Difference between revisions of "Wikisym 2012 Demo"

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(Health effects of Drinking Water Model)
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legend("topleft", legend=names(attr(colcode, "table")),title="Building Age (Yr)", fill=attr(colcode, "palette"),  cex=1.0, bty="y",bg="white")
 
legend("topleft", legend=names(attr(colcode, "table")),title="Building Age (Yr)", fill=attr(colcode, "palette"),  cex=1.0, bty="y",bg="white")
</rcode>
 
 
==Health effects of Drinking Water Model==
 
 
This example is model which is built for calculating health effects of drinking water and how water treatment processess affect to the outcome.
 
 
* [[Ground water pathogen concentrations]]
 
 
<rcode
 
            name="answer"
 
    variables="
 
        name:i.raw.class|description:Water resource|type:selection|
 
            options:
 
                'Ground water - Clean';Ground water - Clean;
 
                'Ground water - Surface water stress';Ground water - Surface water stress;
 
                'Surface water - Low stress';Surface water - Low stress;
 
                'Surface water - Medium stress';Surface water - Medium stress;
 
                'Surface water - High stress';Surface water - High stress|
 
            category:Ground water: Pathogenic concentrations|
 
                name:Kampylo|description:Cambylobacter-concentration estimation (microbe/l)|default:'Use water source specific classification'|
 
                name:Ecoli|description:E.coli O157:H7 -concentration estimation (microbe/l)|default:'Use water source specific classification'|
 
                name:Rota|description:Rotavirus-concentration estimation (microbe/l)|default:'Use water source specific classification'|
 
                name:Noro|description:Norovirus-concentration estimation (microbe/l)|default:'Use water source specific classification'|
 
                name:Crypto|description:Cryptosporidium-concentration estimation (microbe/l)|default:'Use water source specific classification'|
 
                name:Giardia|description:Giardia-concentration estimation (microbe/l)|default:'Use water source specific classification'|
 
               
 
               
 
            name:Kaupunni|description:City default values|default:'Custom'|type:selection|
 
            options:
 
                'Custom';Use values defined above;
 
                'Op_en5799';Gotham City;
 
                'Op_fi2603';Kuopio|
 
            name:Puhdistus|description:Available purification methods|type:checkbox|
 
            options:
 
                1;Traditional purification;
 
                2;Highly effective purification;
 
                3;Enhanced purification;
 
                4;Slow sand filtration;
 
                5;Limestone filtration;
 
                6;Activated carbon filtration;
 
                7;UV filtration;
 
                8;Ozonisation|
 
            default:1;4;5;6|category:Water purification: Purification processess and chlorinesation|
 
        name:KlooriAnnos|default:1.5|description:Chlorine dose (mg/l)|
 
   
 
        name:VedeKulu|default:1153|description:Water consumption (ml)|category:Water network and consumers|
 
        name:Vaestonkoko|default:100000|description:Population
 
    "
 
>
 
library(OpasnetUtils)
 
library(xtable)
 
library(reshape2)
 
    i.raw.pat.conc.val <- list(Kampylo, Ecoli, Rota, Noro, Crypto, Giardia)
 
 
    #vedenkulutus
 
   
 
    VedeKulu = data.frame(VedkulResult = VedeKulu)
 
    InpVedkul = new("ovariable",name = "InpVedkul" , output = VedeKulu)
 
 
   
 
    #Patogeenien pitoisuudet
 
   
 
    #Fetch2(data.frame(Name = "RaaPatPitLuo", Key = "AEmnj6ZNfhIHAt2X"), evaluate = TRUE)
 
    # fetching data from english Opasnet
 
    #Fetch2(data.frame(Name = "RaaPatPitLuo", Key = "kjRoRPqqAzhaG8qR"), evaluate = TRUE)
 
    temp <- tidy(op_baseGetData("opasnet_base", "Op_en5800"), objname = "RaaPatPitLuo")
 
    print(xtable(temp), type = "html")
 
 
    RaaPatPitLuo <- new("ovariable",
 
name        = "RaaPatPitLuo",
 
data        = temp
 
    )
 
   
 
  # RaaPatPitLuo@output <- RaaPatPitLuo@output[RaaPatPitLuo@output$Raakavesilähde == i.raw.class, ]
 
  RaaPatPitLuo@output <- RaaPatPitLuo@output[RaaPatPitLuo@output$Water_source == i.raw.class, ]
 
    RaaPatPitLuo@output <- merge(
 
        RaaPatPitLuo@output,
 
        data.frame(
 
            Patogeeni = c("Kampylobakteeri","E.coli O157:H7","Rotavirus","Norovirus","Cryptosporidium","Giardia"),
 
