sensitivity analysis added

1Rotavirus.R

@@ -105,19 +105,17 @@ write.csv(matrix.Dose, file="Dose.rota.csv")
 write.csv(matrix.Risk, file="Risk.rota.csv")
 
 
-#--------------------------------------------------------------------------------
-#Sensitivity Analysis---------------------------------------------------
+#5. Sensitivity Analysis---------------------------------------------------
 
-spear.Rota<-data.frame(T.handarea, Surface.area.laundry, Frac.HS, Frac.HF, Item.laundry,
-                       Contact.time.laundry, Contact.time.face.w, Contact.time.face.d, Contact.time.face.f,
-                       Reduc.wash, Reduc.dry, Reduc.hwash, TE.dry, TE.wet, TE.face, Conc.feces, 
-                       Mass.feces, Conc.onecloth, Inact.h, Inact.s, Risk.3[8,])  
+spear.Rota<-data.frame(T.handarea, Frac.HS, Frac.HF, Reduc.intv,TE.all, TE.face,
+                        Conc.i.face, Conc.i.hand, Conc.i.surface, Risk[2,])  
 
 spear.anal<-cor(spear.Rota,method="spearman")
 
 View(spear.anal)
 
 library(openxlsx)
-write.xlsx(spear.anal, sheetName="Rota1", file="Sensitivity.rota1.xlsx")
+write.csv (spear.anal, file="Sensitivity.rota.csv")
+
 
 

2InfluenzaA.R

@@ -104,3 +104,15 @@ library(openxlsx)
 write.csv(matrix.Conc, file="Conc.influ.csv")
 write.csv(matrix.Dose, file="Dose.influ.csv")
 write.csv(matrix.Risk, file="Risk.influ.csv")
+
+#5. Sensitivity Analysis---------------------------------------------------
+
+spear.Influ<-data.frame(T.handarea, Frac.HS, Frac.HF, Reduc.intv,TE.all, TE.face,
+                       Conc.i.face, Conc.i.hand, Conc.i.surface, Risk[2,])  
+
+spear.anal<-cor(spear.Influ,method="spearman")
+
+View(spear.anal)
+
+library(openxlsx)
+write.csv (spear.anal, file="Sensitivity.influ.csv")

3Rhinovirus.R

@@ -104,3 +104,16 @@ library(openxlsx)
 write.csv(matrix.Conc, file="Conc.rhino.csv")
 write.csv(matrix.Dose, file="Dose.rhino.csv")
 write.csv(matrix.Risk, file="Risk.rhino.csv")
+
+
+#5. Sensitivity Analysis---------------------------------------------------
+
+spear.Rhino<-data.frame(T.handarea, Frac.HS, Frac.HF, Reduc.intv,TE.all, TE.face,
+                       Conc.i.face, Conc.i.hand, Conc.i.surface, Risk[2,])  
+
+spear.anal<-cor(spear.Rhino,method="spearman")
+
+View(spear.anal)
+
+library(openxlsx)
+write.csv (spear.anal, file="Sensitivity.rhino.csv")

4SARS-CoV-2.R

@@ -106,3 +106,14 @@ write.csv(matrix.Dose, file="Dose.sars2.csv")
 write.csv(matrix.Risk, file="Risk.sars2.csv")
 
 
+#5. Sensitivity Analysis---------------------------------------------------
+
+spear.Sars2<-data.frame(T.handarea, Frac.HS, Frac.HF, Reduc.intv,TE.all, TE.face,
+                        Conc.i.face, Conc.i.hand, Conc.i.surface, Risk[2,])  
+
+spear.anal<-cor(spear.Sars2,method="spearman")
+
+View(spear.anal)
+
+library(openxlsx)
+write.csv (spear.anal, file="Sensitivity.sars2.csv")

5Norovirus.R

@@ -1,6 +1,6 @@
 organism<-"Norovirus"
 source("Parameters and distributions.R")
-Risk[2,]<- 0.722*(1-exp(-Dose[2,]/1106))
+
 
