Dalla Lana School of Public Health, University of Toronto, 155 College Street, 6th Floor, Toronto, ON, MT5 3M7, Canada.
BMC Public Health. 2009 Dec 24;9:488. doi: 10.1186/1471-2458-9-488.
Community quarantine is controversial, and the decision to use and prepare for it should be informed by specific quantitative evidence of benefit. Case-study reports on 2002-2004 SARS outbreaks have discussed the role of quarantine in the community in transmission. However, this literature has not yielded quantitative estimates of the reduction in secondary cases attributable to quarantine as would be seen in other areas of health policy and cost-effectiveness analysis.
Using data from the 2003 Ontario, Canada, SARS outbreak, two novel expressions for the impact of quarantine are presented. Secondary Case Count Difference (SCCD) reflects reduction in the average number of transmissions arising from a SARS case in quarantine, relative to not in quarantine, at onset of symptoms. SCCD was estimated using Poisson and negative binomial regression models (with identity link function) comparing the number of secondary cases to each index case for quarantine relative to non-quarantined index cases. The inverse of this statistic is proposed as the number needed to quarantine (NNQ) to prevent one additional secondary transmission.
Our estimated SCCD was 0.133 fewer secondary cases per quarantined versus non-quarantined index case; and a NNQ of 7.5 exposed individuals to be placed in community quarantine to prevent one additional case of transmission in the community. This analysis suggests quarantine can be an effective preventive measure, although these estimates lack statistical precision.
Relative to other health policy areas, literature on quarantine tends to lack in quantitative expressions of effectiveness, or agreement on how best to report differences in outcomes attributable to control measure. We hope to further this discussion through presentation of means to calculate and express the impact of population control measures. The study of quarantine effectiveness presents several methodological and statistical challenges. Further research and discussion are needed to understand the costs and benefits of enacting quarantine, and this includes a discussion of how quantitative benefit should be communicated to decision-makers and the public, and evaluated.
社区隔离存在争议，因此应根据具体的效益定量证据来决定是否使用和准备实施。对 2002-2004 年 SARS 爆发的案例研究报告讨论了社区隔离在传播中的作用。然而，与其他卫生政策和成本效益分析领域的研究不同，这些文献并未对归因于隔离的继发病例减少量进行定量估计。
利用来自 2003 年加拿大安大略省 SARS 爆发的数据，本文提出了两种用于评估隔离影响的新方法。继发病例数差异（SCCD）反映了相对于无症状期未隔离的 SARS 病例，隔离的 SARS 病例平均传播数的减少。使用泊松和负二项回归模型（采用恒等链接函数），比较了每例隔离病例与非隔离病例的继发病例数，从而估算 SCCD。该统计量的倒数被提出作为预防社区内发生一例额外传播所需的隔离人数（NNQ）。
我们估计的 SCCD 为隔离病例比非隔离病例的继发病例数少 0.133；为预防社区内发生一例额外传播，需要对 7.5 名暴露个体进行社区隔离。该分析表明，隔离是一种有效的预防措施，尽管这些估计缺乏统计学精度。
与其他卫生政策领域相比，有关隔离的文献往往缺乏对有效性的定量表达，或者对如何最好地报告归因于控制措施的结果差异也没有达成共识。我们希望通过介绍计算和表达人群控制措施影响的方法，进一步推动这方面的讨论。隔离效果的研究提出了几个方法学和统计学方面的挑战。需要进一步研究和讨论来了解实施隔离的成本效益，包括如何向决策者和公众传达定量效益，并对其进行评估。
