| SpatialNetData {EpiILMCT} | R Documentation |
Simulated epidemic data set from a distance and network-based SIR ILM
Description
This is a simulated epidemic data set of population size = 50 individuals that was generated using a combined distance and network-based SIR individual-level model (ILM) with power-law distance kernel. The model has one binary susceptible covariate and the infectivity rate is given by:
\lambda_{jt} = (\alpha_{0} + \alpha_{1}z_{j}) \sum_{i \in I_{t}}{d_{ij}^{-\beta_{1}}+\beta_{2}c_{ij}}
The infectious period is assumed to follow an exponential distribution with rate \delta. The epidemic was simulated with the following parameter values: \alpha_{0} = 0.008, \alpha_{1} = 0.2, \beta_{1} = 2, \beta_{2} = 0.5 and \delta = 2.
The data set file is a list of an object of class "datagen" that contains of type, kerneltype, epidat, location and network, and the covariate matrix.
Usage
data(SpatialNetData)Format
It is a list of an object of class “datagen” that contains the following:
- type:
-
The “SIR” compartmental framework.
- kerneltype:
-
The “both” distance and network kernel functions.
- epidat:
-
A matrix of the simulated epidemic with four columns as: the id numbers of individuals, removal times, infectious periods, and infection times.
- location:
-
A matrix of the XY coordinates of individuals.
- network:
-
The undirected binary contact network matrix.
and a 50 \times 2 matrix of the covariates represents the unity intercept and the binary covariate z.