formal/zimbabwe/analysis.R
In jackolney/CascadeDashboard: A Shiny App for Investigating The Current Trajectory of HIV Care
# Zimbabwe Cascade Tool Formal Analysis Script
rm(list=ls())
# AIM = Boil the calibration down to a set of REALLY NEAT FUNCTIONS.
setwd("~/git/CascadeDashboard/inst/app")
graphics.off()
quartz.options(w = 10, h = 8)
figFont <- "Avenir Next"
# Source initial files
source("../../formal/initial.R")
# GLOBAL
MasterName <- "Zimbabwe"
MasterData <- GetMasterDataSet(MasterName)
# ---- #
set.seed(100)
# ---- #
MaxError <- 0.06
MinNumber <- 1000
# Define Parameter Range
# function can now be edited
# e.g. DefineParmRange(p = c(0, 1))
# parRange <- DefineParmRange()
# parRange <- DefineParmRange(p = c(0.86, 1), omega = c(0, 0.01))
parRange <- DefineParmRange(p = c(0.7, 1), omega = c(0, 0.01))
# Run Calibration
RunNSCalibration(
country = MasterName,
data = MasterData,
maxIterations = 1e4,
maxError = MaxError,
limit = MinNumber,
parRange = parRange,
targetIterations = 1e5)
# Cascade in 2015
graphics.off(); quartz.options(w = 10, h = 4)
BuildCalibPlot_Thesis(data = CalibOut,
originalData = MasterData,
limit = MinNumber)
quartz.save(file = "../../formal/zimbabwe/fig/cal/cascade-2015.pdf", type = "pdf")
# Error Histogram
graphics.off(); quartz.options(w = 6, h = 3)
BuildCalibrationHistogram_Thesis(
runError = runError,
maxError = 0.06)
quartz.save(file = "../../formal/zimbabwe/fig/cal/calib-hist.pdf", type = "pdf")
# Calibration Detail
graphics.off(); quartz.options(w = 10, h = 8)
BuildCalibDetailPlot_Thesis(
data = CalibOut,
originalData = MasterData,
limit = MinNumber)
quartz.save(file = "../../formal/zimbabwe/fig/cal/calib-detail.pdf", type = "pdf")
# Parameter Histograms
graphics.off(); quartz.options(w = 10, h = 4)
BuildCalibrationParameterHistGroup_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/cal/par-hist.pdf", type = "pdf")
# DataReviewPlot
graphics.off(); quartz.options(w = 10, h = 4)
BuildDataReviewPlot_Thesis(data = MasterData$calib)
quartz.save(file = "../../formal/zimbabwe/fig/cal/calib-data.pdf", type = "pdf")
# Parameter means
round(colMeans(CalibParamOut), 4)
# Parameter values
a <- paste0(round(Quantile_95(CalibParamOut[["rho"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["rho"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["rho"]])[["upper"]], 4), "]")
b <- paste0(round(Quantile_95(CalibParamOut[["q"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["q"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["q"]])[["upper"]], 4), "]")
c <- paste0(round(Quantile_95(CalibParamOut[["epsilon"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["epsilon"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["epsilon"]])[["upper"]], 4), "]")
d <- paste0(round(Quantile_95(CalibParamOut[["kappa"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["kappa"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["kappa"]])[["upper"]], 4), "]")
e <- paste0(round(Quantile_95(CalibParamOut[["gamma"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["gamma"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["gamma"]])[["upper"]], 4), "]")
f <- paste0(round(Quantile_95(CalibParamOut[["theta"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["theta"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["theta"]])[["upper"]], 4), "]")
g <- paste0(round(Quantile_95(CalibParamOut[["p"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["p"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["p"]])[["upper"]], 4), "]")
h <- paste0(round(Quantile_95(CalibParamOut[["omega"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["omega"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["omega"]])[["upper"]], 4), "]")
list(a,b,c,d,e,f,g,h)
Quantile_95(CalibParamOut[["rho"]])
Quantile_95(CalibParamOut[["q"]])
Quantile_95(CalibParamOut[["epsilon"]])
Quantile_95(CalibParamOut[["kappa"]])
Quantile_95(CalibParamOut[["gamma"]])
Quantile_95(CalibParamOut[["theta"]])
Quantile_95(CalibParamOut[["p"]])
Quantile_95(CalibParamOut[["omega"]])
