R: Plot Data from a Stochastic Network Epidemic Model

plot.netsim {EpiModel}

R Documentation

Plot Data from a Stochastic Network Epidemic Model

Description

Plots epidemiological and network data from a stochastic network model simulated with netsim.

Usage

## S3 method for class 'netsim'
plot(
  x,
  type = "epi",
  y,
  popfrac = FALSE,
  sim.lines = FALSE,
  sims,
  sim.col,
  sim.lwd,
  sim.alpha,
  mean.line = TRUE,
  mean.smooth = TRUE,
  mean.col,
  mean.lwd = 2,
  mean.lty = 1,
  qnts = 0.5,
  qnts.col,
  qnts.alpha = 0.5,
  qnts.smooth = TRUE,
  legend,
  leg.cex = 0.8,
  axs = "r",
  grid = FALSE,
  add = FALSE,
  network = 1,
  at = 1,
  col.status = FALSE,
  shp.g2 = NULL,
  vertex.cex,
  stats,
  targ.line = TRUE,
  targ.col,
  targ.lwd = 2,
  targ.lty = 2,
  plots.joined,
  duration.imputed = TRUE,
  method = "l",
  ...
)

Arguments

`x`	An `EpiModel` model object of class `netsim`.
`type`	Type of plot: `"epi"` for epidemic model results, `"network"` for a static network plot (`plot.network`), or `"formation"`, `"duration"`, or `"dissolution"` for network formation, duration, or dissolution statistics.
`y`	Output compartments or flows from `netsim` object to plot.
`popfrac`	If `TRUE`, plot prevalence of values rather than numbers (see details).
`sim.lines`	If `TRUE`, plot individual simulation lines. Default is to plot lines for one-group models but not for two-group models.
`sims`	If `type="epi"` or `"formation"`, a vector of simulation numbers to plot. If `type="network"`, a single simulation number for which to plot the network, or else `"min"` to plot the simulation number with the lowest disease prevalence, `"max"` for the simulation with the highest disease prevalence, or `"mean"` for the simulation with the prevalence closest to the mean across simulations at the specified time step.
`sim.col`	Vector of any standard R color format for simulation lines.
`sim.lwd`	Line width for simulation lines.
`sim.alpha`	Transparency level for simulation lines, where 0 = transparent and 1 = opaque (see `adjustcolor` function).
`mean.line`	If `TRUE`, plot mean of simulations across time.
`mean.smooth`	If `TRUE`, use a loess smoother on the mean line.
`mean.col`	Vector of any standard R color format for mean lines.
`mean.lwd`	Line width for mean lines.
`mean.lty`	Line type for mean lines.
`qnts`	If numeric, plot polygon of simulation quantiles based on the range implied by the argument (see details). If `FALSE`, suppress polygon from plot.
`qnts.col`	Vector of any standard R color format for polygons.
`qnts.alpha`	Transparency level for quantile polygons, where 0 = transparent and 1 = opaque (see `adjustcolor` function).
`qnts.smooth`	If `TRUE`, use a loess smoother on quantile polygons.
`legend`	If `TRUE`, plot default legend.
`leg.cex`	Legend scale size.
`axs`	Plot axis type (see `par` for details), with default of `"r"`.
`grid`	If `TRUE`, a grid is added to the background of plot (see `grid` for details), with default of nx by ny.
`add`	If `TRUE`, new plot window is not called and lines are added to existing plot window.
`network`	Network number, for simulations with multiple networks representing the population.
`at`	If `type = "network"`, time step for network graph.
`col.status`	If `TRUE` and `type="network"`, automatic disease status colors (blue = susceptible, red = infected, green = recovered).
`shp.g2`	If `type = "network"` and `x` is for a two-group model, shapes for the Group 2 vertices, with acceptable inputs of "triangle" and "square". Group 1 vertices will remain circles.
`vertex.cex`	Relative size of plotted vertices if `type="network"`, with implicit default of 1.
`stats`	If `type="formation","duration","dissolution"`, statistics to plot. For `type = "formation"`, `stats` are among those specified in `nwstats.formula` of `control.net`; for `type = "duration", "dissolution"`, `stats` are among those of the dissolution model (without `offset()`). The default is to plot all statistics.
`targ.line`	If `TRUE`, plot target or expected value line for the statistic of interest.
`targ.col`	Vector of standard R colors for target statistic lines, with default colors based on `RColorBrewer` color palettes.
`targ.lwd`	Line width for the line showing the target statistic values.
`targ.lty`	Line type for the line showing the target statistic values.
`plots.joined`	If `TRUE` and `type="formation","duration","dissolution"`, combine all statistics in one plot, versus one plot per statistic if `FALSE`.
`duration.imputed`	If `type = "duration"`, a logical indicating whether or not to impute starting times for relationships extant at the start of the simulation. Defaults to `TRUE` when `type = "duration"`.
`method`	Plot method for `type="formation", "duration", "dissolution"`, with options of `"l"` for line plots and `"b"` for box plots.
`...`	Additional arguments to pass.

