Difference between revisions of "Assessment of building policies' effect on dampness and asthma in Europe"

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(added a resulting barplot)
(→‎R code for detailed analysis)
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===R code for detailed analysis===
 
===R code for detailed analysis===
 +
 +
*The code calculates the difference in number of asthmas due to dampness, between policies being successful or not and compared to the initial year of 2010.
  
 
  <nowiki>BP <- op_baseGetData("opasnet_base", "Op_en4068")
 
  <nowiki>BP <- op_baseGetData("opasnet_base", "Op_en4068")
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asthmaxBP <- IntArray(asthma, BParray, "Successful")
 
asthmaxBP <- IntArray(asthma, BParray, "Successful")
 
array <- DataframeToArray(asthmaxBP)
 
array <- DataframeToArray(asthmaxBP)
−
gmean <- function(x) exp(mean(log(x[is.na(x)==FALSE])))
 
 
final <- apply(array, c(6,8,7,3), mean, na.rm=TRUE)
 
final <- apply(array, c(6,8,7,3), mean, na.rm=TRUE)
 
final <- apply(final, c(1,2,3), sum, na.rm=TRUE)
 
final <- apply(final, c(1,2,3), sum, na.rm=TRUE)
 
final <- final[,"1",]-final[,"0",]
 
final <- final[,"1",]-final[,"0",]
−
finaldf <- as.data.frame(as.table(final))
+
final <- final[,]-final[rep(1,4),]
−
barplot(matrix(finaldf[,"Freq"],4,4), beside=TRUE, names.arg=c("Behavioral changes", "EPBD 2008", "More eff. urb. structures", "More renewables"))
+
barplot(final, beside=TRUE, legend.text=c("2010","2020","2030","2050"))</nowiki>
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#levels(finaldf[,"policy"]))
 
−
#final <- data.frame(Policy=rep(levels(factor(asthmaxBP[,"policy"])), each=2), Successful=rep(c(1,0),4),  
 
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# Mean=c(mean(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[1]&asthmaxBP[,"Successful"]==1,"Result"]),
 
−
# mean(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[1]&asthmaxBP[,"Successful"]==0,"Result"]),
 
−
# mean(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[2]&asthmaxBP[,"Successful"]==1,"Result"]),
 
−
# mean(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[2]&asthmaxBP[,"Successful"]==0,"Result"]),
 
−
# mean(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[3]&asthmaxBP[,"Successful"]==1,"Result"]),
 
−
# mean(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[3]&asthmaxBP[,"Successful"]==0,"Result"]),
 
−
# mean(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[4]&asthmaxBP[,"Successful"]==1,"Result"]),
 
−
# mean(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[4]&asthmaxBP[,"Successful"]==0,"Result"])),
 
−
# GMean=c(exp(mean(log(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[1]&asthmaxBP[,"Successful"]==1,"Result"]))),
 
−
# exp(mean(log(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[1]&asthmaxBP[,"Successful"]==0,"Result"]))),
 
−
# exp(mean(log(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[2]&asthmaxBP[,"Successful"]==1,"Result"]))),
 
−
# exp(mean(log(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[2]&asthmaxBP[,"Successful"]==0,"Result"]))),
 
−
# exp(mean(log(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[3]&asthmaxBP[,"Successful"]==1,"Result"]))),
 
−
# exp(mean(log(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[3]&asthmaxBP[,"Successful"]==0,"Result"]))),
 
−
# exp(mean(log(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[4]&asthmaxBP[,"Successful"]==1,"Result"]))),
 
−
# exp(mean(log(asthmaxBP[asthmaxBP[,"policy"]==levels(factor(asthmaxBP[,"policy"]))[4]&asthmaxBP[,"Successful"]==0,"Result"])))))
 
−
#barplot(final[,4])</nowiki>
 
  
 
==Result==
 
==Result==

Revision as of 09:05, 23 December 2010



Scope

Purpose

What are the effects of different building policies on dampness and asthma prevalence in Europe?

Boundaries etc.

Boundaries, scenarios, intended users, and participants are the same as in the Mega case study.

Definition

Decision variables
Other variables
Indicators

R code for detailed analysis

  • The code calculates the difference in number of asthmas due to dampness, between policies being successful or not and compared to the initial year of 2010.
BP <- op_baseGetData("opasnet_base", "Op_en4068")
asthma <- op_baseGetData("opasnet_base", "Op_en4723")
BParray <- DataframeToArray(BP)
asthmaxBP <- IntArray(asthma, BParray, "Successful")
array <- DataframeToArray(asthmaxBP)
final <- apply(array, c(6,8,7,3), mean, na.rm=TRUE)
final <- apply(final, c(1,2,3), sum, na.rm=TRUE)
final <- final[,"1",]-final[,"0",]
final <- final[,]-final[rep(1,4),]
barplot(final, beside=TRUE, legend.text=c("2010","2020","2030","2050"))

Result

Asthma incidence increase due to building dampness in Europe: Show results

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See also

Keywords

Dampness, indoor air, asthma, Europe

References

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