# Mean of over-riding parameter bounds from non-shiny interface
################################################################################
# Projection
AdvCalib <- data.frame(NatMort = 0.005, HIVMort = 1)
# CareCascade Plot
graphics.off(); quartz.options(w = 10, h = 4)
GenCascadePlot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/cascade-projection.pdf", type = "pdf")
# 90-90-90 Plot
graphics.off(); quartz.options(w = 9, h = 4)
Gen909090Plot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/90-90-90.pdf", type = "pdf")
# Powers Plot
graphics.off(); quartz.options(w = 15, h = 4)
GenPowersCascadePlot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/cascade-powers.pdf", type = "pdf")
# New Infections
graphics.off(); quartz.options(w = 6, h = 4)
GenNewInfPlot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/new-infections.pdf", type = "pdf")
# AIDS Deaths
graphics.off(); quartz.options(w = 6, h = 4)
GenAidsDeathsPlot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/AIDS-deaths.pdf", type = "pdf")
# Discrete Cascade
graphics.off(); quartz.options(w = 10, h = 4)
GenDiscreteCascade_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/cascade-discrete.pdf", type = "pdf")
# NUMBERS
# PLHIV Estimate in 2015
scales::comma(round(t0$res[1], -3))
1.388e+6
scales::comma(round(t5$res[1], -3))
1.540e+6
# DIAGNOSED
scales::comma(round(t0$res[2], -3))
1.237e+6
scales::comma(round(t5$res[2], -3))
1.403e+6
# On ART
scales::comma(round(t0$res[4], -3))
scales::comma(round(t5$res[4], -3))
round(t5$res[4], -3) / round(t0$res[4], -3)
30\% (0.858M to 1.118M)
# Viral suppression
scales::comma(round(t0$res[5], -3))
scales::comma(round(t5$res[5], -3))
round(t5$res[5], -3) / round(t0$res[5], -3)
33\% (0.759M to 1.009M)
t0
t0$res[5]/t0$res[1]
t5$res[5]/t5$res[1]
################################################################################
# Optimisation
intSwitch <- data.frame(
testing = TRUE,
linkage = TRUE,
preRetention = TRUE,
initiation = TRUE,
adherence = TRUE,
retention = TRUE
)
OptInput <- c()
OptInput$intValue_rho <- parRange["rho", "max"]
OptInput$intValue_q <- parRange["q", "max"]
OptInput$intValue_kappa <- parRange["kappa", "min"]
OptInput$intValue_gamma <- parRange["gamma", "max"]
OptInput$intValue_sigma <- 0.5
OptInput$intValue_omega <- parRange["omega", "min"]
reactiveCost <- data.frame(
test = 10,
link = 40,
care = 40,
art = 367
)
# This is used by the function 'AdjustHIVTetsCost'
SafeReactiveCost <- data.frame(
test = 10,
link = 40,
care = 40,
art = 367
)
custom <- data.frame(target = 0.9^3)
AdvCalib <- data.frame(NatMort = 0.005, HIVMort = 1)
reactiveAdjustCost <- data.frame(switch = TRUE)
intLength = 2
AdjustHIVTestCost()
theOut <- RunNSOptimisation(propRuns = 0.1, intLength = intLength)
# Frontier Plot (optResults comes from RunNSOptimisation
graphics.off(); quartz.options(w = 8, h = 4)
BuildFrontierPlot_Thesis(CalibParamOut = CalibParamOut, optResults = optResults, target = 0.9^3)
quartz.save(file = "../../formal/zimbabwe/fig/opt/frontier.pdf", type = "pdf")
# FIGURE GENERATION
graphics.off(); quartz.options(w = 8, h = 4)
BuildChangesPlot_Thesis(CalibParamOut = CalibParamOut, optResults = optResults, target = 0.9^3)
quartz.save(file = "../../formal/zimbabwe/fig/opt/changes.pdf", type = "pdf")
################################################################################
# TABULATE RESULTS #
simLength <- dim(GetParaMatrixRun(cParamOut = CalibParamOut, runNumber = 1, length = intLength))[1]
optRuns <- WhichAchieved73(simData = theOut, simLength = simLength, target = custom$target)
optRuns
frontierList <- GetFrontiers(simData = theOut, optRuns = optRuns, simLength = simLength)
frontierList
intRes <- RunInterpolation(simData = theOut, optRuns = optRuns, simLength = simLength, frontierList = frontierList, target = custom$target)
colMeans(intRes)
results <- intRes[,c("iTest","iLink","iPreR","iInit","iAdhr","iRetn")]
results$iPreR <- abs(results$iPreR)
results$iRetn <- abs(results$iRetn)
results[results$iTest < 0, "iTest"] <- 0
results[results$iLink < 0, "iLink"] <- 0
