nbTransmission (version 1.1.2)

plotRt: Creates a plot of the effective reproductive number

Description

The function plotRt creates a plot of the effective reproductive number (Rt) over the course of the outbreak. Using various options, the plot can include the overall average Rt value for the outbreak and the confidence intervals.

Usage

plotRt(
  rData,
  includeRtAvg = FALSE,
  includeRtCI = FALSE,
  includeRtAvgCI = FALSE
)

Arguments

rData

A list that is the output of estimateR. It should contain the dataframes RtDf, RtAvgDf, and vectors timeFrame and rangeForAvg

includeRtAvg

A logical. If TRUE, a horizontal line will be drawn for the average Rt value over rangeForAvg and verticle lines will be drawn at the rangeForAvg values.

includeRtCI

A logical. If TRUE, error bars will be added to the Rt values representing the bootstrap confidence intervals.

includeRtAvgCI

A logical. If TRUE, horizontal lines will be drawn around the Rt average line representing the bootstrap confidence interval.

Details

The main input rData should be the output of estimateRt with the time-level reproductive numbers, overall average, range used to calculate that average, and time frame.

The options includeRtCI and includeRtAvgCI add confidence interval bounds to the plot. If set to true, rData should be from a call of estimateRt with bootSamples > 0 so that confidence intervals are available. If includeRtAvgCI is set to TRUE, a line for the point estimate of the average Rt value will be drawn even if includeRtAvg is set to FALSE.

See Also

nbProbabilities estimateR

Examples

## Use the nbResults data frame included in the package which has the results
# of the nbProbabilities() function on a TB-like outbreak.

## Getting initial estimates of the reproductive number
# (ithout specifying nbResults and without confidence intervals)
rInitial <- estimateR(nbResults, dateVar = "infectionDate",
               indIDVar = "individualID", pVar = "pScaled",
               timeFrame = "months")
               
## Finding the stable portion of the outbreak for rangeForAvg using the plot
plotRt(rInitial)
cut1 <- 25
cut2 <- 125

## Finding the final reproductive number estimates with confidence intervals
# NOTE should run with bootSamples > 10.
rFinal <- estimateR(nbResults, dateVar = "infectionDate",
             indIDVar = "individualID", pVar = "pScaled",
             timeFrame = "months", rangeForAvg = c(cut1, cut2),
             bootSamples = 10, alpha = 0.05)

## Ploting the final result              
plotRt(rFinal, includeRtAvg = TRUE, includeRtCI = TRUE, includeRtAvgCI = TRUE)