论文标题
传染病数据的个体建模：Epiilm
Individual-Level Modelling of Infectious Disease Data: EpiILM
论文作者
论文摘要
在本文中，我们介绍了R套件上的EPIILM，该内容为Deardon等人提出的传染性疾病传播的离散时间传播模型提供了模拟和推断的工具。 （2010）。该推论是在贝叶斯框架中设置的，是通过大都市马尔可夫链蒙特卡洛（MCMC）进行的。为了快速实施，密钥功能在Fortran中进行了编码。空间和接触网络模型均在软件包中实现，可以在易感感染（SI）或易感感染的隔离室框架中设置。通过涉及模拟和真实数据的示例来证明软件包的使用。
In this article, we introduce the R package EpiILM, which provides tools for simulation from, and inference for, discrete-time individual-level models of infectious disease transmission proposed by Deardon et al. (2010). The inference is set in a Bayesian framework and is carried out via Metropolis-Hastings Markov chain Monte Carlo (MCMC). For its fast implementation, key functions are coded in Fortran. Both spatial and contact network models are implemented in the package and can be set in either susceptible-infected (SI) or susceptible-infected-removed (SIR) compartmental frameworks. The use of the package is demonstrated through examples involving both simulated and real data.