            TempResult = suppressWarnings(as.numeric(i.raw.pat.conc.val))
 
        )
 
    )
 
    RaaPatPitLuo@output$RaaPatPitLuoResult <- ifelse(
 
        is.na(RaaPatPitLuo@output$TempResult),
 
        RaaPatPitLuo@output$RaaPatPitLuoResult,
 
        RaaPatPitLuo@output$TempResult
 
    )
 
    RaaPatPitLuo@output <- RaaPatPitLuo@output[,!colnames(RaaPatPitLuo@output)%in%"TempResult"]
 
 
 
    Temp = rep(FALSE,8)
 
    Temp[Puhdistus] = TRUE
 
    Puhdistus = Temp
 
   
 
 
    InpKloori = new("ovariable", output = data.frame(KlooriResult = KlooriAnnos))
 
   
 
    #tehdaan InpVedKasTeh ovariable paalla olevista puhdistuksista
 
    Fetch2(data.frame(Name = c("VedKasTeh","VedDesTeh"), Key = c("J8AofoHKjKEOuPWK","iFnLQFpUAH3QfwGz")))
 
        VedKasTeh <- EvalOutput(VedKasTeh)
 
    VedDesTeh <- EvalOutput(VedDesTeh, substitute = TRUE)
 
 
    Puhdistus = c(Puhdistus,TRUE)
 
    Puhdistus = data.frame(tottavaitarua = Puhdistus, Vedenpuhdistusmenetelmä = c("Perinteinen puhdistus"
 
    ,"Hyvin toimva puhdistus" , "Tehostettu puhdistus" ,"Hidas hiekkasuodatus"
 
    ,"Kalkkikivisuodatus","Aktiivihiilisuodatus" ,"UV" ,"Otsonointi","Klooraus"))
 
    PuhdistusKasTeh = Puhdistus[1:6,]
 
    PuhdistusDesTeh = Puhdistus[7:9,]
 
   
 
    VedKasTeh@output = merge(VedKasTeh@output, PuhdistusKasTeh)
 
    colnames(PuhdistusDesTeh)[colnames(PuhdistusDesTeh) == "Vedenpuhdistusmenetelmä"] = "Menetelmä"
 
    VedDesTeh@output = merge(VedDesTeh@output, PuhdistusDesTeh)
 
   
 
    VedKasTeh@output[,"VedKasTehResult"] = ifelse(
 
        VedKasTeh@output[,"tottavaitarua"] == FALSE,
 
        0,
 
        VedKasTeh@output[,"VedKasTehResult"]
 
    )
 
    VedDesTeh@output[,"VedDesTehResult"] = ifelse(
 
        VedDesTeh@output[,"tottavaitarua"] == FALSE,
 
        0,
 
        VedDesTeh@output[,"VedDesTehResult"]
 
    )
 
   
 
    VedKasTeh@output <- VedKasTeh@output[,!colnames(VedKasTeh@output) %in%c("tottavaitarua")]
 
    VedDesTeh@output <- VedDesTeh@output[,!colnames(VedDesTeh@output) %in%c("tottavaitarua")]
 
 
    Fetch2(data.frame(Name = "ExpoPatAnn", Key = "PPdMOCJzOZikWlKW"))
 
   
 
    #Fetch2(data.frame(Name = "Exposure", Key = "YpqDCiPvtTUDUGMO"))
 
   
 
    Fetch2(data.frame(Name = "PatPitPuhVed", Key = "hjUP8y5Rc2laF45F"))
 
   
 
    PatPitPuhVed <- EvalOutput(PatPitPuhVed)
 
   
 
    #print(xtable(VedKasTeh@output), type = "html")
 
    #print(xtable(VedDesTeh@output), type = "html")
 
    #print(xtable(PatPitPuhVed@output), type = "html")
 
   
 
    #Exposure <- EvalOutput(Exposure, substitute = TRUE)
 
   
 
    #Exposure
 
   
 
    #print(xtable(Exposure@output), type = "html")
 
   
 
    ExpoPatAnn <- EvalOutput(ExpoPatAnn, substitute = TRUE)
 
    #print(xtable(ExpoPatAnn@output), type = "html")
 
