Prevalent vax vs. No vax (40% VE)

rm(list = ls(all.names = TRUE))
library(ggplot2)
library(tidyr)
library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

library(knitr)
library(rmarkdown)
library(formatR)

data <- read.csv("df/icer-all.csv", as.is = TRUE)
# subset comparator = base
df <- data[(data$scenario=="vaxbase"),]
df$cost.diff.per100k <- as.numeric(df$cost.diff.per100k)
df$cases.averted <- as.numeric(df$cases.averted)
df$cases.averted.per100k <- as.numeric(df$cases.averted.per100k)
df$icer.case.averted <- as.numeric(df$icer.case.averted)
df$deaths.averted <- as.numeric(df$deaths.averted)
df$deaths.averted.per100k <- as.numeric(df$ deaths.averted.per100k)
df$icer.death.averted <- as.numeric(df$icer.death.averted)
df$dalys <- as.numeric(df$dalys)
df$dalys.per100k <- as.numeric(df$dalys.per100k)
df$dalys.averted <- as.numeric(df$dalys.averted)
df$dalys.averted.per100k <- as.numeric(df$dalys.averted.per100k)
df$icer.daly.averted <- as.numeric(df$icer.daly.averted)

# subset efficacy
df <- df[!(df$scenario == 'vaxbase' & df$v.eff %in% c(50, 60)),]
# factors
df$age <- factor(df$age, levels = c("0-4 yrs", "5-19 yrs", "20-64 yrs", "65+ yrs", "All"))
df$risk <- factor(df$risk, levels = c("High", "Non-high", "All"))
df$scenario <- factor(df$scenario, levels = c("vaxbase", "vax70"))
df$v.eff <- factor(df$v.eff)

1 Tables

2 Subset data.

# subset scenario
df_base <- df[(df$scenario == 'vaxbase'),]
# age groups
age_df_base <- df_base[(df_base$risk == "All"),]
# risk groups
risk_df_base <- df_base[!(df_base$age == 'All'),]

2.1 40% VE: ICER per case averted

ggplot(df_base[(df_base$v.eff == "40"),], aes(x = age, y = icer.case.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Risk group") + 
  ylab("$ saved per case averted") + ggtitle("Prevalent Vaccination (40% efficacy): ICER per case averted")

2.2 40% VE: ICER per death averted

ggplot(df_base[(df_base$v.eff == "40"),], aes(x = age, y = icer.death.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Risk group") + 
  ylab("$ saved per death averted") + ggtitle("Prevalent Vaccination (40% efficacy): ICER per death averted")

2.3 40% VE: ICER per DALY averted

ggplot(df_base[(df_base$v.eff == "40"),], aes(x = age, y = icer.daly.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Risk group") + 
  ylab("$ saved per DALY averted") + ggtitle("Prevalent Vaccination (40% efficacy): ICER per DALY averted")

2.4 40% VE: Cases, cases averted

g4 <- ggplot(df_base[(df_base$v.eff == "40"),], aes(x = age, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Risk group")
g4 + aes(y = cases) + labs(y = "Cases", title = "Prevalent Vaccination (40% VE): Cases")

g4 + aes(y = cases.per100k) + labs(y = "Cases per 100k", title = "Prevalent Vaccination (40% VE): Cases per 100k")

g4 + aes(y = cases.averted) + labs(y = "Cases averted", title = "Prevalent Vaccination (40% VE): Cases averted")

g4 + aes(y = cases.averted.per100k) + labs(y = "Cases averted per 100k", title = "Prevalent Vaccination (40% VE): Cases averted per 100k")

2.5 40% VE: Deaths, deaths averted

g4 + aes(y = deaths) + labs(y = "Deaths", title = "Prevalent Vaccination (40% VE): Deaths")

g4 + aes(y = deaths.per100k) + labs(y = "Deaths per 100k", title = "Prevalent Vaccination (40% VE): Deaths per 100k")

g4 + aes(y = deaths.averted) + labs(y = "Deaths averted", title = "Prevalent Vaccination (40% VE): Deaths averted")

g4 + aes(y = deaths.averted.per100k) + labs(y = "Deaths averted per 100k", title = "Prevalent Vaccination (40% VE): Deaths averted per 100k")

