的基于实验室的监测系统。大多数疾病模型都通过手动收集、分析和解释 IBS 信息。根据疾病的不同,一些受访者没有任何 EBS 活动。大多数受访者通过专家审查手动进行信号评估。跨部门合作存在差异。超过一半的参与机构在大多数疾病模型中与邻国和/或国际机构在各个层面(数据共享、沟通等)进行合作。我们的发现强调了欧洲 PH 和 AH 机构在疫情情报学活动方面的显著参与,但在这些努力的整合、标准化和自动化方面仍存在机会。对传统 IBS 和基于实验室的监测系统的严重依赖,强调了国内实验室网络的关键作用。疫情情报学活动特别受益于跨境合作的投资、可以在 IBS 和 EBS 数据中自动评估信号的方法的开发,以及对超越科学文献和主流媒体的 EBS 数据的进一步投资。