流行病和流行病情报的数据集成和综合。

Q2 Biochemistry, Genetics and Molecular Biology
Barbara Tornimbene, Zoila Beatriz Leiva Rioja, Manoel Barral-Netto, Carlos Castillo-Salgado, Irena Djordjevic, Moritz Kraemer, Martina McMenamin, Oliver Morgan
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引用次数: 0

摘要

2019冠状病毒病大流行凸显了临床研究和流行病学分析所需的实时数据生成和管理方面的重大障碍。大流行过去三年后,对数据整合困难的反思为改进应急准备工作提供了潜力。世卫组织大流行病和流行病情报论坛第四届会议力求报告全球主要机构在数据整合和综合方面的经验,目的是确定有效整合的解决办法。数据整合的定义是将异质来源组合成一个有凝聚力的系统,它允许将流行病学数据与社会经济决定因素等背景因素结合起来,以更全面地了解疾病模式。该方法对于预测疫情、确定疾病负担和评估干预措施至关重要。使用上下文信息可改善实时情报和风险评估,从而加快疫情应对。本报告反映了人们日益认识到数据整合在提高公共卫生情报和准备方面的重要性,并举例说明了全球机构如何加强应对这一需求的举措。然而,障碍仍然存在,包括互操作性、数据标准化和道德考虑。未来数据整合工作的成功将取决于共同技术和法律框架的发展、全球合作的促进以及敏感数据的保护。最终,有效的数据整合有可能改变公共卫生情报和我们成功应对未来流行病的方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data integration and synthesis for pandemic and epidemic intelligence.

The COVID-19 pandemic highlighted substantial obstacles in real-time data generation and management needed for clinical research and epidemiological analysis. Three years after the pandemic, reflection on the difficulties of data integration offers potential to improve emergency preparedness. The fourth session of the WHO Pandemic and Epidemic Intelligence Forum sought to report the experiences of key global institutions in data integration and synthesis, with the aim of identifying solutions for effective integration. Data integration, defined as the combination of heterogeneous sources into a cohesive system, allows for combining epidemiological data with contextual elements such as socioeconomic determinants to create a more complete picture of disease patterns. The approach is critical for predicting outbreaks, determining disease burden, and evaluating interventions. The use of contextual information improves real-time intelligence and risk assessments, allowing for faster outbreak responses. This report captures the growing acknowledgment of data integration importance in boosting public health intelligence and readiness and show examples of how global institutions are strengthening initiatives to respond to this need. However, obstacles persist, including interoperability, data standardization, and ethical considerations. The success of future data integration efforts will be determined by the development of a common technical and legal framework, the promotion of global collaboration, and the protection of sensitive data. Ultimately, effective data integration can potentially transform public health intelligence and our way to successfully respond to future pandemics.

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来源期刊
BMC Proceedings
BMC Proceedings Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
3.50
自引率
0.00%
发文量
6
审稿时长
10 weeks
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