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Gametocyte fraction over time.R
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Gametocyte fraction over time.R
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# Data cleaning -----------------------------------------------------------
library(readxl)
library(lubridate)
library(dplyr)
dt <- read_excel("Cleaned data.xlsx")
dt = dt %>%
group_by(infection_id) %>%
mutate(cumsum=cumsum(clinical),cumsum=ifelse(cumsum>1,1,cumsum),
cumcause =cumsum(cause))
dt = dt %>% mutate(cause = ifelse(clinical==1 & cumcause==0,2,cause),
cause = ifelse(clinical==0 & cumsum==1,0,cause),
qpcr = ifelse(clinical==0 & cumsum==1,0,qpcr),
Tgam_uL_adj = ifelse(clinical==0 & cumsum==1,0,Tgam_uL_adj))
dtrm = dt %>% filter(!(clinical==0 & cumsum==1))
dtrm= dtrm %>% mutate(male= ifelse(gender=="Male",1,0),
hbs.homo = ifelse(HbS=="homo",1,0),
hbs.hetero = ifelse(HbS=="hetero",1,0),
g6pd376.homo = ifelse(G6PD376=="homo",1,0),
g6pd376.hetero = ifelse(G6PD376=="hetero",1,0),
g6pd202.homo = ifelse(G6PD202=="homo",1,0),
g6pd202.hetero = ifelse(G6PD202=="hetero",1,0),
age2 = ifelse(agecat==2,1,0),
age3 = ifelse(agecat==3,1,0),
moib = ifelse(moi>1,1,0),
infection_id=as.factor(infection_id))
dtrm$logqpcr = log(dtrm$qpcr+0.1)
dtrm$loggamfrac = ifelse(dtrm$qpcr==0,NA,log((dtrm$Tgam_uL_adj/dtrm$qpcr)+0.001))
# Analysis ----------------------------------------------------------------
library(mgcv)
library(ggplot2)
library(ggprism)
library(ggpubr)
mod0 = bam(loggamfrac ~ s(weeks, bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod0)
gam.vcomp(mod0)
newd = expand.grid(weeks=seq(0,40,0.1), infection_id="1")
preds=predict.gam(mod0,newd,exclude="s(infection_id)",se.fit=TRUE)
newd$loggamfrac = preds$fit
newd$loggamfrac.lci=preds$fit-1.96*preds$se.fit
newd$loggamfrac.uci=preds$fit+1.96*preds$se.fit
newd$gamfrac = exp(newd$loggamfrac)-0.001
newd$gamfrac.lci = exp(newd$loggamfrac.lci)-0.001
newd$gamfrac.uci = exp(newd$loggamfrac.uci)-0.001
plot1.gamfrac=ggplot(data=newd, aes(x=weeks,y=gamfrac))+
geom_line(size=1.2)+
geom_ribbon(aes(ymin=gamfrac.lci,ymax=gamfrac.uci),alpha=0.2)+
theme_prism()+
ylab("Gametocyte fraction")+
scale_x_continuous(breaks=seq(0,40,by=4))+
xlab("Time from first detection of incident malaria (weeks)")
plot1.gamfrac
#ggsave("gamfrac_dens.pdf",plot=plot1,device="pdf",dpi=300, width=6, height=4)
plot1.c=ggarrange(plot1+rremove("xlab"),
plot1.gam+rremove("xlab"),
plot1.gamfrac+rremove("xlab"), nrow=1,
labels=c("A","B","C"))
plot1.c=annotate_figure(plot1.c,
bottom = text_grob("Time from first detection of incident malaria (weeks)",face="bold",size=14))
plot1.c
ggsave("figures/all_longitudinal_densities.pdf",plot=plot1.c,device="pdf",dpi=300, width=12, height=8)
# Covariate effects -------------------------------------------------------
#adjust for parasite density
mod.c = bam(loggamfrac ~ s(weeks, bs="bs")+
s(logqpcr,bs="bs")+
s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
gam.vcomp(mod.c)
gamfracbypar = expand.grid(weeks=4,logqpcr=seq(-2,5,by=0.01),tend=1,infection_id="1") %>%
add_hazard(mod.c,exclude="s(infection_id)")
plot.gfp=ggplot(data=gamfracbypar, aes(x=(exp(logqpcr)-0.1),y=hazard-0.001))+
geom_line(size=1.2)+
geom_ribbon(aes(ymin=ci_lower-0.001,ymax=ci_upper-0.001),alpha=0.2)+
theme_prism()+
xlab("Parasite density/\U00B5L")+
ylab("Gametocyte fraction")+
scale_x_continuous(
trans = log_trans(),
breaks = trans_breaks("log", function(x) exp(x)),
labels = trans_format("log", function(x) round(exp(x),1))
)
plot.gfp
plot1.d=ggarrange(plot.gp+rremove("xlab"),
plot.gfp+rremove("xlab"), nrow=1,
labels=c("A","B"))
plot1.d=annotate_figure(plot1.d,
bottom = text_grob("Parasite density/\U00B5L",face="bold",size=14))
ggsave("figures/gam_dens_and_frac_by_parasitedensity.pdf",plot=plot1.d,device="pdf",dpi=300, width=12, height=8)
## Univariable ------------------------------------------------------------
PDoutput=data.frame(matrix(NA, nrow=10, ncol=5))
rownames(PDoutput)=c("age2","age3","male", "hbs.homo","hbs.hetero","g6pd376.homo","g6pd376.hetero", "g6pd202.homo", "g6pd202.hetero","moib")
colnames(PDoutput) <- c("DR","SE","DR.lci","DR.uci","pval")
mod.c = bam(loggamfrac ~ age2+age3+s(weeks, bs="bs")+
s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, age2=1, age3=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(age2=0),exclude="s(infection_id)"))
PDoutput["age2",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:5)]
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, age2=0, age3=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(age3=0),exclude="s(infection_id)"))
PDoutput["age3",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:5)]
