Incubation periods of acute respiratory viral infections: a systematic review.

Incubation periods of acute respiratory viral infections: a systematic review.
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DOI:
10.1016/s1473-3099(09)70069-6
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发表时间:
2009-05
影响因子:
56.3
通讯作者:
Cummings, Derek A. T.
Cummings, Derek A. T.
中科院分区:
医学1区
文献类型:
--
作者:
Lessler, Justin;Reich, Nicholas G.;Brookmeyer, Ron;Perl, Trish M.;Nelson, Kenrad E.;Cummings, Derek A. T.

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对潜伏期的了解在传染病的调查和控制中是必不可少的,但关于潜伏期的陈述往往没有很好的参考、不一致或基于有限的数据。在对9种对公共卫生有重要意义的呼吸道病毒感染的文献的系统回顾中,我们确定了436篇关于潜伏期的陈述和38篇关于汇集分析的数据。我们用对数正态分布对混合数据进行了拟合,发现腺病毒的潜伏期中位数为5·6天(95%CI 4·8-6·3),人类冠状病毒为3·2天(95%CI 2·8-3·7),严重急性呼吸综合征冠状病毒为4·0天(95%CI 3·6-4·4),甲型流感为1.4天(95%CI 1·3-1·5),乙型流感为0·6天(95%CI 0·5-0·6),麻疹12·5天(95%CI 11·8~13·3),副流感2·6天(95%CI 2·1~3·1),呼吸道合胞病毒4·4天(95%CI 3·9~4·9),鼻病毒1.9天(95%CI 1·4~2·4)。在使用潜伏期时,重要的是要考虑其完全分布:检疫政策的正确尾巴、可能的时间和感染源的中心地区以及大流行规划中使用的模型的完全分布。我们的估计结合了已公布的数据,为这些和其他应用提供了必要的细节。
Knowledge of the incubation period is essential in the investigation and control of infectious disease, but statements of incubation period are often poorly referenced, inconsistent, or based on limited data. In a systematic review of the literature on nine respiratory viral infections of public-health importance, we identified 436 articles with statements of incubation period and 38 with data for pooled analysis. We fitted a log-normal distribution to pooled data and found the median incubation period to be 5·6 days (95% CI 4·8–6·3) for adenovirus, 3·2 days (95% CI 2·8–3·7) for human coronavirus, 4·0 days (95% CI 3·6–4·4) for severe acute respiratory syndrome coronavirus, 1·4 days (95% CI 1·3–1·5) for influenza A, 0·6 days (95% CI 0·5–0·6) for influenza B, 12·5 days (95% CI 11·8–13·3) for measles, 2·6 days (95% CI 2·1–3·1) for parainfluenza, 4·4 days (95% CI 3·9–4·9) for respiratory syncytial virus, and 1·9 days (95% CI 1·4–2·4) for rhinovirus. When using the incubation period, it is important to consider its full distribution: the right tail for quarantine policy, the central regions for likely times and sources of infection, and the full distribution for models used in pandemic planning. Our estimates combine published data to give the detail necessary for these and other applications.