Training health impact: Difference between revisions

Latest revision as of 15:48, 24 March 2015

This page is a knowledge crystal of subtype variable. The page identifier is Op_en5675
Moderator:Jouni (see all)
This page is a stub. You may improve it into a full page.
Upload data {{#opasnet_base_link:Op_en5675}}

Question

What is the health impact in the Training assessment?

Answer

+ Show code - Hide code


library(OpasnetUtils)
library(ggplot2)

objects.latest("Op_en5675", code_name = "initiate") # [[Training health impact]]

health_impact <- EvalOutput(health_impact)

oprint(summary(health_impact))

ggplot(health_impact@output, aes(x = health_impactResult, colour = Year)) +
	geom_density() +
	facet_grid(Trait ~ Year) +
	theme_grey(base_size = 24)

Rationale

Data

Training health impact(cases /(µg/m3) /a)
Obs	Trait	Result	Description
1	Respiratory disease	20 - 30

Dependencies

Training exposure

Calculations

+ Show code - Hide code


library(OpasnetUtils)

health_impact <- Ovariable("health_impact", 
	dependencies = data.frame(Name = "exposure", Ident = "Op_en5674/initiate"), # [[Training exposure]] exposure
	formula = function(...) {
		ERF <- Ovariable("ERF", ddata = "Op_en5675") # [[Training health impact]]
		colnames(ERF@data) <- gsub("[ \\.]", "_", colnames(ERF@data))

		out <- exposure * ERF

		return(out)
	}
)

objects.store(health_impact)

cat("Ovariable health_impact saved.\n")

**Materials and examples for training in Opasnet and open assessment**
Help pages	Wiki editing • How to edit wikipages • Quick reference for wiki editing • Drawing graphs • Opasnet policies • Watching pages • Writing formulae • Word to Wiki • Wiki editing Advanced skills
Training assessment (examples of different objects)	Training assessment • Training exposure • Training health impact • Training costs • Climate change policies and health in Kuopio • Climate change policies in Kuopio
Methods and concepts	Assessment • Variable • Method • Question • Answer • Rationale • Attribute • Decision • Result • Object-oriented programming in Opasnet • Universal object • Study • Formula • OpasnetBaseUtils • Open assessment • PSSP
Terms with changed use	Scope • Definition • Result • Tool

Keywords

References

Related files

@@ Line 1: / Line 1: @@
 [[Category:Costs and valuations]]
 [[Category:Opasnet training]]
+[[Category:Contains R code]]
 {{variable|moderator=Jouni|stub=Yes}}
@@ Line 9: / Line 10: @@
 == Answer ==
-<rcode
+<rcode 	graphics=1>
-	name="answer"
-	label="Run code"
-	graphics="1"
-	include="
-		page:Opasnet_(R_library)|name:answer|
-		page:Training_health_impact|name:formula|
-		page:Training_exposure|name:formula
-	"
-	variables="name:population|description:What is the size of the population|default:100000"
->
-cat("Initiation successful. Now starting the model.\n")
+library(OpasnetUtils)
+library(ggplot2)
-out <- make.ovariable(
+objects.latest("Op_en5675", code_name = "initiate") # [[Training health impact]]
-	name         = "health.impact",
-	data         = fetch("Op_en5675"),
+health_impact <- EvalOutput(health_impact)
-	formula      = formula.Op_en5675,
-	dependencies = dependencies.Op_en5675
+oprint(summary(health_impact))
-)
-print(out)
+ggplot(health_impact@output, aes(x = health_impactResult, colour = Year)) +
-plot(out)
+	geom_density() +
+	facet_grid(Trait ~ Year) +
+	theme_grey(base_size = 24)
 </rcode>
@@ Line 39: / Line 32: @@
 ===Data===
-<t2b index="Year,Observation" locations="Unit,Result,Description" unit="-">
+<t2b index="Trait" obs="Result" desc="Description" unit="cases /(µg/m3) /a">
-|cases/year|10 - 100|
+Respiratory disease|20 - 30|
-|cases/year|15 - 150|
 </t2b>
-===Formula===
+===Dependencies===
-<rcode
+* [[Training exposure]]
-	name="formula"
-	label="Initiate functions"
->
-erf <- data.frame(Unit = "RR per ug/m3", Result = 1.5)
+===Calculations===
-background <- 100 / 100000 # cases per 100000 person-years
+<rcode label="Initiate ovariable" name="initiate">
-dependencies.Op_en5675 <- data.frame(
+library(OpasnetUtils)
-	Name = "",
-	Identifier = c("Op_en5674", "", "", ""),
+health_impact <- Ovariable("health_impact",
-	Direction = "wide",
+	dependencies = data.frame(Name = "exposure", Ident = "Op_en5674/initiate"), # [[Training exposure]] exposure
-	Result = c("exposure", "erf", "population", "background")
+	formula = function(...) {
+		ERF <- Ovariable("ERF", ddata = "Op_en5675") # [[Training health impact]]
+		colnames(ERF@data) <- gsub("[ \\.]", "_", colnames(ERF@data))
+		out <- exposure * ERF
+		return(out)
+	}
 )
+objects.store(health_impact)
-formula.Op_en5675 <- function(x) {
+cat("Ovariable health_impact saved.\n")
-	exposure   <- make.ovariable(fetch(x[1, "Result"]), name = "exposure")
-	erf        <- make.ovariable(fetch(x[2, "Result"]), name = "erf")
-	population <- make.ovariable(
-		data = fetch(x[3, "Result"]),
-		name = "population",
-		formula = function(x) {return(interpret("50000-150000"))},
-		dependencies = data.frame(Result = 0)
-	)
-	background <- make.ovariable(fetch(x[4, "Result"]), name = "background")
-	cases      <- population * background * exp(exposure * log(erf))
-	return(cases)
-}
 </rcode>
@@ Line 90: / Line 75: @@
 ==Related files==
-{{mfiles}}

Training health impact: Difference between revisions

Latest revision as of 15:48, 24 March 2015

Contents

Question

Answer

Rationale

Data

Dependencies

Calculations

See also

Keywords

References

Related files

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