Details

This plot function can produce three types of plots with a stochastic network model simulated through netsim:

type="epi": epidemic model results (e.g., disease prevalence and incidence) may be plotted.
type="network": a static network plot will be generated. A static network plot of a dynamic network is a cross-sectional extraction of that dynamic network at a specific time point. This plotting function wraps the plot.network function in the network package. Consult the help page for plot.network for all of the plotting parameters. In addition, four plotting parameters specific to netsim plots are available: sim, at, col.status, and shp.g2.
type="formation": summary network statistics related to the network model formation are plotted. These plots are similar to the formation plots for netdx objects. When running a netsim simulation, one must specify there that save.nwstats=TRUE; the plot here will then show the network statistics requested explicitly in nwstats.formula, or will use the formation formula set in netest otherwise.
type="duration","dissolution": as in plot.netdx; supported in plot.netsim only when the dissolution model is ~offset(edges), tergmLite is FALSE, and save.network is TRUE.

When type="epi", this plotting function will extract the epidemiological output from a model object of class netsim and plot the time series data of disease prevalence and other results. The summary statistics that the function calculates and plots are individual simulation lines, means of the individual simulation lines, and quantiles of those individual simulation lines. The mean line, toggled on with mean.line=TRUE, is calculated as the row mean across simulations at each time step.

Compartment prevalences are the size of a compartment over some denominator. To plot the raw numbers from any compartment, use popfrac=FALSE; this is the default for any plots of flows. The popfrac parameter calculates and plots the denominators of all specified compartments using these rules: 1) for one-group models, the prevalence of any compartment is the compartment size divided by the total population size; 2) for two-group models, the prevalence of any compartment is the compartment size divided by the group population size. For any prevalences that are not automatically calculated, the mutate_epi function may be used to add new variables to the netsim object to plot or analyze.

The quantiles show the range of outcome values within a certain specified quantile range. By default, the interquartile range is shown: that is the middle 50\ middle 95\ where they are plotted by default, specify qnts=FALSE.

When type="network", this function will plot cross sections of the simulated networks at specified time steps. Because it is only possible to plot one time step from one simulation at a time, it is necessary to enter these in the at and sims parameters. To aid in visualizing representative and extreme simulations at specific time steps, the sims parameter may be set to "mean" to plot the simulation in which the disease prevalence is closest to the average across all simulations, "min" to plot the simulation in which the prevalence is lowest, and "max" to plot the simulation in which the prevalence is highest.

Examples

## SI Model without Network Feedback
# Initialize network and set network model parameters
nw <- network_initialize(n = 100)
nw <- set_vertex_attribute(nw, "group", rep(1:2, each = 50))
formation <- ~edges
target.stats <- 50
coef.diss <- dissolution_coefs(dissolution = ~offset(edges), duration = 20)

# Estimate the network model
est <- netest(nw, formation, target.stats, coef.diss, verbose = FALSE)

# Simulate the epidemic model
param <- param.net(inf.prob = 0.3, inf.prob.g2 = 0.15)
init <- init.net(i.num = 10, i.num.g2 = 10)
control <- control.net(type = "SI", nsteps = 20, nsims = 3,
                       verbose = FALSE, save.nwstats = TRUE,
                       nwstats.formula = ~edges + meandeg + concurrent)
mod <- netsim(est, param, init, control)

# Plot epidemic trajectory
plot(mod)
plot(mod, type = "epi", grid = TRUE)
plot(mod, type = "epi", popfrac = TRUE)
plot(mod, type = "epi", y = "si.flow", qnts = 1, ylim = c(0, 4))

# Plot static networks
par(mar = c(0, 0, 0, 0))
plot(mod, type = "network", vertex.cex = 1.5)

# Automatic coloring of infected nodes as red
par(mfrow = c(1, 2), mar = c(0, 0, 2, 0))
plot(mod, type = "network", main = "Min Prev | Time 50",
     col.status = TRUE, at = 20, sims = "min", vertex.cex = 1.25)
plot(mod, type = "network", main = "Max Prev | Time 50",
     col.status = TRUE, at = 20, sims = "max", vertex.cex = 1.25)

# Automatic shape by group number (circle = group 1)
par(mar = c(0, 0, 0, 0))
plot(mod, type = "network", at = 20, col.status = TRUE,
     shp.g2 = "square")
plot(mod, type = "network", at = 20, col.status = TRUE,
     shp.g2 = "triangle", vertex.cex = 2)

# Plot formation statistics
par(mfrow = c(1,1), mar = c(3,3,1,1), mgp = c(2,1,0))
plot(mod, type = "formation", grid = TRUE)
plot(mod, type = "formation", plots.joined = FALSE)
plot(mod, type = "formation", sims = 2:3)
plot(mod, type = "formation", plots.joined = FALSE,
     stats = c("edges", "concurrent"))
plot(mod, type = "formation", stats = "meandeg",
     mean.lwd = 1, qnts.col = "seagreen", mean.col = "black")