EpiEstim: plot.estimate_R – R documentation

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plot.estimate_R

Plot outputs of estimate_r

Description

The plot method of estimate_r objects can be used to visualise three types of information. The first one shows the epidemic curve. The second one shows the posterior mean and 95% credible interval of the reproduction number. The estimate for a time window is plotted at the end of the time window. The third plot shows the discrete distribution(s) of the serial interval.

Usage

## S3 method for class 'estimate_R'
plot(
  x,
  what = c("all", "incid", "R", "SI"),
  add_imported_cases = FALSE,
  options_I = list(col = palette(), transp = 0.7, xlim = NULL, ylim = NULL, interval =
    1L, xlab = "Time", ylab = "Incidence"),
  options_R = list(col = palette(), transp = 0.2, xlim = NULL, ylim = NULL, xlab =
    "Time", ylab = "R"),
  options_SI = list(prob_min = 0.001, col = "black", transp = 0.25, xlim = NULL, ylim =
    NULL, xlab = "Time", ylab = "Frequency"),
  legend = TRUE,
  ...
)

Arguments

`x`	The output of function `estimate_R` or function `wallinga_teunis`. To plot simultaneous outputs on the same plot use `estimate_R_plots` function
`what`	A string specifying what to plot, namely the incidence time series (`what='incid'`), the estimated reproduction number (`what='R'`), the serial interval distribution (`what='SI'`, or all three (`what='all'`)).
`add_imported_cases`	A boolean to specify whether, on the incidence time series plot, to add the incidence of imported cases.
`options_I`	For what = "incid" or "all". A list of graphical options: col A color or vector of colors used for plotting incid. By default uses the default R colors. transp A numeric value between 0 and 1 used to monitor transparency of the bars plotted. Defaults to 0.7. xlim A parameter similar to that in `par`, to monitor the limits of the horizontal axis ylim A parameter similar to that in `par`, to monitor the limits of the vertical axis interval An integer or character indicating the (fixed) size of the time interval used for plotting the incidence; defaults to 1 day. xlab, ylab Labels for the axes of the incidence plot
`options_R`	For what = "R" or "all". A list of graphical options: col A color or vector of colors used for plotting R. By default uses the default R colors. transp A numeric value between 0 and 1 used to monitor transparency of the 95%CrI. Defaults to 0.2. xlim A parameter similar to that in `par`, to monitor the limits of the horizontal axis ylim A parameter similar to that in `par`, to monitor the limits of the vertical axis xlab, ylab Labels for the axes of the R plot
`options_SI`	For what = "SI" or "all". A list of graphical options: prob_min A numeric value between 0 and 1. The SI distributions explored are only shown from time 0 up to the time t so that each distribution explored has probability < `prob_min` to be on any time step after t. Defaults to 0.001. col A color or vector of colors used for plotting the SI. Defaults to black. transp A numeric value between 0 and 1 used to monitor transparency of the lines. Defaults to 0.25 xlim A parameter similar to that in `par`, to monitor the limits of the horizontal axis ylim A parameter similar to that in `par`, to monitor the limits of the vertical axis xlab, ylab Labels for the axes of the serial interval distribution plot
`legend`	A boolean (TRUE by default) governing the presence / absence of legends on the plots
`...`	further arguments passed to other methods (currently unused).

Value

a plot (if what = "incid", "R", or "SI") or a grob object (if what = "all").

Author(s)

Rolina van Gaalen rolina.van.gaalen@rivm.nl and Anne Cori a.cori@imperial.ac.uk; S3 method by Thibaut Jombart

Examples

## load data on pandemic flu in a school in 2009
data("Flu2009")

## estimate the instantaneous reproduction number
## (method "non_parametric_si")
R_i <- estimate_R(Flu2009$incidence,
                  method = "non_parametric_si",
                  config = list(t_start = seq(2, 26), 
                                t_end = seq(8, 32), 
                                si_distr = Flu2009$si_distr
                               )
                 )

## visualise results
plot(R_i, legend = FALSE)

## estimate the instantaneous reproduction number
## (method "non_parametric_si")
R_c <- wallinga_teunis(Flu2009$incidence, 
                       method = "non_parametric_si",
                       config = list(t_start = seq(2, 26), 
                                     t_end = seq(8, 32), 
                                     si_distr = Flu2009$si_distr
                                    )
                      )

## produce plot of the incidence
## (with, on top of total incidence, the incidence of imported cases),
## estimated instantaneous and case reproduction numbers
## and serial interval distribution used
p_I <- plot(R_i, "incid", add_imported_cases=TRUE) # plots the incidence
p_SI <- plot(R_i, "SI") # plots the serial interval distribution
p_Ri <- plot(R_i, "R",
             options_R = list(ylim = c(0, 4)))
        # plots the estimated instantaneous reproduction number
p_Rc <- plot(R_c, "R",
             options_R = list(ylim = c(0, 4)))
        # plots the estimated case reproduction number
gridExtra::grid.arrange(p_I, p_SI, p_Ri, p_Rc, ncol = 2)

EpiEstim

Estimate Time Varying Reproduction Numbers from Epidemic Curves

v2.2-4

GPL (>= 2)

Authors

Anne Cori [aut, cre] (<https://orcid.org/0000-0002-8443-9162>), Simon Cauchemez [ctb], Neil M. Ferguson [ctb] (<https://orcid.org/0000-0002-1154-8093>), Christophe Fraser [ctb] (<https://orcid.org/0000-0003-2399-9657>), Elisabeth Dahlqwist [ctb] (<https://orcid.org/0000-0001-5797-6803>), P. Alex Demarsh [ctb], Thibaut Jombart [ctb] (<https://orcid.org/0000-0003-2226-8692>), Zhian N. Kamvar [ctb] (<https://orcid.org/0000-0003-1458-7108>), Justin Lessler [ctb] (<https://orcid.org/0000-0002-9741-8109>), Shikun Li [ctb], Jonathan A. Polonsky [ctb] (<https://orcid.org/0000-0002-8634-4255>), Jake Stockwin [ctb], Robin Thompson [ctb] (<https://orcid.org/0000-0001-8545-5212>), Rolina van Gaalen [ctb]

Initial release