epiworldR (version 0.6.1.0)

epiworld-data: Accessing the database of epiworld

Description

Models in epiworld are stored in a database. This database can be accessed using the functions described in this manual page. Some elements of the database are: the transition matrix, the incidence matrix, the reproductive number, the generation time, and daily incidence at the virus and tool level.

Usage

get_hist_total(x)
get_today_total(x)
get_hist_virus(x)
get_hist_tool(x)
get_transition_probability(x)
get_reproductive_number(x)
# S3 method for epiworld_repnum
plot(
  x,
  y = NULL,
  ylab = "Average Rep. Number",
  xlab = "Day (step)",
  main = "Reproductive Number",
  type = "b",
  plot = TRUE,
  ...
)
plot_reproductive_number(x, ...)
get_hist_transition_matrix(x, skip_zeros = FALSE)
# S3 method for epiworld_hist_transition
as.array(x, ...)
plot_incidence(x, ...)
# S3 method for epiworld_hist_transition
plot(
  x,
  type = "b",
  xlab = "Day (step)",
  ylab = "Counts",
  main = "Daily incidence",
  plot = TRUE,
  ...
)
get_transmissions(x)
get_generation_time(x)
# S3 method for epiworld_generation_time
plot(
  x,
  type = "b",
  xlab = "Day (step)",
  ylab = "Avg. Generation Time",
  main = "Generation Time",
  plot = TRUE,
  ...
)
plot_generation_time(x, ...)

Value

• The get_hist_total function returns an object of class epiworld_hist_total.

• The get_today_total function returns a named vector with the total number of individuals in each state at the end of the simulation.

• The get_hist_virus function returns an object of class epiworld_hist_virus.

• The get_hist_tool function returns an object of epiworld_hist_virus.

• The get_transition_probability function returns an object of class matrix.

• The get_reproductive_number function returns an object of class epiworld_repnum.

• The plot function returns a plot of the reproductive number over time.

• get_hist_transition_matrix returns a data.frame with four columns: "state_from", "state_to", "date", and "counts."

• The as.array method for epiworld_hist_transition objects turns the data.frame returned by get_hist_transition_matrix into an array of nstates x nstates x (ndays + 1) entries, where the first entry is the initial state.

• The plot_incidence function returns a plot originating from the object get_hist_transition_matrix.

• The plot function returns a plot which originates from the epiworld_hist_transition object.

• The function get_transmissions returns a data.frame with the following columns: date, source, target, virus_id, virus, and source_exposure_date.

• The function get_generation_time returns a data.frame with the following columns: "agent", "virus_id", "virus", "date", and "gentime".

• The function plot_generation_time is a wrapper for plot and get_generation_time.

Arguments

x

An object of class epiworld_sir, epiworld_seir, etc. any model.

y

Ignored.

ylab, xlab, main, type

Further parameters passed to graphics::plot()

plot

Logical scalar. If TRUE (default), the function will the desired statistic.

...

In the case of plot methods, further arguments passed to graphics::plot.

skip_zeros

Logical scalar. When FALSE it will return all the entries in the transition matrix.

Details

The plot_reproductive_number function is a wrapper around get_reproductive_number that plots the result.

The plot_incidence function is a wrapper between get_hist_transition_matrix and it's plot method.

The plot method for the epiworld_hist_transition class plots the daily incidence of each state. The function returns the data frame used for plotting.

See Also

Other Models: ModelDiffNet(), ModelSEIR(), ModelSEIRCONN(), ModelSEIRD(), ModelSEIRDCONN(), ModelSEIRMixing(), ModelSIR(), ModelSIRCONN(), ModelSIRD(), ModelSIRDCONN(), ModelSIRLogit(), ModelSIRMixing(), ModelSIS(), ModelSISD(), ModelSURV()

Examples

# SEIR Connected
seirconn <- ModelSEIRCONN(
  name              = "Disease",
  n                 = 10000,
  prevalence        = 0.1,
  contact_rate      = 2.0,
  transmission_rate = 0.8,
  incubation_days   = 7.0,
  recovery_rate     = 0.3
)

# Running the simulation for 50 steps (days)
set.seed(937)
run(seirconn, 50)

# Retrieving the transition probability
get_transition_probability(seirconn)

# Retrieving date, state, and counts dataframe including any added tools
get_hist_tool(seirconn)

# Retrieving overall date, state, and counts dataframe
head(get_hist_total(seirconn))

# Retrieving date, state, and counts dataframe by variant
head(get_hist_virus(seirconn))

# Retrieving (and plotting) the reproductive number
rp <- get_reproductive_number(seirconn)
plot(rp) # Also equivalent to plot_reproductive_number(seirconn)

# We can go further and get all the history
t_hist <- get_hist_transition_matrix(seirconn)

head(t_hist)

# And turn it into an array
as.array(t_hist)[, , 1:3]

# We cam also get (and plot) the incidence, as well as
# the generation time
inci <- plot_incidence(seirconn)
gent <- plot_generation_time(seirconn)