Lung cancer cases due to radon in Europe: Difference between revisions
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!Policy!!2010!!2020!!2030!!2050 | !Policy!!2010!!2020!!2030!!2050 | ||
|---- | |---- | ||
|BAU || | |BAU || 42691 (22042-95542) || 51138 (24733-111979) || 57618 (25785-137181) || 62461 (27023-143632) | ||
|---- | |---- | ||
|All || NA || | |All || NA || 53385 (25402-130453) || 68338 (28863-171718) || 81873 (31372-239696) | ||
|---- | |---- | ||
|Biomass || NA || NA || NA || | |Biomass || NA || NA || NA || 81849 (32497-218247) | ||
|---- | |---- | ||
|Insulation || NA || NA || NA || | |Insulation || NA || NA || NA || 80534 (32445-236962) | ||
|---- | |---- | ||
|Renovation || NA || NA || NA || | |Renovation || NA || NA || NA || 94075 (35396-288323) | ||
|---- | |---- | ||
|} | |} | ||
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! Country of observation!! Mean!! SD | ! Country of observation!! Mean!! SD | ||
|---- | |---- | ||
| Austria | |||
| 1105 | |||
| 1146 | |||
|---- | |---- | ||
| Belgium | |||
| 857 | |||
| 796 | |||
|---- | |---- | ||
| Bulgaria | |||
| 303 | |||
| 382 | |||
|---- | |---- | ||
| Switzerland | |||
| 1636 | |||
| 2835 | |||
|---- | |---- | ||
| Cyprus | |||
| 10 | |||
| 14 | |||
|---- | |---- | ||
| Germany | |||
| 4754 | |||
| 4305 | |||
|---- | |---- | ||
| Denmark | |||
| 382 | |||
| 408 | |||
|---- | |---- | ||
| Estonia | |||
| 222 | |||
| 239 | |||
|---- | |---- | ||
| Spain | |||
| 8245 | |||
| 15249 | |||
|---- | |---- | ||
| Finland | |||
| 805 | |||
| 792 | |||
|---- | |---- | ||
| France | |||
| 8204 | |||
| 12176 | |||
|---- | |---- | ||
| Greece | |||
| 857 | |||
| 977 | |||
|---- | |---- | ||
| Hungary | |||
| 1583 | |||
| 1985 | |||
|---- | |---- | ||
| Ireland | |||
| 533 | |||
| 580 | |||
|---- | |---- | ||
| Italy | |||
| 5035 | |||
| 5117 | |||
|---- | |---- | ||
| Lithuania | |||
| 223 | |||
| 233 | |||
|---- | |---- | ||
| Luxembourg | |||
| 68 | |||
| 64 | |||
|---- | |---- | ||
| Latvia | |||
| 229 | |||
| 289 | |||
|---- | |---- | ||
| Malta | |||
| 43 | |||
| 50 | |||
|---- | |---- | ||
| Netherlands | |||
| 504 | |||
| 338 | |||
|---- | |---- | ||
| Norway | |||
| 566 | |||
| 667 | |||
|---- | |---- | ||
| Poland | |||
| 2175 | |||
| 1864 | |||
|---- | |---- | ||
| Portugal | |||
| 1183 | |||
| 1208 | |||
|---- | |---- | ||
| Romania | |||
| 1233 | |||
| 1357 | |||
|---- | |---- | ||
| Sweden | |||
| 1353 | |||
| 1475 | |||
|---- | |---- | ||
| Slovakia | |||
| 586 | |||
| 661 | |||
|---- | |---- | ||
|| '''Total'''|| ''' | || '''Total'''|| '''42691'''|| | ||
|---- | |---- | ||
|} | |} |
Revision as of 14:26, 14 January 2011
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).
- The referenced impact function is scaled down in assuming only 4.6% of population is exposed, but we assume all are exposed.
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[1:1000,,,], "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 <- rnorm(nrow(popxconc), 0.16, (0.31-0.05)/3.92)*58.2 #RR * background rate lungmortality <- data.frame(popxconc[,c("obs","Country","policy","Year","Age","Rate","Sex")], Result = k * popxconc[, "Concentration"] / 100 * popxconc[, "Population"] / 100000)
Result
{{#opasnet_base_link:Op_en4715}}
Year | ||||
---|---|---|---|---|
Policy | 2010 | 2020 | 2030 | 2050 |
BAU | 42691 (22042-95542) | 51138 (24733-111979) | 57618 (25785-137181) | 62461 (27023-143632) |
All | NA | 53385 (25402-130453) | 68338 (28863-171718) | 81873 (31372-239696) |
Biomass | NA | NA | NA | 81849 (32497-218247) |
Insulation | NA | NA | NA | 80534 (32445-236962) |
Renovation | NA | NA | NA | 94075 (35396-288323) |
Country of observation | Mean | SD |
---|---|---|
Austria | 1105 | 1146 |
Belgium | 857 | 796 |
Bulgaria | 303 | 382 |
Switzerland | 1636 | 2835 |
Cyprus | 10 | 14 |
Germany | 4754 | 4305 |
Denmark | 382 | 408 |
Estonia | 222 | 239 |
Spain | 8245 | 15249 |
Finland | 805 | 792 |
France | 8204 | 12176 |
Greece | 857 | 977 |
Hungary | 1583 | 1985 |
Ireland | 533 | 580 |
Italy | 5035 | 5117 |
Lithuania | 223 | 233 |
Luxembourg | 68 | 64 |
Latvia | 229 | 289 |
Malta | 43 | 50 |
Netherlands | 504 | 338 |
Norway | 566 | 667 |
Poland | 2175 | 1864 |
Portugal | 1183 | 1208 |
Romania | 1233 | 1357 |
Sweden | 1353 | 1475 |
Slovakia | 586 | 661 |
Total | 42691 |
See also
Keywords
References
Related files
<mfanonymousfilelist></mfanonymousfilelist>