Continuous Time Individual-Level Models of Infectious Disease: Package <b>EpiILMCT</b>

This paper describes the R package EpiILMCT, which allows users to study spread of infectious disease using continuous time individual level models (ILMs). The provides tools for simulation from ILMs that are based on either spatial demographic, contact network, or a combination both them, and graphical summarization epidemics. Model fitting is carried out within Bayesian Markov Chain Monte Carlo framework. can be implemented susceptible-infected-removed (SIR) susceptible-infected-notified-removed (SIN R) compartmental frameworks. As data often partially observed, uncertainties in form missing infection times - some situations removal accounted augmentation techniques. illustrated simulated an experimental set tomato spotted wilt virus disease.