 
#################################################################################
 
 
dose.response = ExpoPatAnn@output
 
 
Pathogen <- c("Kampylobakteeri","E.coli O157:H7","Rotavirus","Norovirus","Cryptosporidium","Giardia")
 
 
vaesto <- op_baseGetData("opasnet_base", "Op_fi2652")[,c("Ikä","Result")]
 
colnames(vaesto) <- c("Age", "Osuus")
 
 
vaesto$Populaatio <- vaesto$Osuus * Vaestonkoko
 
 
odotettu.elinika <- 81
 
 
colnames(dose.response)[colnames(dose.response) == "Patogeeni"] <- "Pathogen"
 
colnames(dose.response)[colnames(dose.response) == "ExpoPatAnnResult"] <- "P.inf"
 
colnames(dose.response)[colnames(dose.response) == "ExposureResult"] <- "Exp.pat"
 
#dose.response = data.frame(Pathogen = ExpoPatAnn@output[,"Patogeeni"],P.inf = ExpoPatAnn@output[,"ExpoPatAnnResult"])
 
P.ill.g.inf <- data.frame(Pathogen, P.ill.g.inf = c(0.33, 1 - (270 / 1540), 0.9, 0.7, 0.71, 1)) # todennäköisyys sairastua kun saa infektion
 
 
# Kampylobakteeri, DALYt per infektio
 
 
P.treat.g.ill.Kamp.Gastr <- data.frame(Pathogen = Pathogen[c(1,1,1)], Outcome = "Gastroenteritis", ill.treat = c("Untreated",
 
    "General practitioner", "Hospitalised", "Unspecified")[c(1,2,3)], P.treat.g.ill = c(0.7627, 0.2373, 0.0097))
 
 
P.treat.ill.g.inf.Kamp.Gastr <- merge(P.treat.g.ill.Kamp.Gastr, P.ill.g.inf)
 
P.treat.ill.g.inf.Kamp.Gastr$P.treat.ill.g.inf <- P.treat.ill.g.inf.Kamp.Gastr$P.ill.g.inf *
 
    P.treat.ill.g.inf.Kamp.Gastr$P.treat.g.ill
 
 
duration.ill.treat.Kamp.Gastr <- data.frame(Outcome = c("Gastroenteritis"), ill.treat = c("Untreated", "General practitioner",
 
    "Hospitalised", "Unspecified")[c(1,2,3)], dur.ill = c(5.1 / 365, 8.4 / 365, 14.39 / 365))
 
 
severity.ill.treat.Kamp.Gastr <- data.frame(Outcome = c("Gastroenteritis"), ill.treat = c("Untreated", "General practitioner",
 
    "Hospitalised", "Unspecified")[c(1,2,3)], sev.ill = c(0.067, 0.393, 0.393))
 
 
daly.ill.treat.Kamp.Gastr <- merge(P.treat.ill.g.inf.Kamp.Gastr, duration.ill.treat.Kamp.Gastr)
 
daly.ill.treat.Kamp.Gastr <- merge(daly.ill.treat.Kamp.Gastr, severity.ill.treat.Kamp.Gastr)
 
daly.ill.treat.Kamp.Gastr$dalys <- daly.ill.treat.Kamp.Gastr$P.treat.ill.g.inf * daly.ill.treat.Kamp.Gastr$dur.ill *
 
    daly.ill.treat.Kamp.Gastr$sev.ill
 
 
 
P.death.g.ill.Gastr <- 0.0004
 
P.death.g.inf.Gastr <- P.death.g.ill.Gastr * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "Kampylobakteeri"]
 
death.Gastr.life.lost <- 13.2
 
daly.death.Kamp.Gastr <- P.death.g.inf.Gastr * death.Gastr.life.lost
 
 
## GBS Kamp.
 
 
P.gbs.g.ill <- 2e-004
 
P.gbs.g.inf <- P.gbs.g.ill * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "Kampylobakteeri"]
 
dur.sev.factor.gbs <- data.frame(Outcome = c("Clinical GBS", "Residual GBS"), dur.sev.factor = c(0.29, 5.8)) # duration * severity * fraction?
 
daly.Kamp.gbs <- data.frame(dur.sev.factor.gbs$Outcome, dalys = dur.sev.factor.gbs$dur.sev.factor * P.gbs.g.inf)
 
