plot.netsim: Plot Data from a Stochastic Network Epidemic Model

In EpiModel: Mathematical Modeling of Infectious Disease Dynamics

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:

1. type="epi": epidemic model results (e.g., disease prevalence and incidence) may be plotted.

2. 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.

3. 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.

4. 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.

See Also

plot.network, mutate_epi

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")

EpiModel documentation built on July 9, 2023, 5:21 p.m.