Training health impact: Difference between revisions

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== Answer ==
== Answer ==


<rcode
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")
out <- make.ovariable(
name        = "health.impact",
data        = fetch("Op_en5675"),
formula      = formula.Op_en5675,
dependencies = dependencies.Op_en5675
)
print(out)
plot(out)
</rcode>


==Rationale==
==Rationale==
Line 47: Line 22:


<rcode  
<rcode  
name="formula"
label="Initiate functions"  
label="Initiate functions"  
>
>
library(OpasnetUtils)
library(xtable)
dependencies <- data.frame(
Name = c("exposure"),
Key = c("muRtYjhkphoNPQJI")
)
formula <- function(dependencies, ...) {
ComputeDependencies(dependencies, ...)
erf <- 1.5 # RR per ug / m3


erf <- data.frame(Unit = "RR per ug/m3", Result = 1.5)
background <- 100 / 100000 # cases per 100000 person-years
population <- 50000
cases      <- exposure * population * background * erf
return(cases)
}


background <- 100 / 100000 # cases per 100000 person-years
data <- tidy(op_baseGetData("opasnet_base", "Op_en5675"), "health.impact")


dependencies.Op_en5675 <- data.frame(
health.impact <- new("ovariable",
Name = "",  
name        = "health.impact",
Identifier = c("Op_en5674", "", "", ""),  
formula      = formula,
Direction = "wide",  
dependencies = dependencies,
Result = c("exposure", "erf", "population", "background")
data        = data
)
)


out <- EvalOutput(health.impact, N = 10)


formula.Op_en5675 <- function(x) {
print(xtable(out@output), type = "html")
exposure  <- make.ovariable(fetch(x[1, "Identifier"]), 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)
}


objects.put(health.impact)
</rcode>
</rcode>


Revision as of 08:36, 16 August 2012



Question

What is the health impact in the Training assessment?

Answer

Rationale

Data

Training health impact: Difference between revisions(-)
ObsYearUnitResultDescription
12012cases/year10 - 100
22020cases/year15 - 150

Formula

+ Show code

See also

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

<mfanonymousfilelist></mfanonymousfilelist>

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