 #1.A single fomite contact & a single orifice contact 
 
@@ -103,20 +103,16 @@ write.csv(matrix.Conc, file="Conc.noro.csv")
 write.csv(matrix.Dose, file="Dose.noro.csv")
 write.csv(matrix.Risk, file="Risk.noro.csv")
 
+#5. Sensitivity Analysis---------------------------------------------------
 
-#--------------------------------------------------------------------------------
-#Sensitivity Analysis---------------------------------------------------
-
-spear.Rota<-data.frame(T.handarea, Surface.area.laundry, Frac.HS, Frac.HF, Item.laundry,
-                       Contact.time.laundry, Contact.time.face.w, Contact.time.face.d, Contact.time.face.f,
-                       Reduc.wash, Reduc.dry, Reduc.hwash, TE.dry, TE.wet, TE.face, Conc.feces, 
-                       Mass.feces, Conc.onecloth, Inact.h, Inact.s, Risk.3[8,])  
+spear.Noro<-data.frame(T.handarea, Frac.HS, Frac.HF, Reduc.intv,TE.all, TE.face,
+                        Conc.i.face, Conc.i.hand, Conc.i.surface, Risk[2,])  
 
-spear.anal<-cor(spear.Rota,method="spearman")
+spear.anal<-cor(spear.Noro,method="spearman")
 
 View(spear.anal)
 
 library(openxlsx)
-write.xlsx(spear.anal, sheetName="Rota1", file="Sensitivity.rota1.xlsx")
+write.csv (spear.anal, file="Sensitivity.noro.csv")
 
 