mod.c = bam(loggamfrac ~ male+s(weeks, bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, male=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(male=0),exclude="s(infection_id)"))
PDoutput["male",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:4)]
mod.c = bam(loggamfrac ~ hbs.homo+hbs.hetero+s(weeks, bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, hbs.homo=1, hbs.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(hbs.homo=0),exclude="s(infection_id)"))
PDoutput["hbs.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:5)]
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, hbs.homo=0, hbs.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(hbs.hetero=0),exclude="s(infection_id)"))
PDoutput["hbs.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:5)]
mod.c = bam(loggamfrac ~ g6pd376.homo+g6pd376.hetero+s(weeks, bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, g6pd376.homo=1, g6pd376.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd376.homo=0),exclude="s(infection_id)"))
PDoutput["g6pd376.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:5)]
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, g6pd376.homo=0, g6pd376.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd376.hetero=0),exclude="s(infection_id)"))
PDoutput["g6pd376.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:5)]
mod.c = bam(loggamfrac ~ g6pd202.homo+g6pd202.hetero+
s(weeks, bs="bs")+
s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, g6pd202.homo=1, g6pd202.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd202.homo=0),exclude="s(infection_id)"))
PDoutput["g6pd202.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:5)]
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, g6pd202.homo=0, g6pd202.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd202.hetero=0),exclude="s(infection_id)"))
PDoutput["g6pd202.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:5)]
mod.c = bam(loggamfrac ~ moib+
s(weeks, bs="bs")+
s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(expand.grid(tend=1,weeks=4, moib=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(moib=0),exclude="s(infection_id)"))
PDoutput["moib",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:4)]
PDoutput$pval = 2*pnorm(-abs(log(PDoutput$DR)/PDoutput$SE))
PDoutput2 = cbind(round(PDoutput[,1:4],2),round(PDoutput[,5],4))
PDoutput2
# Multivariable results ---------------------------------------------------
PDoutput.x=data.frame(matrix(NA, nrow=10, ncol=5))
rownames(PDoutput.x)=c("age2","age3","male", "hbs.homo","hbs.hetero","g6pd376.homo","g6pd376.hetero", "g6pd202.homo", "g6pd202.hetero","moib")
colnames(PDoutput.x) <- c("DR","SE","DR.lci","DR.uci","pval")
mod.c = bam(loggamfrac ~ age2+ age3+ male+
s(weeks, bs="bs")+
s(logqpcr,bs="bs")+
s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=1,age3=0,male=0, cumclinical=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(age2=0),
exclude="s(infection_id)"))
PDoutput.x["age2",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:8)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=1,male=0, cumclinical=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(age3=0),
exclude="s(infection_id)"))
PDoutput.x["age3",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:8)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=1, cumclinical=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(male=0),
exclude="s(infection_id)"))
PDoutput.x["male",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:8)]
mod.c = bam(loggamfrac ~ age2+ age3+ male+ hbs.homo+hbs.hetero+
s(weeks, bs="bs")+ s(logqpcr,bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,hbs.homo=1,hbs.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(hbs.homo=0),
exclude="s(infection_id)"))
PDoutput.x["hbs.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,hbs.homo=0,hbs.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(hbs.hetero=0),
exclude="s(infection_id)"))
PDoutput.x["hbs.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
mod.c = bam(loggamfrac ~ age2+ age3+ male+ g6pd376.homo+g6pd376.hetero+
s(weeks, bs="bs")+ s(logqpcr,bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,g6pd376.homo=1,g6pd376.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd376.homo=0),
exclude="s(infection_id)"))
PDoutput.x["g6pd376.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,g6pd376.homo=0,g6pd376.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd376.hetero=0),
exclude="s(infection_id)"))
PDoutput.x["g6pd376.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
mod.c = bam(loggamfrac ~ age2+ age3+ male+ g6pd202.homo+g6pd202.hetero+
s(weeks, bs="bs")+
