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Copy path5 - WHO summary.R
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581 lines (435 loc) · 34.1 KB
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setwd("~/Downloads/rstudio-export")
library(tidyverse)
library(ggplot2)
library(robustbase)
cnt_reg = read_csv("~/Downloads/cnt_reg.csv")
load("outmat_cvdevents1")
load("outmat_chfevents1")
load("outmat_nephevents1")
load("outmat_retinevents1")
load("outmat_neuroevents1")
load("outmat_cvddeaths1")
load("outmat_chfdeaths1")
load("outmat_nephdeaths1")
load("outmat_retindeaths1")
load("outmat_neurodeaths1")
load("outmat_cvddalys1")
load("outmat_chfdalys1")
load("outmat_nephdalys1")
load("outmat_retindalys1")
load("outmat_neurodalys1")
load("outmat_scrcosts1")
load("outmat_rxbpcosts1")
load("outmat_rxdmcosts1")
load("outmat_rxstatincosts1")
load("outmat_cvdcosts1")
load("outmat_chfcosts1")
load("outmat_nephcosts1")
load("outmat_retincosts1")
load("outmat_neurocosts1")
##### DALYS #####
cvddalys = outmat_cvddalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "cvd")
chfdalys = outmat_chfdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "chf")
nephdalys = outmat_nephdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "neph")
neurodalys = outmat_neurodalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "neuro")
retindalys = outmat_retindalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "retin")
totdalys = rbind(cvddalys,chfdalys,nephdalys,neurodalys,retindalys)
tot = totdalys %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot)
colMedians(sapply(tot[2:6],as.numeric))
totd= totdalys %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totd[,1],totd[,2:6]*1000)
colSums(totd[,2:6])
totd[,2:6]/colSums(totd[,2:6])
tottab = totdalys %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
# 25th centile
cvddalys25 = outmat_cvddalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "cvd")
chfdalys25 = outmat_chfdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_chfdalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "chf")
nephdalys25 = outmat_nephdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_nephdalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neph")
neurodalys25 = outmat_neurodalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_neurodalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neuro")
retindalys25 = outmat_retindalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_retindalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "retin")
totdalys25 = rbind(cvddalys25,chfdalys25,nephdalys25,neurodalys25,retindalys25)
tot25 = totdalys25 %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot25)
colMedians(sapply(tot25[2:6],as.numeric))
totd25 = totdalys25 %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totd25[,1],totd25[,2:6]*1000)
colSums(totd25[,2:6])
totd25[,2:6]/colSums(totd25[,2:6])
tottab25 = totdalys25 %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
#75th centile
cvddalys75 = outmat_cvddalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "cvd")
chfdalys75 = outmat_chfdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_chfdalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "chf")
nephdalys75 = outmat_nephdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_nephdalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "neph")
neurodalys75 = outmat_neurodalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_neurodalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "neuro")
retindalys75 = outmat_retindalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_retindalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "retin")
totdalys75 = rbind(cvddalys75,chfdalys75,nephdalys75,neurodalys75,retindalys75)
tot75 = totdalys75 %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot75)
colMedians(sapply(tot75[2:6],as.numeric))
totd75 = totdalys75 %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totd75[,1],totd75[,2:6]*1000)
colSums(totd75[,2:6])
totd75[,2:6]/colSums(totd75[,2:6])
tottab75 = totdalys75 %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
# BY REGION AND OUTCOME
cvddalys = outmat_cvddalys %>% left_join(cnt_reg) %>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median) %>% mutate(outcome = "cvd")
chfdalys = outmat_chfdalys %>% left_join(cnt_reg) %>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median) %>% mutate(outcome = "chf")
nephdalys = outmat_nephdalys %>% left_join(cnt_reg) %>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median) %>% mutate(outcome = "neph")
