论文标题
连续时间的传染病的个人级别模型：包装epiilmct
Continuous Time Individual-Level Models of Infectious Disease: a Package EpiILMCT
论文作者
论文摘要
本文描述了R套件Epiilmct，该包装允许用户使用连续的时间个体水平模型（ILM）研究传染病的传播。该软件包提供了基于空间人群，联系网络或两者组合的连续时间ILM的模拟工具，以及流行病学的图形汇总。模型拟合是在贝叶斯马尔可夫链蒙特卡洛（MCMC）框架内进行的。连续时间ILM可以在易感性感染的（SIR）或易感感染的识别（SINR）隔室框架中实现。由于通常观察到传染病数据，因此使用数据增强技术来解释以缺失感染时间的数据不确定性 - 在某些情况下缺少删除时间。使用模拟和实验数据集进行了有关番茄发现的枯萎病毒（TSWV）疾病的传播的实验数据。
This paper describes the R package EpiILMCT, which allows users to study the spread of infectious disease using continuous time individual level models (ILMs). The package provides tools for simulation from continuous time ILMs that are based on either spatial demographic, contact network, or a combination of both of them, and for the graphical summarization of epidemics. Model fitting is carried out within a Bayesian Markov Chain Monte Carlo (MCMC) framework. The continuous time ILMs can be implemented within either susceptible-infected-removed (SIR) or susceptible-infected-notified-removed (SINR) compartmental frameworks. As infectious disease data is often partially observed, data uncertainties in the form of missing infection times - and in some situations missing removal times - are accounted for using data augmentation techniques. The package is illustrated using both simulated and an experimental data set on the spread of the tomato spotted wilt virus (TSWV) disease.