2.6 40% VE: DALYs, DALYs averted

g4 + aes(y = dalys) + labs(y = "DALYs", title = "Prevalent Vaccination (40% VE): DALYs")

g4 + aes(y = dalys.per100k) + labs(y = "DALYs per 100k", title = "Prevalent Vaccination (40% VE): DALYs per 100k")

g4 + aes(y = dalys.averted) + labs(y = "DALYs averted", title = "Prevalent Vaccination (40% VE): DALYs averted")

g4 + aes(y = dalys.averted.per100k) + labs(y = "DALYs averted per 100k", title = "Prevalent Vaccination (40% VE): DALYs averted per 100k")

2.7 Fig. Cost-effectiveness plane (40% VE)

g5 <- ggplot(df_base, aes(x = dalys.averted.per100k, y = cost.diff.per100k)) +
  labs(x = "DALYs averted per 100K", y = "Cost saved per 100K", title = "Prevalent Vaccination: Cost saved vs. DALYs averted")
g5 + aes(color = risk, group = risk) + geom_point() + facet_grid(v.eff ~ age)

g5 + aes(color = age, group = age) + geom_point() + facet_grid(v.eff ~ risk)

3 Prevalent vax vs. No vax (All VE)

3.1 Fig. ICER per case averted

t <- labs(y = "$ saved per case averted", title = "Prevalent Vaccination: ICER per case averted")
ggplot(age_df_base, aes(x = age, y = icer.case.averted, color = v.eff, group = v.eff)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Vaccine \nefficacy") + t

ggplot(df_base[(df_base$age=="All"),], aes(x = v.eff, y = icer.case.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Vaccine efficacy (%)", color = "Risk") + t

ggplot(df_base, aes(x = age, y = icer.case.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Risk group") + t +
  facet_grid(~ v.eff)

3.2 Fig. ICER per death averted

t <- labs(y = "$ saved per death averted", title = "Prevalent Vaccination: ICER per death averted")
ggplot(age_df_base, aes(x = age, y = icer.death.averted, color = v.eff, group = v.eff)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Vaccine \nefficacy") + t

ggplot(df_base[(df_base$age=="All"),], aes(x = v.eff, y = icer.death.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Vaccine efficacy (%)", color = "Risk") + t

ggplot(df_base, aes(x = age, y = icer.death.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Risk group") + t +
  facet_grid(~ v.eff)

3.3 Fig. ICER per DALY averted

t <- labs(y = "$ saved per DALY averted", title = "Prevalent Vaccination: ICER per DALY averted")
ggplot(age_df_base, aes(x = age, y = icer.daly.averted, color = v.eff, group = v.eff)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Vaccine \nefficacy") + t

ggplot(df_base[(df_base$age=="All"),], aes(x = v.eff, y = icer.daly.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Vaccine efficacy (%)", color = "Risk") + t

ggplot(df_base, aes(x = age, y = icer.daly.averted, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Risk group") + t +
  facet_grid(~ v.eff)

3.4 Set up plots.

# age
g1 <- ggplot(age_df_base, aes(x = age, group = v.eff, color = v.eff)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Vaccine \nefficacy")
# risk
g2 <- ggplot(df_base[(df_base$age=="All"),], aes(x = v.eff, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Vaccine efficacy", color = "Risk group")
g3 <- ggplot(risk_df_base, aes(x = age, group = risk, color = risk)) +
  geom_point() + geom_line(linetype = "dotted") + labs(x = "Age group", color = "Risk group") +
  facet_grid(~ v.eff)

3.5 Fig. Cases, cases averted

# age groups
g1 + aes(y = cases) + labs(y = "Cases", title = "Prevalent Vaccination: Cases")

g1 + aes(y = cases.per100k) + labs(y = "Cases per 100k", title = "Prevalent Vaccination: Cases per 100k")

g1 + aes(y = cases.averted) + labs(y = "Cases averted", title = "Prevalent Vaccination: Cases averted")

g1 + aes(y = cases.averted.per100k) + labs(y = "Cases averted per 100k", title = "Prevalent Vaccination: Cases averted per 100k")

# risk groups
g2 + aes(y = cases) + labs(y = "Cases", title = "Prevalent Vaccination: Cases")

g2 + aes(y = cases.per100k) + labs(y = "Cases per 100k", title = "Prevalent Vaccination: Cases per 100k")

g2 + aes(y = cases.averted) + labs(y = "Cases averted", title = "Prevalent Vaccination: Cases averted")

g2 + aes(y = cases.averted.per100k) + labs(y = "Cases averted per 100k", title = "Prevalent Vaccination: Cases averted per 100k")

g3 + aes(y = cases) + labs(y = "Cases", title = "Prevalent Vaccination: Cases")

g3 + aes(y = cases.per100k) + labs(y = "Cases per 100k", title = "Prevalent Vaccination: Cases per 100k")

g3 + aes(y = cases.averted) + labs(y = "Cases averted", title = "Prevalent Vaccination: Cases averted")

g3 + aes(y = cases.averted.per100k) + labs(y = "Cases averted per 100k", title = "Prevalent Vaccination: Cases averted per 100k")