6Adenovirus.R

@@ -0,0 +1,121 @@
+organism<-"Adenovirus"
+source("Parameters and distributions.R")
+
+
+#1.A single fomite contact & a single orifice contact 
+
+##1.0 Matrix -------------------------------------------------
+numevents<-2
+eventsname<-c("pre", "post")
+
+Conc<-matrix(nrow=numevents,ncol=iterations)
+rownames(Conc)<-eventsname
+
+Dose<-matrix(nrow=numevents, ncol=iterations)
+rownames(Dose)<-eventsname
+
+Risk<-matrix(nrow=numevents, ncol=iterations)
+rownames(Risk)<-eventsname
+
+##1.1 Baseline scenario ----------------------------------------
+k<-0.607
+
+Conc[1,] <- TE.all*Frac.HS*Conc.i.surface
+Dose[1,]<- TE.face*T.handarea*Frac.HF*Conc [1, ] #multiply surface area of hand 
+Risk[1,]<- 1-exp(-Dose[1,]*k)
+
+
+##1.2 Intervention scenario ----------------------------------------
+
+Conc[2,] <- TE.all*Frac.HS*(Conc.i.surface/10^(Reduc.intv)) # <--- change the calculation 
+Dose[2,]<- TE.face*T.handarea*Frac.HF*Conc[2, ]
+Risk[2,]<-1-exp(-Dose[2,]*k)
+
+##1.3 plotting---------------------------------------------------------------
+library(ggplot2)
+library(ggpubr)
+
+Conc.df<-as.data.frame(t(Conc))
+Dose.df<-as.data.frame(t(Dose))
+Risk.df<-as.data.frame(t(Risk))
+
+event<-rep(c(rep("pre",iterations),rep("post",iterations)),3)
+
+type<-c(rep("Conc",2*iterations),rep("Dose",2*iterations),rep("Risk",2*iterations))
+value<-c(Conc.df$"pre", Conc.df$"post", Dose.df$"pre", Dose.df$"post",Risk.df$"pre", Risk.df$"post")
+
+data<-data.frame(event,type,value)
+
+windows()
+ggplot(data)+geom_violin(aes(x=event,y=value,fill=type, group=event),alpha=0.3,draw_quantiles = c(0.25,0.5,0.75))+
+  facet_wrap(~type,scales="free") +
+  scale_y_continuous(trans="log10") +
+  scale_x_discrete(limits=c("pre","post"))+
+  ggtitle("Comparison between Pre- and Post-intervention (Adenovirus)")
+
+ggsave("adeno_intevention.tiff", dpi=600, dev='tiff', height=4, width=6, units="in")
+
+
+
+##1.4 Data pulling-----------------------------------------------------------
+
+#Conc
+matrix.Conc<-matrix(nrow=2, ncol=4)
+colnames(matrix.Conc)<-c('mean', 'sd', 'min', 'max')
+rownames(matrix.Conc)<-c("pre","post")
+
+
+for (f in 1:2){
+  matrix.Conc[f,1]<-mean(Conc[f,])
+  matrix.Conc[f,2]<-sd(Conc[f,])
+  matrix.Conc[f,3]<-min(Conc[f,])
+  matrix.Conc[f,4]<-max(Conc[f,])
+}
+
+#Dose
+matrix.Dose<-matrix(nrow=2, ncol=4)
+colnames(matrix.Dose)<-c('mean', 'sd', 'min', 'max')
+rownames(matrix.Dose)<-c("pre","post")
+
+for (f in 1:2){
+  matrix.Dose[f,1]<-mean(Dose[f,])
+  matrix.Dose[f,2]<-sd(Dose[f,])
+  matrix.Dose[f,3]<-min(Dose[f,])
+  matrix.Dose[f,4]<-max(Dose[f,])
+}
+
+#Risk 
+matrix.Risk<-matrix(nrow=2, ncol=4)
+colnames(matrix.Risk)<-c('mean', 'sd', 'min', 'max')
+rownames(matrix.Risk)<-c('pre','post')
+
+for (f in 1:2){
+  matrix.Risk[f,1]<-mean(Risk[f,])
+  matrix.Risk[f,2]<-sd(Risk[f,])
+  matrix.Risk[f,3]<-min(Risk[f,])
+  matrix.Risk[f,4]<-max(Risk[f,])
+}
+#Check the data 
+View(matrix.Conc)
+View(matrix.Dose)
+View(matrix.Risk)
+
+#Pull out the data 
+library(openxlsx)
+write.csv(matrix.Conc, file="Conc.adeno.csv")
+write.csv(matrix.Dose, file="Dose.adeno.csv")
+write.csv(matrix.Risk, file="Risk.adeno.csv")
+
+
+#5. Sensitivity Analysis---------------------------------------------------
+
+spear.Adeno<-data.frame(T.handarea, Frac.HS, Frac.HF, Reduc.intv,TE.all, TE.face,
+                       Conc.i.face, Conc.i.hand, Conc.i.surface, Risk[2,])  
+
+spear.anal<-cor(spear.Adeno,method="spearman")
+
+View(spear.anal)
+
+library(openxlsx)
+write.csv (spear.anal, file="Sensitivity.adeno.csv")
+