results[results$iInit < 0, "iInit"] <- 0
results[results$iAdhr < 0, "iAdhr"] <- 0
results$run <- 1:dim(results)[1]
resTable <- results
resTable[resTable$iTest < 0, "iTest"] <- 0
resTable[resTable$iLink < 0, "iLink"] <- 0
resTable[resTable$iInit < 0, "iInit"] <- 0
resTable[resTable$iAdhr < 0, "iAdhr"] <- 0
colMeans(resTable)
# BASELINE
b1 <- paste0("iCost = ", scales::dollar(Quantile_95(BaselineCost)["mean"] / 5), " [", scales::dollar(Quantile_95(BaselineCost)["lower"] / 5), " to ", scales::dollar(Quantile_95(BaselineCost)["upper"] / 5), "]")
b2 <- paste0("iTest = ", scales::comma(round(Quantile_95(BaselineTest)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineTest)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineTest)["upper"] / 5, 0)), "]")
b3 <- paste0("iLink = ", scales::comma(round(Quantile_95(BaselineLink)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineLink)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineLink)["upper"] / 5, 0)), "]")
b4 <- paste0("iPreR = ", scales::comma(round(Quantile_95(BaselinePreR)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselinePreR)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselinePreR)["upper"] / 5, 0)), "]")
b5 <- paste0("iInit = ", scales::comma(round(Quantile_95(BaselineInit)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineInit)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineInit)["upper"] / 5, 0)), "]")
b6 <- paste0("iAdhr = ", scales::comma(round(Quantile_95(BaselineAdhr)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineAdhr)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineAdhr)["upper"] / 5, 0)), "]")
b7 <- paste0("iRetn = ", scales::comma(round(Quantile_95(BaselineRetn)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineRetn)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineRetn)["upper"] / 5, 0)), "]")
b1
b2
b3
b4
b5
b6
b7
# INTERVENTIONS
round(Quantile_95(intRes[,"iCost"])["mean"] / 1e6, 2)
i1 <- paste0("iCost = ", scales::dollar(Quantile_95(intRes[,"iCost"])["mean"] / 5), " [", scales::dollar(Quantile_95(intRes[,"iCost"])["lower"] / 5), " to ", scales::dollar(Quantile_95(intRes[,"iCost"])["upper"] / 5), "]")
i2 <- paste0("iTest = ", scales::comma(round(Quantile_95(resTable[,"iTest"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iTest"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iTest"])["upper"] / 5, 0)), "]")
i3 <- paste0("iLink = ", scales::comma(round(Quantile_95(resTable[,"iLink"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iLink"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iLink"])["upper"] / 5, 0)), "]")
i4 <- paste0("iPreR = ", scales::comma(round(Quantile_95(resTable[,"iPreR"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iPreR"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iPreR"])["upper"] / 5, 0)), "]")
i5 <- paste0("iInit = ", scales::comma(round(Quantile_95(resTable[,"iInit"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iInit"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iInit"])["upper"] / 5, 0)), "]")
i6 <- paste0("iAdhr = ", scales::comma(round(Quantile_95(resTable[,"iAdhr"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iAdhr"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iAdhr"])["upper"] / 5, 0)), "]")
i7 <- paste0("iRetn = ", scales::comma(round(Quantile_95(resTable[,"iRetn"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iRetn"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iRetn"])["upper"] / 5, 0)), "]")
i1
i2
i3
i4
i5
i6
i7
Quantile_95(resTable[,"iTest"]) / 5
Quantile_95(resTable[,"iLink"]) / 5
Quantile_95(resTable[,"iPreR"]) / 5
Quantile_95(resTable[,"iInit"]) / 5
Quantile_95(resTable[,"iAdhr"]) / 5
Quantile_95(resTable[,"iRetn"]) / 5
Quantile_95(intRes[,"iTCst"]) / 5
################################################################################
# SAVE IMAGE #
# save.image("../../formal/zimbabwe/data.RData")
# save.image("../../formal/zimbabwe/big-data.RData")
jackolney/CascadeDashboard documentation built on May 18, 2019, 7:56 a.m.
