Lung cancer cases due to radon in Europe: Difference between revisions

Revision as of 09:19, 13 January 2011

This page is a knowledge crystal of subtype variable. The page identifier is Op_en4715
Moderator:Teemu R (see all)
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Scope

Mortality due to indoor radon concentrations.

Spatial: Europe
Temporal: years 2010-2050

Definition

Lung cancer cases calculated from radon concentration using <math>cases = impact function * concentration * population</math>. IF taken from HEIMTSA and INTARESE (Darby 2004; Darby 2005).

Data

Dependencies

Radon concentrations in European residences
Population of Europe
Lung cancer mortality in Europe (from WHO mortality data)
ERF of radon exposure on lung cancer mortality (heande:ERFs of several pollutants), impact function on the same page used for code below.

Unit

cases per year

Formula

R code

This code features R functions described on pages Opasnet Base Connection for R and Operating intelligently with multidimensional arrays in R.
Possible extensions, to accomodate more complex models, are left commented out with # for now.

#library(ff)
#mortlocs <- op_baseGetLocs("opasnet_base", "Op_en2778")
#mort <- op_baseGetData("opasnet_base", "Op_en2778", include = mortlocs[grep("C34|1034|UE15|All Ages", mortlocs$loc),"loc_id"])
#poplocs <- op_baseGetLocs("opasnet_base", "Op_en4691")
pop <- op_baseGetData("opasnet_base", "Op_en4691", include = 1367, exclude = c(1435, 1436))
#countries <- c("AT", "BE", "BG", "CH", "CY", "CZ", "DE", "DK", "EE", "ES", "FI", "FR", "GR", "HU", "IE", "IS", "IT", "LT", "LU", 
#	"LV", "MT", "NL", "NO", "PL", "PT", "RO", "SE", "SI", "SK", "UK")
countries <- c("Austria", "Belgium", "Bulgaria", "Switzerland", "Cyprus", "Czech Republic", "Germany", "Denmark", "Estonia", "Spain", 
	"Finland", "France", "Greece", "Hungary", "Ireland", "Iceland", "Italy", "Lithuania", "Luxembourg", "Latvia", "Malta", "Netherlands", 
	"Norway", "Poland", "Portugal", "Romania", "Sweden", "Slowenia", "Slovakia", "United Kingdom")
conc <- op_baseGetData("opasnet_base", "Op_en4713")
levels(pop[,"CountryID"]) <- countries
colnames(pop)[4] <- "Country"
colnames(pop)[8] <- "Population"
#y <- 0
#mort0 <- mort[1,]
#temp <- mort[1,]
#for (i in 1:length(levels(mort[,"Country"]))) {
#	icountry <- levels(mort[,"Country"])[i]
#	temp <- mort[mort[,"Country"] == icountry&mort[,"Age"] == "All Ages"&mort[,"Year"] == as.character(max(as.numeric(as.character(mort[
#	mort[, "Country"] == icountry, "Year"])))),]
#	if(nrow(temp)>0) mort0[(y+1):(y+nrow(temp)),] <- temp[,]
#	y <- nrow(mort0)
#}
#mort0 <- mort0[,c(3,4,5,6,7,9)]
pop <- pop[,c(3,4,5,6,7,8)]
#conc <- conc[,c(2,3,4,5)]
#mort0array <- DataframeToArray(mort0)
levels(pop[,"Age"])[1] <- "All Ages" #Fixed to match mortality format
#popxmort0 <- IntArray(pop, mort0array, "Mortality")
#ffpopxmort0 <- ffdf(Age=as.ff(popxmort0[,1]), Country=as.ff(popxmort0[,2]), Rate=as.ff(popxmort0[,3]), Sex=as.ff(popxmort0[,4]), 
#	Year=as.ff(popxmort0[,5]), Population=as.ff(popxmort0[,6]), Cause=as.ff(factor(popxmort0[,7])), List=as.ff(factor(popxmort0[,8])), 
#	Mortality=as.ff(popxmort0[,9]))
concarray <- DataframeToArray(conc)
#meanconcarray <- apply(concarray, c(2,3), mean)
#ffconcarray <- as.ff(concarray)
popxconc <- IntArray(pop, concarray, "Concentration")
#popxmort0xconc <- IntArray(popxmort0, concarray[1:1000,,])
#y <- 1
#temp <- IntArray(ffpopxmort0[1,], concarray)
#ffpopxmort0xconc <- temp[]
#for (i in 1:(nrow(ffpopxmort0)%/%5)) {
#	temp[] <- IntArray(ffpopxmort0[(1+(i-1)*5):(i*5),], concarray)
#	ffpopxmort0xconc[y:(y+nrow(temp)-1)] <- temp[]
#	y <- y + nrow(temp)
#}
#for (i in list(1=1:5, 2=8:3)) print(i[1]+i[2])
k <- 0.37
lungmortality <- data.frame(popxconc[,c("obs","Country","policy","Year","Age","Rate","Sex")], Result = k * popxconc[, 
"Concentration"] / 100 * popxconc[, "Population"] / 100000)

Result

Keywords

References

Related files

@@ Line 26: / Line 26: @@
 === Formula ===
-==== R code prototype ====
+==== R code ====
 *This code features R functions described on pages [[Opasnet Base Connection for R]] and [[Operating intelligently with multidimensional arrays in R]].
-*This code is incomplete
+*Possible extensions, to accomodate more complex models, are left commented out with # for now.
-**Some possible expansions are commented out using "#"
   <nowiki>
@@ Line 59: / Line 58: @@
 #mort0 <- mort0[,c(3,4,5,6,7,9)]
 pop <- pop[,c(3,4,5,6,7,8)]
-conc <- conc[,c(2,3,4,5)]
+#conc <- conc[,c(2,3,4,5)]
 #mort0array <- DataframeToArray(mort0)
 levels(pop[,"Age"])[1] <- "All Ages" #Fixed to match mortality format
@@ Line 81: / Line 80: @@
 #for (i in list(1=1:5, 2=8:3)) print(i[1]+i[2])
 k <- 0.37
-lungmortality <- data.frame(popxconc[,c(1,2,3,4,5,7)], Result = k * popxconc[, "Concentration"] / 100 * popxconc[, "Population"] / 100000)</nowiki>
+lungmortality <- data.frame(popxconc[,c("obs","Country","policy","Year","Age","Rate","Sex")], Result = k * popxconc[,
+"Concentration"] / 100 * popxconc[, "Population"] / 100000)</nowiki>
 == Result ==