ROI {denvax}

Compute the ROI surfaces given test and vaccine cost fractions.

Description

Compute the ROI surfaces given test and vaccine cost fractions.

Usage

ROI(rcoeffs, nus = seq(0.3, 0.9, by = 0.05), taus = 10^seq(-2, -0.5, by
  = 0.05))

Arguments

rcoeffs

a data.frame with the ROI surface coefficients from ROIcoeffs

nus

the series of normalized vaccine costs to use for ROI calcs

taus

the series of normalized test costs to use for ROI calcs

Details

tabulates ROI

Value

a 'data.frame' ('data.table', if available) with columns:

nu

numeric, the normalized vaccine cost used

tau

numeric, the normalized test cost used

mechanism

character, either "ordinal" or "binary" corresponding to the type of test

A

integer; the age when routine test-then-vaccinate strategy starts (from As)

L

integer; the maximum number of tests for routine test-then-vaccinate strategy (from Ls)

cost

numeric; the intervention cost (as a fraction of second infection cost)

benefit

numeric; the difference in health outcome cost (as a fraction of second infection cost) minus 'cost'; positive values indicate positive net benefit

roi

numeric; return on investment: 'benefit' over 'cost'

Examples

require(denvax);
data(morrison2010) # has counts by age
fit <- with(morrison2010, serofit(sero=Seropositive, N=Number, age.min=Age))
m2010pop <- synthetic.pop(fit, runs = 10, popsize = 10) # small sample size for example run time
m2010lh <- nPxA(m2010pop)
L <- 5
rc <- ROIcoeffs(m2010lh, As=5:10, Ls=L)
rois <- ROI(rc, nus = 0.5, taus = 0.01)
srois <- subset(rois, mechanism == "binary")
mrois <- matrix(srois$roi, nrow = L)
contour(x=unique(srois$L), y=unique(srois$A), z=mrois,
  xlab = "Max # of Tests", ylab = "Initial Age", main="ROI Contour"
)