neurodalys = outmat_neurodalys %>% left_join(cnt_reg) %>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median) %>% mutate(outcome = "neuro")
retindalys = outmat_retindalys %>% left_join(cnt_reg) %>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median) %>% mutate(outcome = "retin")
totdalys = rbind(cvddalys,chfdalys,nephdalys,neurodalys,retindalys)
totdalys %>% select(3:8) %>% group_by(outcome) %>% summarize_all(median)
# 25th centile
cvddalys25 = outmat_cvddalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "cvd")
chfdalys25 = outmat_chfdalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_chfdalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "chf")
nephdalys25 = outmat_nephdalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_nephdalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neph")
neurodalys25 = outmat_neurodalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_neurodalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neuro")
retindalys25 = outmat_retindalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_retindalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "retin")
totdalys25 = rbind(cvddalys25,chfdalys25,nephdalys25,neurodalys25,retindalys25)
totdalys25 %>% select(2:7) %>% group_by(outcome) %>% summarize_all(median)
#75th centile
cvddalys75 = outmat_cvddalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "cvd")
chfdalys75 = outmat_chfdalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_chfdalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "chf")
nephdalys75 = outmat_nephdalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_nephdalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "neph")
neurodalys75 = outmat_neurodalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_neurodalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "neuro")
retindalys75 = outmat_retindalys %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_retindalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "retin")
totdalys75 = rbind(cvddalys75,chfdalys75,nephdalys75,neurodalys75,retindalys75)
totdalys75 %>% select(2:7) %>% group_by(outcome) %>% summarize_all(median)
##### COSTS #####
scrcosts = outmat_scrcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "scr")
scrcosts[is.na(scrcosts)] = mean(colMeans(scrcosts[,3:6],na.rm=T))
rxbpcosts = outmat_rxbpcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxbp")
rxdmcosts = outmat_rxdmcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxdm")
rxstatincosts = outmat_rxstatincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxstatin")
cvdcosts = outmat_cvdcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "cvd")
chfcosts = outmat_chfcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "chf")
nephcosts = outmat_nephcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "neph")
neurocosts = outmat_neurocosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "neuro")
retincosts = outmat_retincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "retin")
totcosts = rbind(scrcosts,rxbpcosts,rxdmcosts,rxstatincosts,cvdcosts,chfcosts,nephcosts,neurocosts,retincosts)
tot = totcosts %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot)
colMedians(sapply(tot[2:6],as.numeric))
totc= totcosts %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totc[,1],totc[,2:6]*1000)
colSums(totc[,2:6])*1000
totc[,2:6]/colSums(totc[,2:6])
tottab = totcosts %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
# 25th centile
scrcosts25 = outmat_scrcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "scr")
rxbpcosts25 = outmat_rxbpcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxbp")
rxdmcosts25 = outmat_rxdmcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxdm")
rxstatincosts25 = outmat_rxstatincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxstatin")
cvdcosts25 = outmat_cvdcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "cvd")
chfcosts25 = outmat_chfcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "chf")
nephcosts25 = outmat_nephcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neph")
neurocosts25 = outmat_neurocosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neuro")
retincosts25 = outmat_retincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "retin")
totcosts25 = rbind(rxbpcosts25,rxdmcosts25,rxstatincosts25,cvdcosts25,chfcosts25,nephcosts25,neurocosts25,retincosts25)
tot25 = totcosts25 %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot25)
colMedians(sapply(tot25[2:6],as.numeric))
totc25= totcosts25 %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totc25[,1],totc25[,2:6]*1000)