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# Zimbabwe Cascade Tool Formal Analysis Script
rm(list=ls())
# AIM = Boil the calibration down to a set of REALLY NEAT FUNCTIONS.
setwd("~/git/CascadeDashboard/inst/app")
graphics.off()
quartz.options(w = 10, h = 8)
figFont <- "Avenir Next"
# Source initial files
source("../../formal/initial.R")
# GLOBAL
MasterName <- "Zimbabwe"
MasterData <- GetMasterDataSet(MasterName)
# ---- #
set.seed(100)
# ---- #
MaxError <- 0.06
MinNumber <- 1000
# Define Parameter Range
# function can now be edited
# e.g. DefineParmRange(p = c(0, 1))
# parRange <- DefineParmRange()
# parRange <- DefineParmRange(p = c(0.86, 1), omega = c(0, 0.01))
parRange <- DefineParmRange(p = c(0.7, 1), omega = c(0, 0.01))
# Run Calibration
RunNSCalibration(
country = MasterName,
data = MasterData,
maxIterations = 1e4,
maxError = MaxError,
limit = MinNumber,
parRange = parRange,
targetIterations = 1e5)
# Cascade in 2015
graphics.off(); quartz.options(w = 10, h = 4)
BuildCalibPlot_Thesis(data = CalibOut,
originalData = MasterData,
limit = MinNumber)
quartz.save(file = "../../formal/zimbabwe/fig/cal/cascade-2015.pdf", type = "pdf")
# Error Histogram
graphics.off(); quartz.options(w = 6, h = 3)
BuildCalibrationHistogram_Thesis(
runError = runError,
maxError = 0.06)
quartz.save(file = "../../formal/zimbabwe/fig/cal/calib-hist.pdf", type = "pdf")
# Calibration Detail
graphics.off(); quartz.options(w = 10, h = 8)
BuildCalibDetailPlot_Thesis(
data = CalibOut,
originalData = MasterData,
limit = MinNumber)
quartz.save(file = "../../formal/zimbabwe/fig/cal/calib-detail.pdf", type = "pdf")
# Parameter Histograms
graphics.off(); quartz.options(w = 10, h = 4)
BuildCalibrationParameterHistGroup_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/cal/par-hist.pdf", type = "pdf")
# DataReviewPlot
graphics.off(); quartz.options(w = 10, h = 4)
BuildDataReviewPlot_Thesis(data = MasterData$calib)
quartz.save(file = "../../formal/zimbabwe/fig/cal/calib-data.pdf", type = "pdf")
# Parameter means
round(colMeans(CalibParamOut), 4)
# Parameter values
a <- paste0(round(Quantile_95(CalibParamOut[["rho"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["rho"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["rho"]])[["upper"]], 4), "]")
b <- paste0(round(Quantile_95(CalibParamOut[["q"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["q"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["q"]])[["upper"]], 4), "]")
c <- paste0(round(Quantile_95(CalibParamOut[["epsilon"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["epsilon"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["epsilon"]])[["upper"]], 4), "]")
d <- paste0(round(Quantile_95(CalibParamOut[["kappa"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["kappa"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["kappa"]])[["upper"]], 4), "]")
e <- paste0(round(Quantile_95(CalibParamOut[["gamma"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["gamma"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["gamma"]])[["upper"]], 4), "]")
f <- paste0(round(Quantile_95(CalibParamOut[["theta"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["theta"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["theta"]])[["upper"]], 4), "]")
g <- paste0(round(Quantile_95(CalibParamOut[["p"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["p"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["p"]])[["upper"]], 4), "]")
h <- paste0(round(Quantile_95(CalibParamOut[["omega"]])[["mean"]], 4), " [", round(Quantile_95(CalibParamOut[["omega"]])[["lower"]], 4), " to ", round(Quantile_95(CalibParamOut[["omega"]])[["upper"]], 4), "]")
list(a,b,c,d,e,f,g,h)
Quantile_95(CalibParamOut[["rho"]])
Quantile_95(CalibParamOut[["q"]])
Quantile_95(CalibParamOut[["epsilon"]])
Quantile_95(CalibParamOut[["kappa"]])
Quantile_95(CalibParamOut[["gamma"]])
Quantile_95(CalibParamOut[["theta"]])
Quantile_95(CalibParamOut[["p"]])
Quantile_95(CalibParamOut[["omega"]])