 
P.death.g.gbs <- 0.08 / 3 # triangular 0.01, 0.02, 0.05
 
P.death.g.inf.gbs <- P.death.g.gbs * P.gbs.g.inf
 
death.gbs.life.lost <- 18.7
 
daly.death.Kamp.gbs <- P.death.g.inf.gbs * death.gbs.life.lost
 
 
## reactive arthritis Kamp.
 
 
P.arth.g.ill <- 0.02 # triangluar 0.01, 0.02, 0.03
 
P.arth.g.inf <- P.arth.g.ill * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "Kampylobakteeri"]
 
duration.arth <- 6 / 52
 
severity.arth <- 0.21
 
daly.Kamp.arth <- P.arth.g.inf * duration.arth * severity.arth
 
 
# E.coli
 
 
P.wd.g.ill <- 0.53 # watery diarrhea
 
P.wd.g.inf <- P.wd.g.ill * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "E.coli O157:H7"]
 
severity.wd <- 0.067
 
duration.wd <- 3.4 / 365
 
daly.wd.Ecoli <- P.wd.g.inf * severity.wd * duration.wd
 
 
P.hc.g.ill <- 0.47
 
P.hc.g.inf <- P.hc.g.ill * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "E.coli O157:H7"]
 
severity.hc <- 0.39
 
duration.hc <- 5.6 / 365
 
daly.hc.Ecoli <- P.hc.g.inf * severity.hc * duration.hc
 
 
P.death.g.ill.Ecoli <- 0.00027
 
P.death.g.inf.Ecoli <- P.death.g.ill.Ecoli * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "E.coli O157:H7"]
 
age.death.Ecoli <- 81 - 13.2
 
daly.death.Ecoli <- P.death.g.inf.Ecoli * (odotettu.elinika - age.death.Ecoli)
 
 
## Haemolytic uraemic syndrome (HUS)
 
 
P.hus.g.ill <- 0.01
 
P.hus.g.inf <- P.hus.g.ill * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "E.coli O157:H7"]
 
severity.hus <- 0.93
 
duration.hus <- 21 / 365
 
daly.hus.Ecoli <- P.hus.g.inf * severity.hus * duration.hus
 
 
P.death.g.hus <- 0.04
 
P.death.hus.g.inf <- P.death.g.hus * P.hus.g.inf
 
age.death.hus.Ecoli <- 81 - 26.2
 
daly.death.hus.Ecoli <- P.death.hus.g.inf * (odotettu.elinika - age.death.hus.Ecoli)
 
 
## End Stage Renal Disease (ESRD)
 
 
P.esrd.g.hus <- 0.118
 
P.esrd.g.inf <- P.hus.g.inf * P.esrd.g.hus
 
severity.duration.hus <- 8.7 # severity * duration
 
daly.esrd.Ecoli <- P.esrd.g.inf * severity.duration.hus
 
 
P.death.g.esrd <- 0.0252
 
P.death.esrd.g.inf <- P.esrd.g.inf * P.death.g.esrd
 
age.death.esrd.Ecoli <- 81 - 34
 
daly.death.esrd.Ecoli <- P.death.esrd.g.inf * (odotettu.elinika - age.death.esrd.Ecoli)
 
 
# Rotavirus
 
 
P.treat.g.ill.Rotavirus <- data.frame(Pathogen = "Rotavirus", ill.treat = c("Untreated",
 
    "General practitioner", "Hospitalised")[rep(1:3, each = 82)], Age = rep(0:81, 3), P.treat.g.ill = c(rep(0.82,5),
 
    rep(0.95, 10), rep(0.99, 50), rep(0.97, 17), rep(0.137, 5), rep(0.0244, 5), rep(0.0511, 5), rep(0.0127, 50),
 
    rep(0.0299, 17), rep(0.0416, 5), rep(0.0213, 5), rep(0, 72)))
 
 
P.treat.ill.g.inf.Rotavirus <- merge(P.treat.g.ill.Rotavirus, P.ill.g.inf)
 
P.treat.ill.g.inf.Rotavirus$P.treat.g.inf <- P.treat.ill.g.inf.Rotavirus$P.ill.g.inf * P.treat.ill.g.inf.Rotavirus$P.treat.g.ill
 
 
duration.ill.treat.Rotavirus <- data.frame(ill.treat = c("Untreated", "General practitioner","Hospitalised"), dur.ill = c(4.9 / 365,
 
    7.1 / 365, 7.7 / 365))
 
 
severity.ill.treat.Rotavirus <- data.frame(ill.treat = c("Untreated", "General practitioner", "Hospitalised"), sev.ill = c(0.067,
 
    0.393, 0.393))
 
 
daly.ill.treat.Rotavirus <- merge(P.treat.ill.g.inf.Rotavirus, duration.ill.treat.Rotavirus)
 
daly.ill.treat.Rotavirus <- merge(daly.ill.treat.Rotavirus, severity.ill.treat.Rotavirus)
 
daly.ill.treat.Rotavirus$dalys <- daly.ill.treat.Rotavirus$P.treat.g.inf * daly.ill.treat.Rotavirus$dur.ill *
 
    daly.ill.treat.Rotavirus$sev.ill
 
 
 