colSums(totc25[,2:6])*1000
totc25[,2:6]/colSums(totc25[,2:6])
tottab25 = totcosts25 %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
# 75th centile
scrcosts75 = outmat_scrcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "scr")
rxbpcosts75 = outmat_rxbpcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxbp")
rxdmcosts75 = outmat_rxdmcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxdm")
rxstatincosts75 = outmat_rxstatincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxstatin")
cvdcosts75 = outmat_cvdcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "cvd")
chfcosts75 = outmat_chfcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "chf")
nephcosts75 = outmat_nephcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "neph")
neurocosts75 = outmat_neurocosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "neuro")
retincosts75 = outmat_retincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "retin")
totcosts75 = rbind(rxbpcosts75,rxdmcosts75,rxstatincosts75,cvdcosts75,chfcosts75,nephcosts75,neurocosts75,retincosts75)
tot75 = totcosts75 %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot75)
colMedians(sapply(tot75[2:6],as.numeric))
totc75= totcosts75 %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totc75[,1],totc75[,2:6]*1000)
colSums(totc75[,2:6])*1000
totc75[,2:6]/colSums(totc75[,2:6])
tottab75 = totcosts75 %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
# by region and by outcome
scrcosts = outmat_scrcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "scr")
rxbpcosts = outmat_rxbpcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxbp")
rxdmcosts = outmat_rxdmcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxdm")
rxstatincosts = outmat_rxstatincosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxstatin")
cvdcosts = outmat_cvdcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "cvd")
chfcosts = outmat_chfcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "chf")
nephcosts = outmat_nephcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "neph")
neurocosts = outmat_neurocosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "neuro")
retincosts = outmat_retincosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "retin")
totcosts = rbind(scrcosts,rxbpcosts,rxdmcosts,rxstatincosts,cvdcosts,chfcosts,nephcosts,neurocosts,retincosts)
totcosts %>% select(3:8) %>% group_by(outcome) %>% summarize_all(median)
# 25th centile
scrcosts25 = outmat_scrcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "scr")
rxbpcosts25 = outmat_rxbpcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxbp")
rxdmcosts25 = outmat_rxdmcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxdm")
rxstatincosts25 = outmat_rxstatincosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxstatin")
cvdcosts25 = outmat_cvdcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "cvd")
chfcosts25 = outmat_chfcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "chf")
nephcosts25 = outmat_nephcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neph")
neurocosts25 = outmat_neurocosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neuro")
retincosts25 = outmat_retincosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "retin")
totcosts25 = rbind(scrcosts25,rxbpcosts25,rxdmcosts25,rxstatincosts25,cvdcosts25,chfcosts25,nephcosts25,neurocosts25,retincosts25)
totcosts25 %>% select(2:7) %>% group_by(outcome) %>% summarize_all(median)
# 75th centile
scrcosts75 = outmat_scrcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "scr")
rxbpcosts75 = outmat_rxbpcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxbp")
rxdmcosts75 = outmat_rxdmcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxdm")
rxstatincosts75 = outmat_rxstatincosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxstatin")
cvdcosts75 = outmat_cvdcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "cvd")
chfcosts75 = outmat_chfcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "chf")
nephcosts75 = outmat_nephcosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "neph")
neurocosts75 = outmat_neurocosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "neuro")
retincosts75 = outmat_retincosts %>% left_join(cnt_reg)%>% mutate_at(2:6,as.numeric) %>% group_by(Region) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "retin")
totcosts75 = rbind(scrcosts75,rxbpcosts75,rxdmcosts75,rxstatincosts75,cvdcosts75,chfcosts75,nephcosts75,neurocosts75,retincosts75)
totcosts75 %>% select(2:7) %>% group_by(outcome) %>% summarize_all(median)
#### ICER ####
scrcosts = outmat_scrcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "scr")