3.6 Fig. Deaths, deaths averted

# age groups
g1 + aes(y = deaths) + labs(y = "Deaths", title = "Prevalent Vaccination: Deaths")

g1 + aes(y = deaths.per100k) + labs(y = "Deaths per 100k", title = "Prevalent Vaccination: Deaths per 100k")

g1 + aes(y = deaths.averted) + labs(y = "Deaths averted", title = "Prevalent Vaccination: Deaths averted")

g1 + aes(y = deaths.averted.per100k) + labs(y = "Deaths averted per 100k", title = "Prevalent Vaccination: Deaths averted per 100k")

# risk groups
g2 + aes(y = deaths) + labs(y = "Deaths", title = "Prevalent Vaccination: Deaths")

g2 + aes(y = deaths.per100k) + labs(y = "Deaths per 100k", title = "Prevalent Vaccination: Deaths per 100k")

g2 + aes(y = deaths.averted) + labs(y = "Deaths averted", title = "Prevalent Vaccination: Deaths averted")

g2 + aes(y = deaths.averted.per100k) + labs(y = "Deaths averted per 100k", title = "Prevalent Vaccination: Deaths averted per 100k")

g3 + aes(y = deaths) + labs(y = "Deaths", title = "Prevalent Vaccination: Deaths")

g3 + aes(y = deaths.per100k) + labs(y = "Deaths per 100k", title = "Prevalent Vaccination: Deaths per 100k")

g3 + aes(y = deaths.averted) + labs(y = "Deaths averted", title = "Prevalent Vaccination: Deaths averted")

g3 + aes(y = deaths.averted.per100k) + labs(y = "Deaths averted per 100k", title = "Prevalent Vaccination: Deaths averted per 100k")

3.7 Fig. DALYs, DALYs averted

# age groups
g1 + aes(y = dalys) + labs(y = "DALYs", title = "Prevalent Vaccination: DALYs")

g1 + aes(y = dalys.per100k) + labs(y = "DALYs per 100k", title = "Prevalent Vaccination: DALYs per 100k")

g1 + aes(y = dalys.averted) + labs(y = "DALYs averted", title = "Prevalent Vaccination: DALYs averted")

g1 + aes(y = dalys.averted.per100k) + labs(y = "DALYs averted per 100k", title = "Prevalent Vaccination: DALYs averted per 100k")

# risk groups
g2 + aes(y = dalys) + labs(y = "DALYs", title = "Prevalent Vaccination: DALYs")

g2 + aes(y = dalys.per100k) + labs(y = "DALYs per 100k", title = "Prevalent Vaccination: DALYs per 100k")

g2 + aes(y = dalys.averted) + labs(y = "DALYs averted", title = "Prevalent Vaccination: DALYs averted")

g2 + aes(y = dalys.averted.per100k) + labs(y = "DALYs averted per 100k", title = "Prevalent Vaccination: DALYs averted per 100k")

g3 + aes(y = dalys) + labs(y = "DALYs", title = "Prevalent Vaccination: DALYs")

g3 + aes(y = dalys.per100k) + labs(y = "DALYs per 100k", title = "Prevalent Vaccination: DALYs per 100k")

g3 + aes(y = dalys.averted) + labs(y = "DALYs averted", title = "Prevalent Vaccination: DALYs averted")

g3 + aes(y = dalys.averted.per100k) + labs(y = "DALYs averted per 100k", title = "Prevalent Vaccination: DALYs averted per 100k")

3.8 Fig. Cost-effectiveness plane (All VE)

l <- labs(x = "DALYs averted per 100K", y = "Cost saved per 100K")
# All VE%
a <- ggplot(df_base, aes(x = dalys.averted.per100k, y = cost.diff.per100k)) + l +
  labs(title = "Cost-effectiveness plane: Prevalent Vaccination vs. No Vaccination")
a + aes(color = risk, group = risk) + labs(color = "Risk") + geom_point() + facet_grid(v.eff ~ age)

a + aes(color = age, group = age) + labs(color = "Age group") + geom_point() + facet_grid(v.eff ~ risk)