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Plot Data from a Stochastic Network Epidemic Model

Source: R/plot.netsim.R
plot.netsim.Rd

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

Usage

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

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.

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.

main

a main title for the plot, see also title.

xlim

the x limits (x1, x2) of the plot. Note that x1 > x2 is allowed and leads to a ‘reversed axis’.

The default value, NULL, indicates that the range of the finite values to be plotted should be used.

xlab

a label for the x axis, defaults to a description of x.

ylim

the y limits of the plot.

ylab

a label for the y axis, defaults to a description of y.

...

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 network::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

network::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)
#> Starting maximum pseudolikelihood estimation (MPLE):
#> Obtaining the responsible dyads.
#> Evaluating the predictor and response matrix.
#> Maximizing the pseudolikelihood.
#> Finished MPLE.

# 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")