# Mean of over-riding parameter bounds from non-shiny interface
################################################################################
# Projection
AdvCalib <- data.frame(NatMort = 0.005, HIVMort = 1)
# CareCascade Plot
graphics.off(); quartz.options(w = 10, h = 4)
GenCascadePlot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/cascade-projection.pdf", type = "pdf")
# 90-90-90 Plot
graphics.off(); quartz.options(w = 9, h = 4)
Gen909090Plot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/90-90-90.pdf", type = "pdf")
# Powers Plot
graphics.off(); quartz.options(w = 15, h = 4)
GenPowersCascadePlot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/cascade-powers.pdf", type = "pdf")
# New Infections
graphics.off(); quartz.options(w = 6, h = 4)
GenNewInfPlot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/new-infections.pdf", type = "pdf")
# AIDS Deaths
graphics.off(); quartz.options(w = 6, h = 4)
GenAidsDeathsPlot_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/AIDS-deaths.pdf", type = "pdf")
# Discrete Cascade
graphics.off(); quartz.options(w = 10, h = 4)
GenDiscreteCascade_Thesis()
quartz.save(file = "../../formal/zimbabwe/fig/pro/cascade-discrete.pdf", type = "pdf")
# NUMBERS
# PLHIV Estimate in 2015
scales::comma(round(t0$res[1], -3))
1.388e+6
scales::comma(round(t5$res[1], -3))
1.540e+6
# DIAGNOSED
scales::comma(round(t0$res[2], -3))
1.237e+6
scales::comma(round(t5$res[2], -3))
1.403e+6
# On ART
scales::comma(round(t0$res[4], -3))
scales::comma(round(t5$res[4], -3))
round(t5$res[4], -3) / round(t0$res[4], -3)
30\% (0.858M to 1.118M)
# Viral suppression
scales::comma(round(t0$res[5], -3))
scales::comma(round(t5$res[5], -3))
round(t5$res[5], -3) / round(t0$res[5], -3)
33\% (0.759M to 1.009M)
t0
t0$res[5]/t0$res[1]
t5$res[5]/t5$res[1]
################################################################################
# Optimisation
intSwitch <- data.frame(
testing = TRUE,
linkage = TRUE,
preRetention = TRUE,
initiation = TRUE,
adherence = TRUE,
retention = TRUE
)
OptInput <- c()
OptInput$intValue_rho <- parRange["rho", "max"]
OptInput$intValue_q <- parRange["q", "max"]
OptInput$intValue_kappa <- parRange["kappa", "min"]
OptInput$intValue_gamma <- parRange["gamma", "max"]
OptInput$intValue_sigma <- 0.5
OptInput$intValue_omega <- parRange["omega", "min"]
reactiveCost <- data.frame(
test = 10,
link = 40,
care = 40,
art = 367
)
# This is used by the function 'AdjustHIVTetsCost'
SafeReactiveCost <- data.frame(
test = 10,
link = 40,
care = 40,
art = 367
)
custom <- data.frame(target = 0.9^3)
AdvCalib <- data.frame(NatMort = 0.005, HIVMort = 1)
reactiveAdjustCost <- data.frame(switch = TRUE)
intLength = 2
AdjustHIVTestCost()
theOut <- RunNSOptimisation(propRuns = 0.1, intLength = intLength)
# Frontier Plot (optResults comes from RunNSOptimisation
graphics.off(); quartz.options(w = 8, h = 4)
BuildFrontierPlot_Thesis(CalibParamOut = CalibParamOut, optResults = optResults, target = 0.9^3)
quartz.save(file = "../../formal/zimbabwe/fig/opt/frontier.pdf", type = "pdf")
# FIGURE GENERATION
graphics.off(); quartz.options(w = 8, h = 4)
BuildChangesPlot_Thesis(CalibParamOut = CalibParamOut, optResults = optResults, target = 0.9^3)
quartz.save(file = "../../formal/zimbabwe/fig/opt/changes.pdf", type = "pdf")
################################################################################
# TABULATE RESULTS #
simLength <- dim(GetParaMatrixRun(cParamOut = CalibParamOut, runNumber = 1, length = intLength))[1]
optRuns <- WhichAchieved73(simData = theOut, simLength = simLength, target = custom$target)
optRuns
frontierList <- GetFrontiers(simData = theOut, optRuns = optRuns, simLength = simLength)
frontierList
intRes <- RunInterpolation(simData = theOut, optRuns = optRuns, simLength = simLength, frontierList = frontierList, target = custom$target)
colMeans(intRes)
results <- intRes[,c("iTest","iLink","iPreR","iInit","iAdhr","iRetn")]
results$iPreR <- abs(results$iPreR)
results$iRetn <- abs(results$iRetn)
results[results$iTest < 0, "iTest"] <- 0
results[results$iLink < 0, "iLink"] <- 0
results[results$iInit < 0, "iInit"] <- 0
