Uncertainty and sensitivity analysis of the basic reproductive rate. Tuberculosis as an example.
Uncertainty and sensitivity analysis of the basic reproductive rate. Tuberculosis as an example.
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DOI：
10.1093/oxfordjournals.aje.a009076
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发表时间：
1997-06
影响因子：
5
通讯作者：
M. A. Sanchez;S. Blower
中科院分区：
文献类型：
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作者：
M. A. Sanchez;S. Blower
基本繁殖率（R 0）是衡量流行病严重程度的一个指标。在重复拉丁超立方抽样的基础上，对结核病基本生育率进行了不确定性和敏感性分析。不确定性分析可以推导出R 0的频率分布，并评估几个世纪前结核病流行首次出现时R 0的三个组成部分各自的相对贡献。(The R 0的三个组成部分与快速、缓慢和复发性TB相关。R 0估计值表明，结核病流行首次出现时，存在相当严重的流行。结核病发展缓慢的易感人群的R 0（R 0（缓慢））对R 0估计值的贡献最大;然而，随着结核病流行的严重程度增加，相对R 0（缓慢）贡献下降。评估了R 0大小对每个输入参数估计值的不确定性的敏感性。这些结果表明，9个输入参数中的5个，由于其估计的不确定性，在确定R 0的大小时具有影响力。这种不确定性和敏感性方法提供的结果，可以帮助调查人员了解结核病的历史流行病学量化的影响，涉及的传播过程。此外，该方法还可以应用于其他传染病的R 0，以估计流行病爆发的概率。
The basic reproductive rate (R0) is a measure of the severity of an epidemic. On the basis of replicated Latin hypercube sampling, the authors performed an uncertainty and sensitivity analysis of the basic reproductive rate of tuberculosis (TB). The uncertainty analysis allowed for the derivation of a frequency distribution for R0 and the assessment of the relative contribution each of the three components of R0 made when TB epidemics first arose centuries ago. (The three components of R0 are associated with fast, slow, and relapse TB.) R0 estimates indicated the existence of fairly severe epidemics when TB epidemics first arose. The R0 for the susceptible persons who developed TB slowly (R0(slow)) contributed the most to the R0 estimates; however, the relative R0(slow) contribution decreased as the severity of TB epidemics increased. The sensitivity of the magnitude of R0 to the uncertainty in estimating values of each of the input parameters was assessed. These results indicated that five of the nine input parameters, because of their estimation uncertainty, were influential in determining the magnitude of R0. This uncertainty and sensitivity methodology provides results that can aid investigators in understanding the historical epidemiology of TB by quantifying the effect of the transmission processes involved. Additionally, this method can be applied to the R0 of any other infectious disease to estimate the probability of an epidemic outbreak.