rxbpcosts = outmat_rxbpcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxbp")
rxdmcosts = outmat_rxdmcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxdm")
rxstatincosts = outmat_rxstatincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "rxstatin")
cvdcosts = outmat_cvdcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "cvd")
chfcosts = outmat_chfcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "chf")
nephcosts = outmat_nephcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "neph")
neurocosts = outmat_neurocosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "neuro")
retincosts = outmat_retincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median, na.rm = T) %>% mutate(outcome = "retin")
totcosts = rbind(scrcosts,rxbpcosts,rxdmcosts,rxstatincosts,cvdcosts,chfcosts,nephcosts,neurocosts,retincosts)
tot = totcosts %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot)
colMedians(sapply(tot[2:6],as.numeric))
totc= totcosts %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totc[,1],totc[,2:6]*1000)
colSums(totc[,2:6])*1000
totc[,2:6]/colSums(totc[,2:6])
tottab_ov = colMeans(sapply(tot[2:6],as.numeric))
inc_cost_ov = cbind((tottab_ov[2]-tottab_ov[1]),(tottab_ov[3]-tottab_ov[1]),(tottab_ov[4]-tottab_ov[1]),(tottab_ov[5]-tottab_ov[1]))
tottab = totcosts %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
inc_cost = cbind((tottab[,3]-tottab[,2]),(tottab[,4]-tottab[,2]),(tottab[,5]-tottab[,2]),(tottab[,6]-tottab[,2]))
cvddalys = outmat_cvddalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "cvd")
chfdalys = outmat_chfdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "chf")
nephdalys = outmat_nephdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "neph")
neurodalys = outmat_neurodalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "neuro")
retindalys = outmat_retindalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_all(median) %>% mutate(outcome = "retin")
totdalys = rbind(cvddalys,chfdalys,nephdalys,neurodalys,retindalys)
tot = totdalys %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot)
colMedians(sapply(tot[2:6],as.numeric))
tottab_ov = colMeans(sapply(tot[2:6],as.numeric))
inc_daly_ov = -cbind((tottab_ov[2]-tottab_ov[1]),(tottab_ov[3]-tottab_ov[1]),(tottab_ov[4]-tottab_ov[1]),(tottab_ov[5]-tottab_ov[1]))
totd= totdalys %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totd[,1],totd[,2:6]*1000)
colSums(totd[,2:6])
totd[,2:6]/colSums(totd[,2:6])
tottab = totdalys %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
inc_daly = -cbind((tottab[,3]-tottab[,2]),(tottab[,4]-tottab[,2]),(tottab[,5]-tottab[,2]),(tottab[,6]-tottab[,2]))
inc_cost_ov/inc_daly_ov
inc_cost/inc_daly
scrcosts25 = outmat_scrcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "scr")
rxbpcosts25 = outmat_rxbpcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxbp")
rxdmcosts25 = outmat_rxdmcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxdm")
rxstatincosts25 = outmat_rxstatincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "rxstatin")
cvdcosts25 = outmat_cvdcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "cvd")
chfcosts25 = outmat_chfcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "chf")
nephcosts25 = outmat_nephcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neph")
neurocosts25 = outmat_neurocosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neuro")
retincosts25 = outmat_retincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "retin")
totcosts25 = rbind(rxbpcosts25,rxdmcosts25,rxstatincosts25,cvdcosts25,chfcosts25,nephcosts25,neurocosts25,retincosts25)
tot25 = totcosts25 %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot25)
colMedians(sapply(tot25[2:6],as.numeric))
totc25= totcosts25 %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totc25[,1],totc25[,2:6]*1000)
colSums(totc25[,2:6])*1000
totc25[,2:6]/colSums(totc25[,2:6])
tottab_ov = colMeans(sapply(tot25[2:6],as.numeric))
inc_cost_ov25 = cbind((tottab_ov[2]-tottab_ov[1]),(tottab_ov[3]-tottab_ov[1]),(tottab_ov[4]-tottab_ov[1]),(tottab_ov[5]-tottab_ov[1]))
tottab25 = totcosts25 %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
inc_cost25 = cbind((tottab25[,3]-tottab25[,2]),(tottab25[,4]-tottab25[,2]),(tottab25[,5]-tottab25[,2]),(tottab25[,6]-tottab25[,2]))
cvddalys25 = outmat_cvddalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "cvd")
chfdalys25 = outmat_chfdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_chfdalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "chf")
