通过开源情报识别的未知原因疫情的全球流行病学,2020-2022年
Emerging infectious diseases
|February 21, 2025
概括
开源情报 (OSINT) 综合征监测提供了早期疫情检测,特别是在未知原因和资源较差的环境中. EPIWATCH比传统方法更早地发现了许多疫情,改善了全球卫生安全.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 传染病监测 传染病监测 传染病
背景情况:
- 传统的流行病监测依赖于延迟确诊病例.
- 局限性包括延迟报告和未计数病例.
- 新出现的传染病需要新的监测方法.
研究的目的:
- 用基于人工智能的OSINT来描述310个未知原因的全球流行病学.
- 评估OSINT的及时性和实用性,用于早期发现疫情爆发.
- 突出OSINT在资源贫困环境中的作用.
主要方法:
- 使用基于人工智能的OSINT预警系统EPIWATCH.
- 从2019年12月31日到2023年1月1日,分析了310起原因不明的疫情.
- 将OSINT产生的爆发信号与官方报告时间表进行了比较.
主要成果:
- OSINT比官方消息来源更早地发出了疫情的信号,并且在诊断之前.
- 310次爆发与75,968例人类病例和4,235例死亡有关.
- 只有14%的爆发病例被确定为病因,低收入/中等收入经济体的发病率较低.
结论:
- 基于OSINT的综合征监测比传统方法具有显著的优势.
- 它为疫情提供了至关重要的早期警告,特别是那些原因不明的疫情.
- 对于在资源有限的地区加强监视,OSINT特别有价值.
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