7Ecoli.R

@@ -0,0 +1,119 @@
+organism<-"E.coli"
+source("Parameters and distributions.R")
+
+
+#1.A single fomite contact & a single orifice contact 
+
+##1.0 Matrix -------------------------------------------------
+numevents<-2
+eventsname<-c("pre", "post")
+
+Conc<-matrix(nrow=numevents,ncol=iterations)
+rownames(Conc)<-eventsname
+
+Dose<-matrix(nrow=numevents, ncol=iterations)
+rownames(Dose)<-eventsname
+
+Risk<-matrix(nrow=numevents, ncol=iterations)
+rownames(Risk)<-eventsname
+
+##1.1 Baseline scenario ----------------------------------------
+
+Conc[1,] <- TE.all*Frac.HS*Conc.i.surface
+Dose[1,]<- TE.face*T.handarea*Frac.HF*Conc [1, ] #multiply surface area of hand 
+Risk[1,]<- 1-(1+(Dose[1,]/beta))^(-alpha)
+
+##1.2 Intervention scenario ----------------------------------------
+
+Conc[2,] <- TE.all*Frac.HS*(Conc.i.surface/10^(Reduc.intv)) # <--- change the calculation 
+Dose[2,]<- TE.face*T.handarea*Frac.HF*Conc[2, ]
+Risk[2,]<- 1-(1+(Dose[2,]/beta))^(-alpha)
+
+
+##1.3 plotting---------------------------------------------------------------
+library(ggplot2)
+library(ggpubr)
+
+Conc.df<-as.data.frame(t(Conc))
+Dose.df<-as.data.frame(t(Dose))
+Risk.df<-as.data.frame(t(Risk))
+
+event<-rep(c(rep("pre",iterations),rep("post",iterations)),3)
+
+type<-c(rep("Conc",2*iterations),rep("Dose",2*iterations),rep("Risk",2*iterations))
+value<-c(Conc.df$"pre", Conc.df$"post", Dose.df$"pre", Dose.df$"post",Risk.df$"pre", Risk.df$"post")
+
+data<-data.frame(event,type,value)
+
+windows()
+ggplot(data)+geom_violin(aes(x=event,y=value,fill=type, group=event),alpha=0.3,draw_quantiles = c(0.25,0.5,0.75))+
+  facet_wrap(~type,scales="free") +
+  scale_y_continuous(trans="log10") +
+  scale_x_discrete(limits=c("pre","post"))+
+  ggtitle("Comparison between Pre- and Post-intervention (E.coli)")
+
+ggsave("ecoli_intevention.tiff", dpi=600, dev='tiff', height=4, width=6, units="in")
+
+
+
+##1.4 Data pulling-----------------------------------------------------------
+
+#Conc
+matrix.Conc<-matrix(nrow=2, ncol=4)
+colnames(matrix.Conc)<-c('mean', 'sd', 'min', 'max')
+rownames(matrix.Conc)<-c("pre","post")
+
+
+for (f in 1:2){
+  matrix.Conc[f,1]<-mean(Conc[f,])
+  matrix.Conc[f,2]<-sd(Conc[f,])
+  matrix.Conc[f,3]<-min(Conc[f,])
+  matrix.Conc[f,4]<-max(Conc[f,])
+}
+
+#Dose
+matrix.Dose<-matrix(nrow=2, ncol=4)
+colnames(matrix.Dose)<-c('mean', 'sd', 'min', 'max')
+rownames(matrix.Dose)<-c("pre","post")
+
+for (f in 1:2){
+  matrix.Dose[f,1]<-mean(Dose[f,])
+  matrix.Dose[f,2]<-sd(Dose[f,])
+  matrix.Dose[f,3]<-min(Dose[f,])
+  matrix.Dose[f,4]<-max(Dose[f,])
+}
+
+#Risk 
+matrix.Risk<-matrix(nrow=2, ncol=4)
+colnames(matrix.Risk)<-c('mean', 'sd', 'min', 'max')
+rownames(matrix.Risk)<-c('pre','post')
+
+for (f in 1:2){
+  matrix.Risk[f,1]<-mean(Risk[f,])
+  matrix.Risk[f,2]<-sd(Risk[f,])
+  matrix.Risk[f,3]<-min(Risk[f,])
+  matrix.Risk[f,4]<-max(Risk[f,])
+}
+#Check the data 
+View(matrix.Conc)
+View(matrix.Dose)
+View(matrix.Risk)
+
+#Pull out the data 
+library(openxlsx)
+write.csv(matrix.Conc, file="Conc.ecoli.csv")
+write.csv(matrix.Dose, file="Dose.ecoli.csv")
+write.csv(matrix.Risk, file="Risk.ecoli.csv")
+
+#5. Sensitivity Analysis---------------------------------------------------
+
+spear.Ecol<-data.frame(T.handarea, Frac.HS, Frac.HF, Reduc.intv,TE.all, TE.face,
+                       Conc.i.face, Conc.i.hand, Conc.i.surface, Risk[2,])  
+
+spear.anal<-cor(spear.Ecol,method="spearman")
+
+View(spear.anal)
+
+library(openxlsx)
+write.csv (spear.anal, file="Sensitivity.ecol.csv")
+