Suppr超能文献

连接生物监测门户与机构分析师国际网络以检测生物威胁。

Interfacing a biosurveillance portal and an international network of institutional analysts to detect biological threats.

作者信息

Riccardo Flavia, Shigematsu Mika, Chow Catherine, McKnight C Jason, Linge Jens, Doherty Brian, Dente Maria Grazia, Declich Silvia, Barker Mike, Barboza Philippe, Vaillant Laetitia, Donachie Alastair, Mawudeku Abla, Blench Michael, Arthur Ray

出版信息

Biosecur Bioterror. 2014 Nov-Dec;12(6):325-36. doi: 10.1089/bsp.2014.0031.

Abstract

The Early Alerting and Reporting (EAR) project, launched in 2008, is aimed at improving global early alerting and risk assessment and evaluating the feasibility and opportunity of integrating the analysis of biological, chemical, radionuclear (CBRN), and pandemic influenza threats. At a time when no international collaborations existed in the field of event-based surveillance, EAR's innovative approach involved both epidemic intelligence experts and internet-based biosurveillance system providers in the framework of an international collaboration called the Global Health Security Initiative, which involved the ministries of health of the G7 countries and Mexico, the World Health Organization, and the European Commission. The EAR project pooled data from 7 major internet-based biosurveillance systems onto a common portal that was progressively optimized for biological threat detection under the guidance of epidemic intelligence experts from public health institutions in Canada, the European Centre for Disease Prevention and Control, France, Germany, Italy, Japan, the United Kingdom, and the United States. The group became the first end users of the EAR portal, constituting a network of analysts working with a common standard operating procedure and risk assessment tools on a rotation basis to constantly screen and assess public information on the web for events that could suggest an intentional release of biological agents. Following the first 2-year pilot phase, the EAR project was tested in its capacity to monitor biological threats, proving that its working model was feasible and demonstrating the high commitment of the countries and international institutions involved. During the testing period, analysts using the EAR platform did not miss intentional events of a biological nature and did not issue false alarms. Through the findings of this initial assessment, this article provides insights into how the field of epidemic intelligence can advance through an international network and, more specifically, how it was further developed in the EAR project.

摘要

早期预警与报告(EAR)项目于2008年启动,旨在改善全球早期预警和风险评估,并评估整合生物、化学、放射性核素(CBRN)和大流行性流感威胁分析的可行性和机遇。在基于事件的监测领域尚无国际合作之时,EAR的创新方法在一项名为全球卫生安全倡议的国际合作框架内,让传染病情报专家和基于互联网的生物监测系统供应商共同参与,该倡议涉及七国集团国家和墨西哥的卫生部、世界卫生组织以及欧盟委员会。EAR项目将来自7个主要基于互联网的生物监测系统的数据汇集到一个通用门户上,在加拿大、欧洲疾病预防控制中心、法国、德国、意大利、日本、英国和美国的公共卫生机构的传染病情报专家指导下,该门户逐步针对生物威胁检测进行了优化。该团队成为EAR门户的首批最终用户,构成了一个分析人员网络,他们按照统一的标准操作程序和风险评估工具轮流工作,持续筛选和评估网络上有关可能暗示故意释放生物制剂事件的公共信息。在最初的两年试点阶段之后,EAR项目对其监测生物威胁的能力进行了测试,证明其工作模式可行,并展示了相关国家和国际机构的高度投入。在测试期间,使用EAR平台的分析人员没有错过任何具有生物性质的故意事件,也没有发出误报。通过这一初步评估的结果,本文深入探讨了传染病情报领域如何通过国际网络取得进展,更具体地说,它在EAR项目中是如何进一步发展的。