s(logqpcr,bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,g6pd202.homo=1,g6pd202.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd202.homo=0),
exclude="s(infection_id)"))
PDoutput.x["g6pd202.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,g6pd202.homo=0,g6pd202.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd202.hetero=0),
exclude="s(infection_id)"))
PDoutput.x["g6pd202.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
mod.c = bam(loggamfrac ~ age2+ age3+ male+ moib+
s(weeks, bs="bs")+
s(logqpcr,bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,moib=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(moib=0),
exclude="s(infection_id)"))
PDoutput.x["moib",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:9)]
PDoutput.x$pval = 2*pnorm(-abs(log(PDoutput.x$DR)/PDoutput.x$SE))
PDoutput.x2 = cbind(round(PDoutput.x[,1:4],2),round(PDoutput.x[,5],4))
PDoutput.x2
data.frame(DR=paste0(PDoutput2$DR," (",PDoutput2$DR.lci,", ",PDoutput2$DR.uci,")"),
pval=PDoutput2[,5])
data.frame(DR=paste0(PDoutput.x2$DR," (",PDoutput.x2$DR.lci,", ",PDoutput.x2$DR.uci,")"),
pval=PDoutput.x2[,5])
# Multivariable results updated---------------------------------------------------
PDoutput.y=data.frame(matrix(NA, nrow=10, ncol=5))
rownames(PDoutput.y)=c("age2","age3","male", "hbs.homo","hbs.hetero","g6pd376.homo","g6pd376.hetero", "g6pd202.homo", "g6pd202.hetero","moib")
colnames(PDoutput.y) <- c("DR","SE","DR.lci","DR.uci","pval")
mod.c = bam(loggamfrac ~ age2+ age3+
s(weeks, bs="bs")+
s(logqpcr,bs="bs")+
s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=1,age3=0,male=0, cumclinical=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(age2=0),
exclude="s(infection_id)"))
PDoutput.y["age2",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:8)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=1,male=0, cumclinical=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(age3=0),
exclude="s(infection_id)"))
PDoutput.y["age3",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:8)]
mod.c = bam(loggamfrac ~ male+
s(weeks, bs="bs")+
s(logqpcr,bs="bs")+
s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=1, cumclinical=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(male=0),
exclude="s(infection_id)"))
PDoutput.y["male",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:8)]
mod.c = bam(loggamfrac ~ hbs.homo+hbs.hetero+
s(weeks, bs="bs")+ s(logqpcr,bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,hbs.homo=1,hbs.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(hbs.homo=0),
exclude="s(infection_id)"))
PDoutput.y["hbs.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,hbs.homo=0,hbs.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(hbs.hetero=0),
exclude="s(infection_id)"))
PDoutput.y["hbs.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
mod.c = bam(loggamfrac ~ g6pd376.homo+g6pd376.hetero+
s(weeks, bs="bs")+ s(logqpcr,bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,g6pd376.homo=1,g6pd376.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd376.homo=0),
exclude="s(infection_id)"))
PDoutput.y["g6pd376.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,g6pd376.homo=0,g6pd376.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd376.hetero=0),
exclude="s(infection_id)"))
PDoutput.y["g6pd376.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
mod.c = bam(loggamfrac ~ g6pd202.homo+g6pd202.hetero+
s(weeks, bs="bs")+
s(logqpcr,bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,g6pd202.homo=1,g6pd202.hetero=0, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd202.homo=0),
exclude="s(infection_id)"))
PDoutput.y["g6pd202.homo",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,g6pd202.homo=0,g6pd202.hetero=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(g6pd202.hetero=0),
exclude="s(infection_id)"))
PDoutput.y["g6pd202.hetero",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:10)]
mod.c = bam(loggamfrac ~ moib+
s(weeks, bs="bs")+
s(logqpcr,bs="bs")+ s(infection_id, bs="re"),
family=gaussian(),
data=dtrm)
summary(mod.c)
pdpred=suppressWarnings(
expand.grid(tend=1, logqpcr=1,weeks=4,age2=0,age3=0,male=0, cumclinical=0,moib=1, infection_id="1") %>%
add_hazard(mod.c, reference=list(moib=0),
exclude="s(infection_id)"))
PDoutput.y["moib",c("DR","SE","DR.lci","DR.uci")] = pdpred[1,-(1:9)]
PDoutput.y$pval = 2*pnorm(-abs(log(PDoutput.y$DR)/PDoutput.y$SE))
PDoutput.y2 = cbind(round(PDoutput.y[,1:4],2),round(PDoutput.y[,5],4))
PDoutput.y2
resdt = data.frame(var=rownames(PDoutput2),DR=paste0(PDoutput.y2$DR," (",PDoutput.y2$DR.lci,", ",PDoutput.y2$DR.uci,")"),
pval=PDoutput.y2[,5])
xlsx::write.xlsx2(resdt,"results_estimated.xlsx",sheetName = "gametocyte fraction",row.names = FALSE,append=TRUE)