Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT
Dublin Core
Title
Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT
Subject
EpiILMCT, infectious disease, individual level modeling, spatial models, contact
networks, R
networks, R
Description
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 framework. The continuous time ILMs can be implemented
within either susceptible-infected-removed (SIR) or susceptible-infected-notified-removed
(SIN R) 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 disease
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 framework. The continuous time ILMs can be implemented
within either susceptible-infected-removed (SIR) or susceptible-infected-notified-removed
(SIN R) 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 disease
Creator
Waleed Almutiry
Source
https://www.jstatsoft.org/article/view/v098i10
Publisher
Qassim University
Date
May 2021
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Waleed Almutiry, “Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT,” Repository Horizon University Indonesia, accessed February 5, 2025, https://repository.horizon.ac.id/items/show/8196.