Estimation and inference of R0 of an infectious pathogen by a removal method
Estimation and inference of R0 of an infectious pathogen by a removal method
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DOI：
10.1016/j.mbs.2005.08.002
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发表时间：
2005-11-01
影响因子：
4.3
通讯作者：
Dobson, AP
中科院分区：
文献类型：
--
作者：
Ferrari, MJ;Bjornstad, ON;Dobson, AP
基本繁殖比 R-0 是传染性病原体调查和管理的核心量。描述随机流行病的标准模型是连续时间流行病的生灭过程。用于拟合该模型的发病率数据往往以离散单位（天、周等）收集，这使得模型拟合和 R-0 估计变得困难。离散时间流行病模型更好地匹配数据收集的时间尺度，但对随机流行病过程做出了简单化的假设。通过研究离散时间流行病模型假设的性质，我们基于链二项式模型得出了 R-0 的偏差校正最大似然估计。由此产生的“移除”估计量提供了 R-0 的估计值以及感染病例计数时间序列中的初始易感人群规模。我们说明了估计器在模拟数据和真实流行病上的表现。最后，我们讨论解决收集的数据中存在观察误差的方法。 (c) 2005 Elsevier Inc. 保留所有权利。
The basic reproductive ratio, R-0, is a central quantity in the investigation and management of infectious pathogens. The standard model for describing stochastic epidemics is the continuous time epidemic birth-and-death process. The incidence data used to fit this model tend to be collected in discrete units (days, weeks, etc.), which makes model fitting, and estimation of R-0 difficult. Discrete time epidemic models better match the time scale of data collection but make simplistic assumptions about the stochastic epidemic process. By investigating the nature of the assumptions of a discrete time epidemic model, we derive a bias corrected maximum likelihood estimate of R-0 based on the chain binomial model. The resulting 'removal' estimators provide estimates of R-0 and the initial susceptible population size from time series of infectious case counts. We illustrate the performance of the estimators on both simulated data and real epidemics. Lastly, we discuss methods to address data collected with observation error. (c) 2005 Elsevier Inc. All rights reserved.