nephdalys25 = outmat_nephdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_nephdalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neph")
neurodalys25 = outmat_neurodalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_neurodalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "neuro")
retindalys25 = outmat_retindalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_retindalys[,2:6])), list(Q1=~quantile(., probs = 0.25))) %>% mutate(outcome = "retin")
totdalys25 = rbind(cvddalys25,chfdalys25,nephdalys25,neurodalys25,retindalys25)
tot25 = totdalys25 %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot25)
colMedians(sapply(tot25[2:6],as.numeric))
tottab_ov = colMeans(sapply(tot25[2:6],as.numeric))
inc_daly_ov25 = -cbind((tottab_ov[2]-tottab_ov[1]),(tottab_ov[3]-tottab_ov[1]),(tottab_ov[4]-tottab_ov[1]),(tottab_ov[5]-tottab_ov[1]))
totd25 = totdalys25 %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totd25[,1],totd25[,2:6]*1000)
colSums(totd25[,2:6])
totd25[,2:6]/colSums(totd25[,2:6])
tottab25 = totdalys25 %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
inc_daly25 = -cbind((tottab25[,3]-tottab25[,2]),(tottab25[,4]-tottab25[,2]),(tottab25[,5]-tottab25[,2]),(tottab25[,6]-tottab25[,2]))
scrcosts75 = outmat_scrcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "scr")
rxbpcosts75 = outmat_rxbpcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxbp")
rxdmcosts75 = outmat_rxdmcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxdm")
rxstatincosts75 = outmat_rxstatincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "rxstatin")
cvdcosts75 = outmat_cvdcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "cvd")
chfcosts75 = outmat_chfcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "chf")
nephcosts75 = outmat_nephcosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "neph")
neurocosts75 = outmat_neurocosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "neuro")
retincosts75 = outmat_retincosts %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q3=~quantile(., probs = 0.75))) %>% mutate(outcome = "retin")
totcosts75 = rbind(rxbpcosts75,rxdmcosts75,rxstatincosts75,cvdcosts75,chfcosts75,nephcosts75,neurocosts75,retincosts75)
tot75 = totcosts75 %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot75)
tottab_ov = colMeans(sapply(tot75[2:6],as.numeric))
inc_cost_ov75 = cbind((tottab_ov[2]-tottab_ov[1]),(tottab_ov[3]-tottab_ov[1]),(tottab_ov[4]-tottab_ov[1]),(tottab_ov[5]-tottab_ov[1]))
colMedians(sapply(tot75[2:6],as.numeric))
totc75= totcosts75 %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totc75[,1],totc75[,2:6]*1000)
colSums(totc75[,2:6])*1000
totc75[,2:6]/colSums(totc75[,2:6])
tottab75 = totcosts75 %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
inc_cost75 = cbind((tottab75[,3]-tottab75[,2]),(tottab75[,4]-tottab75[,2]),(tottab75[,5]-tottab75[,2]),(tottab75[,6]-tottab75[,2]))
cvddalys75 = outmat_cvddalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_cvddalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "cvd")
chfdalys75 = outmat_chfdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_chfdalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "chf")
nephdalys75 = outmat_nephdalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_nephdalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "neph")
neurodalys75 = outmat_neurodalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_neurodalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "neuro")
retindalys75 = outmat_retindalys %>% mutate_at(2:6,as.numeric) %>% group_by(Country) %>% summarise_at(vars(colnames(outmat_retindalys[,2:6])), list(Q1=~quantile(., probs = 0.75))) %>% mutate(outcome = "retin")
totdalys75 = rbind(cvddalys75,chfdalys75,nephdalys75,neurodalys75,retindalys75)
tot75 = totdalys75 %>%
group_by(Country) %>%
select(2:6)%>%
summarize_all(sum)
summary(tot75)
tottab_ov = colMeans(sapply(tot75[2:6],as.numeric))
inc_daly_ov75 = -cbind((tottab_ov[2]-tottab_ov[1]),(tottab_ov[3]-tottab_ov[1]),(tottab_ov[4]-tottab_ov[1]),(tottab_ov[5]-tottab_ov[1]))
colMedians(sapply(tot75[2:6],as.numeric))
totd75 = totdalys75 %>%
group_by(outcome) %>%
select(2:6) %>%
summarize_all(median)
cbind(totd75[,1],totd75[,2:6]*1000)
colSums(totd75[,2:6])
totd75[,2:6]/colSums(totd75[,2:6])
tottab75 = totdalys75 %>%
left_join(cnt_reg) %>%
group_by(Region) %>%
select(2:6)%>%
summarize_all(sum)
inc_daly75 = -cbind((tottab75[,3]-tottab75[,2]),(tottab75[,4]-tottab75[,2]),(tottab75[,5]-tottab75[,2]),(tottab75[,6]-tottab75[,2]))
inc_cost_ov/inc_daly_ov
inc_cost/inc_daly
inc_cost_ov25/inc_daly_ov75
inc_cost25/inc_daly75
inc_cost_ov75/inc_daly_ov25
inc_cost75/inc_daly25