plot_outputs {REffectivePred}

Plotting function

Description

Various plots related to an epidemic curve.

Usage

plot_outputs(
  curve = NULL,
  Time = NULL,
  cases = NULL,
  cfg = NULL,
  window_size = NULL,
  serial_mean,
  serial_var,
  predict.beyond = 0,
  waves_list = NULL,
  num_waves = NULL,
  rt_func = NULL,
  restrictions = NULL,
  restriction.starts = NULL,
  a1 = NULL,
  a2 = NULL,
  a3 = NULL,
  a4 = NULL,
  rt.max = NULL,
  option = "all",
  verbose = FALSE
)

Arguments

curve

The output list from the prediction function, see pred.curve.

Time

A vector of dates corresponding to cases.

cases

A vector containing cases for each time point.

cfg

The object that contains all variables from the configuration file. curve, Time, and cases are also required for the method to execute. All other parameters will not be used if cfg is passed to the method.

window_size

The maximum value for the serial interval.

serial_mean

Mean of the serial interval on the log scale.

serial_var

Variance of the serial interval on the log scale.

predict.beyond

How many days to predict beyond the end of cases.

waves_list

A two-dimensional list containing the waves' time data.

num_waves

Total number of waves.

rt_func

A flag that indicates which rt function to use. Should match the shape of curve.

restrictions

A numeric integer vector giving the severity of restrictions.

restriction.starts

A vector of same length as restrictions, of times when restrictions came into effect. Note: the first index time should be 1.

a1, a2, a3, a4

Parameters of the contact rate curve specified by rt_func. These override the values given in curve for the last plot only. If not specified, will use the values from curve.

rt.max

An optional upper limit for the y-axis when plotting R_t.

option

A choice of which plot to return (1,2, or 3 - see Value for options). If set to "all" (the default) plots all three figures.

verbose

Logical. If TRUE, provides additional details while running the function.

Value

NULL. Generates a few plots: a plot of R_t over time, with waves shaded (for option = 1); the epidemic curve overlaid on top of observed cases (option = 2), where the shading reflects restriction measures; and a plot of the theoretical R_t versus S_t, in a fully susceptible population with no restrictions (option = 3).

Examples

library(REffectivePred)
## Read in the data
path_to_data <- system.file("extdata/NY_OCT_4_2022.csv", package = "REffectivePred")
data <- read.csv(path_to_data)
head(data)
cases <- diff(c(0, data$cases)) # Convert cumulative cases into daily cases
lt <- length(cases)             # Length of cases
Time <- as.Date(data$date, tryFormats = c("%d-%m-%Y", "%d/%m/%Y"))

navigate_to_config() # Open the config file, make any necessary changes here.
path_to_config <- system.file("config.yml", package = "REffectivePred")  # Read config file
cfg <- load_config()    # Build the cfg object

# Estimate parameters
est <- estimate.mle(
    cases = cases,
    cfg = cfg
    )
a1 <- est$a1
a2 <- est$a2
a3 <- est$a3
a4 <- est$a4
nu <- est$nu
vt <- c(1, est$vt_params_est)
psi <- est$Psi
betas <- est$betas

# Predict curve
r1 <- pred.curve(
a1 = a1,
a2 = a2,
a3 = a3,
a4 = a4,
nu = nu,
variant.transm = vt,
Psi = psi,
betas = betas,
cases = cases,
cfg = cfg
)

plot_outputs(Time = Time,
cases = cases,
window_size = cfg$window.size,
serial_mean = cfg$serial_mean,
serial_var = cfg$serial_var,
predict.beyond = cfg$predict.beyond,
waves_list = cfg$waves_list,
num_waves = cfg$num_waves,
rt_func = cfg$rt.func.num,
curve = r1,
restrictions = cfg$restrictions_params,
restriction.starts = cfg$restriction_st_params,
rt.max = 10
)