results[results$iAdhr < 0, "iAdhr"] <- 0
results$run <- 1:dim(results)[1]
resTable <- results
resTable[resTable$iTest < 0, "iTest"] <- 0
resTable[resTable$iLink < 0, "iLink"] <- 0
resTable[resTable$iInit < 0, "iInit"] <- 0
resTable[resTable$iAdhr < 0, "iAdhr"] <- 0
colMeans(resTable)
# BASELINE
b1 <- paste0("iCost = ", scales::dollar(Quantile_95(BaselineCost)["mean"] / 5), " [", scales::dollar(Quantile_95(BaselineCost)["lower"] / 5), " to ", scales::dollar(Quantile_95(BaselineCost)["upper"] / 5), "]")
b2 <- paste0("iTest = ", scales::comma(round(Quantile_95(BaselineTest)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineTest)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineTest)["upper"] / 5, 0)), "]")
b3 <- paste0("iLink = ", scales::comma(round(Quantile_95(BaselineLink)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineLink)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineLink)["upper"] / 5, 0)), "]")
b4 <- paste0("iPreR = ", scales::comma(round(Quantile_95(BaselinePreR)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselinePreR)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselinePreR)["upper"] / 5, 0)), "]")
b5 <- paste0("iInit = ", scales::comma(round(Quantile_95(BaselineInit)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineInit)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineInit)["upper"] / 5, 0)), "]")
b6 <- paste0("iAdhr = ", scales::comma(round(Quantile_95(BaselineAdhr)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineAdhr)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineAdhr)["upper"] / 5, 0)), "]")
b7 <- paste0("iRetn = ", scales::comma(round(Quantile_95(BaselineRetn)["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(BaselineRetn)["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(BaselineRetn)["upper"] / 5, 0)), "]")
b1
b2
b3
b4
b5
b6
b7
# INTERVENTIONS
round(Quantile_95(intRes[,"iCost"])["mean"] / 1e6, 2)
i1 <- paste0("iCost = ", scales::dollar(Quantile_95(intRes[,"iCost"])["mean"] / 5), " [", scales::dollar(Quantile_95(intRes[,"iCost"])["lower"] / 5), " to ", scales::dollar(Quantile_95(intRes[,"iCost"])["upper"] / 5), "]")
i2 <- paste0("iTest = ", scales::comma(round(Quantile_95(resTable[,"iTest"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iTest"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iTest"])["upper"] / 5, 0)), "]")
i3 <- paste0("iLink = ", scales::comma(round(Quantile_95(resTable[,"iLink"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iLink"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iLink"])["upper"] / 5, 0)), "]")
i4 <- paste0("iPreR = ", scales::comma(round(Quantile_95(resTable[,"iPreR"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iPreR"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iPreR"])["upper"] / 5, 0)), "]")
i5 <- paste0("iInit = ", scales::comma(round(Quantile_95(resTable[,"iInit"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iInit"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iInit"])["upper"] / 5, 0)), "]")
i6 <- paste0("iAdhr = ", scales::comma(round(Quantile_95(resTable[,"iAdhr"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iAdhr"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iAdhr"])["upper"] / 5, 0)), "]")
i7 <- paste0("iRetn = ", scales::comma(round(Quantile_95(resTable[,"iRetn"])["mean"] / 5, 0)), " [", scales::comma(round(Quantile_95(resTable[,"iRetn"])["lower"] / 5, 0)), " to ", scales::comma(round(Quantile_95(resTable[,"iRetn"])["upper"] / 5, 0)), "]")
i1
i2
i3
i4
i5
i6
i7
Quantile_95(resTable[,"iTest"]) / 5
Quantile_95(resTable[,"iLink"]) / 5
Quantile_95(resTable[,"iPreR"]) / 5
Quantile_95(resTable[,"iInit"]) / 5
Quantile_95(resTable[,"iAdhr"]) / 5
Quantile_95(resTable[,"iRetn"]) / 5
Quantile_95(intRes[,"iTCst"]) / 5
################################################################################
# SAVE IMAGE #
# save.image("../../formal/zimbabwe/data.RData")
# save.image("../../formal/zimbabwe/big-data.RData")
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