Estimation of a time-varying force of infection and basic reproduction number with application to an outbreak of classical swine fever.

S C Howard, C A Donnelly
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Abstract

Background: A method was developed for stochastically reconstructing the pattern of infection from observed epidemic data. This allowed for estimation of a time-dependent force of infection, or transmission rate, during an epidemic.

Methods: A discrete-time mechanistic model was used to describe the spread of infection and a stochastic procedure, which utilised the latent and infectious period distributions, was used to reconstruct the dates of infection, becoming infectious and removal from the given data. The four equations describing the model were then solved to obtain least squares estimates of the transmission rate and the basic reproduction number (R0) throughout the epidemic. This process was repeated in order to assess the variability in these key epidemiological parameters. The stochastic epidemic reconstruction procedure was developed to account for changes in the distribution of the survival period over the course of the epidemic and adapted for application to epidemic data where not all infected individuals have yet been observed as cases.

Results: The method was applied to a set of epidemic data from an outbreak of classical swine fever in Pakistan. Constant and time-varying estimates of the transmission rate were derived and compared. There was some evidence to suggest that the force of infection varied over time.

Discussion: The method described can be applied to data from epidemics where observations are incomplete. The confidence limits obtained for the estimated force of infection provide a means of assessing the evidence for time variation in this parameter.

时变感染力和基本繁殖数的估计,并应用于猪瘟暴发。
背景:建立了一种根据观察到的流行病资料随机重建感染模式的方法。这样就可以估计流行病期间随时间变化的传染力或传播率。方法:使用离散时间机制模型来描述感染的传播,并使用随机程序,利用潜伏期和传染期分布,从给定的数据中重建感染,感染和消除的日期。然后对描述该模型的四个方程进行求解,得到整个疫情期间传播率和基本繁殖数(R0)的最小二乘估计。为了评估这些关键流行病学参数的变异性,重复了这一过程。制定了随机流行病重建程序,以解释流行病过程中生存期分布的变化,并对其进行了调整,以便应用于尚未观察到所有受感染个体为病例的流行病数据。结果:该方法应用于巴基斯坦猪瘟暴发的一组流行数据。推导并比较了恒定和时变的传输速率估计。有一些证据表明,感染的力量随着时间的推移而变化。讨论:所述方法可应用于观测不完全的流行病数据。估计感染力的置信限提供了一种评估该参数的时间变化证据的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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