相似文献

2
Public Health Surveillance: At the Core of the Global Health Security Agenda.
Health Secur. 2016 May-Jun;14(3):185-8. doi: 10.1089/hs.2016.0002.
3
An overview of internet biosurveillance.
Clin Microbiol Infect. 2013 Nov;19(11):1006-13. doi: 10.1111/1469-0691.12273. Epub 2013 Jun 21.
4
Strengthening Surveillance for Health Security Threats: The Time Is Now.
Health Secur. 2016 May-Jun;14(3):109-10. doi: 10.1089/hs.2016.0051.
5
Assessing the continuum of event-based biosurveillance through an operational lens.
Biosecur Bioterror. 2012 Mar;10(1):131-41. doi: 10.1089/bsp.2011.0096. Epub 2012 Feb 9.
6
Fighting trafficking of falsified and substandard medicinal products in Russia.
Int J Risk Saf Med. 2015;27 Suppl 1:S37-40. doi: 10.3233/JRS-150681.
7
Event-Based Surveillance During EXPO Milan 2015: Rationale, Tools, Procedures, and Initial Results.
Health Secur. 2016 May-Jun;14(3):161-72. doi: 10.1089/hs.2015.0075.
8
Digital disease detection: A systematic review of event-based internet biosurveillance systems.
Int J Med Inform. 2017 May;101:15-22. doi: 10.1016/j.ijmedinf.2017.01.019. Epub 2017 Feb 8.

引用本文的文献

1
Mathematical models and analysis tools for risk assessment of unnatural epidemics: a scoping review.
Front Public Health. 2024 May 2;12:1381328. doi: 10.3389/fpubh.2024.1381328. eCollection 2024.
2
Bio-safety and bio-security: A major global concern for ongoing COVID-19 pandemic.
Saudi J Biol Sci. 2022 Jan;29(1):132-139. doi: 10.1016/j.sjbs.2021.08.060. Epub 2021 Aug 30.
4
Identifying potential emerging threats through epidemic intelligence activities-looking for the needle in the haystack?
Int J Infect Dis. 2019 Dec;89:146-153. doi: 10.1016/j.ijid.2019.10.011. Epub 2019 Oct 16.
5
Making Online Outbreak Surveillance Work for all.
Ann Glob Health. 2017 May-Aug;83(3-4):625-629. doi: 10.1016/j.aogh.2017.09.002. Epub 2017 Nov 6.
6
Event-Based Surveillance During EXPO Milan 2015: Rationale, Tools, Procedures, and Initial Results.
Health Secur. 2016 May-Jun;14(3):161-72. doi: 10.1089/hs.2015.0075.

本文引用的文献

1
Selecting essential information for biosurveillance--a multi-criteria decision analysis.
PLoS One. 2014 Jan 29;9(1):e86601. doi: 10.1371/journal.pone.0086601. eCollection 2014.
2
An overview of internet biosurveillance.
Clin Microbiol Infect. 2013 Nov;19(11):1006-13. doi: 10.1111/1469-0691.12273. Epub 2013 Jun 21.
4
Event-based internet biosurveillance: relation to epidemiological observation.
Emerg Themes Epidemiol. 2012 Jun 18;9(1):4. doi: 10.1186/1742-7622-9-4.
5
Landscape of international event-based biosurveillance.
Emerg Health Threats J. 2010;3:e3. doi: 10.3134/ehtj.10.003. Epub 2010 Feb 19.
6
Global capacity for emerging infectious disease detection.
Proc Natl Acad Sci U S A. 2010 Dec 14;107(50):21701-6. doi: 10.1073/pnas.1006219107. Epub 2010 Nov 29.
7
The nature of international health security.
Asia Pac J Clin Nutr. 2009;18(4):679-83.
8
Use of unstructured event-based reports for global infectious disease surveillance.
Emerg Infect Dis. 2009 May;15(5):689-95. doi: 10.3201/eid1505.081114.
10
BioCaster: detecting public health rumors with a Web-based text mining system.
Bioinformatics. 2008 Dec 15;24(24):2940-1. doi: 10.1093/bioinformatics/btn534. Epub 2008 Oct 15.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验