基于病例的传染病监测存在挑战
Oliver Eales1,2, James M McCaw1,2, Freya M Shearer1,3
1Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Australia.
Royal Society open science
|August 29, 2024
概括
基于病例的传染病监测容易产生偏见,特别是当其他病原体引起类似症状时. 数学建模揭示了这些偏见如何影响感染发病率估计,影响公共卫生战略.
科学领域:
- 流行病学 流行病学
- 数学生物学 数学生物学
- 公共卫生 公共卫生
背景情况:
- 精确的传染病控制依赖于了解病原体传播动态.
- 感染发病率是传播动态的关键,由于未知的感染时间,通常会间接估计.
- 基于病例的监测,通过阳性测试识别受感染的个体,是常见的,但容易受到各种偏见的影响.
研究的目的:
- 开发一个数学框架来分析基于病例的传染病监测.
- 识别和量化共同监测指标中的潜在偏差.
- 突出与监测数据相似症状的共循环病原体的影响.
主要方法:
- 开发一个基于案例的监控的数学描述.
- 包括现实的流行病学参数和情景.
- 分析共同的监测指标 (例如病例数,检测阳性比例).
主要成果:
- 从基于案例的数据中获得的共同监测指标中存在重大偏差的证明.
- 识别具有相似症状概况的共循环病原体作为偏见的主要来源.
- 量化这些偏差如何影响感染发病率的估计.
结论:
- 基于病例的监测指标可能会因类似病原体的存在而严重扭曲.
- 未来的监控策略必须设计以减轻这些偏差,以获得准确的传输动态.
- 提高监测准确度将导致更有针对性和有效的公共卫生干预措施.
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