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在大流行威胁预警系统中进行综合生物-行为监测。

Integrated biological-behavioural surveillance in pandemic-threat warning systems.

机构信息

Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, United States of America (USA).

EcoHealth Alliance, New York, USA .

出版信息

Bull World Health Organ. 2017 Jan 1;95(1):62-68. doi: 10.2471/BLT.16.175984. Epub 2016 Nov 3.

Abstract

Economically and politically disruptive disease outbreaks are a hallmark of the 21st century. Although pandemics are driven by human behaviours, current surveillance systems for identifying pandemic threats are largely reliant on the monitoring of disease outcomes in clinical settings. Standardized integrated biological-behavioural surveillance could, and should, be used in community settings to complement such clinical monitoring. The usefulness of such an approach has already been demonstrated in studies on human immunodeficiency virus, where integrated surveillance contributed to a biologically based and quantifiable understanding of the behavioural risk factors associated with the transmission dynamics of the virus. When designed according to Strengthening the Reporting of Observational Studies in Epidemiology criteria, integrated surveillance requires that both behavioural risk factors - i.e. exposure variables - and disease-indicator outcome variables be measured in behavioural surveys. In the field of pandemic threats, biological outcome data could address the weaknesses of self-reported data collected in behavioural surveys. Data from serosurveys of viruses with pandemic potential, collected under non-outbreak conditions, indicate that serosurveillance could be used to predict future outbreaks. When conducted together, behavioural surveys and serosurveys could warn of future pandemics, potentially before the disease appears in clinical settings. Traditional disease-outcome surveillance must be frequent and ongoing to remain useful but behavioural surveillance remains informative even if conducted much less often, since behaviour change occurs slowly over time. Only through knowledge of specific behavioural risk factors can interventions and policies that can prevent the next pandemic be developed.

摘要

具有经济和政治破坏力的疾病暴发是 21 世纪的一个特征。虽然大流行是由人类行为驱动的,但目前用于识别大流行威胁的监测系统在很大程度上依赖于临床环境中疾病结果的监测。标准化的综合生物-行为监测可以而且应该在社区环境中用于补充这种临床监测。这种方法的有用性已经在人类免疫缺陷病毒的研究中得到了证明,在这些研究中,综合监测有助于从生物学角度和定量角度理解与病毒传播动态相关的行为风险因素。根据《流行病学观察研究报告的加强标准》进行设计时,综合监测要求在行为调查中同时测量行为风险因素(即暴露变量)和疾病指标结果变量。在大流行威胁领域,生物学结果数据可以解决行为调查中收集的自我报告数据的弱点。具有大流行潜力的病毒的血清学调查在非暴发情况下收集的数据表明,血清学监测可用于预测未来的暴发。当一起进行时,行为调查和血清学调查可以预警未来的大流行,甚至可能在疾病出现在临床环境之前。传统的疾病结果监测必须频繁且持续进行才能保持有用性,但即使行为监测的频率较低,它仍然具有信息性,因为行为变化是随着时间的推移而缓慢发生的。只有了解特定的行为风险因素,才能制定可以预防下一次大流行的干预措施和政策。

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