P.death.Rotavirus <- data.frame(Age = 0:81, P.death.g.ill = c(rep(2.13e-005, 5), rep(0, 77)))
 
P.death.Rotavirus$P.death.g.inf <- P.death.Rotavirus$P.death.g.ill * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "Rotavirus"]
 
P.death.Rotavirus$Life.lost <- odotettu.elinika - P.death.Rotavirus$Age
 
daly.death.Rotavirus <- data.frame(Age = P.death.Rotavirus$Age, dalys = P.death.Rotavirus$P.death.g.inf * P.death.Rotavirus$Life.lost)
 
 
# Norovirus
 
 
P.treat.g.ill.Norovirus <- data.frame(Pathogen = "Norovirus", ill.treat = c("Untreated",
 
    "General practitioner", "Hospitalised")[rep(1:3, each = 82)], Age = rep(0:81, 3), P.treat.g.ill = c(rep(0.94876706,5),
 
    rep(0.9902, 5), rep(0.98239, 5), rep(0.98434, 51), rep(0.992741, 16), rep(0.0448,5), rep(8.6e-003, 5), rep(0.0154, 5),
 
    rep(0.0137, 51), rep(6.17e-003, 16), rep(6.43e-003,5), rep(1.2e-003, 5), rep(2.21e-003, 5), rep(1.96e-003, 51),
 
    rep(8.85e-004, 16)))
 
 
P.treat.ill.g.inf.Norovirus <- merge(P.treat.g.ill.Norovirus, P.ill.g.inf)
 
P.treat.ill.g.inf.Norovirus$P.treat.g.inf <- P.treat.ill.g.inf.Norovirus$P.ill.g.inf * P.treat.ill.g.inf.Norovirus$P.treat.g.ill
 
 
duration.ill.treat.Norovirus <- data.frame(ill.treat = c("Untreated", "General practitioner","Hospitalised"), dur.ill = c(3.8 / 365,
 
    5.73 / 365, 7.23 / 365))
 
 
severity.ill.treat.Norovirus <- data.frame(ill.treat = c("Untreated", "General practitioner", "Hospitalised"), sev.ill = c(0.067,
 
    0.393, 0.393))
 
 
daly.ill.treat.Norovirus <- merge(P.treat.ill.g.inf.Norovirus, duration.ill.treat.Norovirus)
 
daly.ill.treat.Norovirus <- merge(daly.ill.treat.Norovirus, severity.ill.treat.Norovirus)
 
daly.ill.treat.Norovirus$dalys <- daly.ill.treat.Norovirus$P.treat.g.inf * daly.ill.treat.Norovirus$dur.ill *
 
    daly.ill.treat.Norovirus$sev.ill
 
 
P.death.Norovirus <- data.frame(Age = 0:81, P.death.g.ill = c(rep(2.94e-006, 5), rep(0, 61), rep(2.04e-004, 16)))
 
P.death.Norovirus$P.death.g.inf <- P.death.Norovirus$P.death.g.ill * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "Norovirus"]
 
P.death.Norovirus$Life.lost <- odotettu.elinika - P.death.Norovirus$Age
 
daly.death.Norovirus <- data.frame(Age = P.death.Norovirus$Age, dalys = P.death.Norovirus$P.death.g.inf * P.death.Norovirus$Life.lost)
 
 
# Cryptosporidium
 
 
P.treat.g.ill.Crypt <- data.frame(Pathogen = "Cryptosporidium", ill.treat = c("Untreated",
 
    "General practitioner", "Hospitalised")[rep(1:3, each = 82)], Age = rep(0:81, 3), P.treat.g.ill = c(rep(0.9175730049999999,5),
 
    rep(0.80937, 5), rep(0.6810499999999999, 5), rep(0.9774191, 50), rep(0.94706, 17), rep(0.082,5), rep(0.188, 5), rep(0.316, 5),
 
    rep(0.0209, 50), rep(0.0367, 17), rep(4.26e-004,5), rep(2.63e-003, 5), rep(2.95e-003, 5), rep(1.66e-003, 50), rep(0.0146, 17)))
 
 
P.treat.ill.g.inf.Crypt <- merge(P.treat.g.ill.Crypt, P.ill.g.inf)
 
P.treat.ill.g.inf.Crypt$P.treat.g.inf <- P.treat.ill.g.inf.Crypt$P.ill.g.inf * P.treat.ill.g.inf.Crypt$P.treat.g.ill
 
 
duration.ill.treat.Crypt <- data.frame(ill.treat = c("Untreated", "General practitioner","Hospitalised"), dur.ill = c(3.5 / 365,
 
    7 /365, 18.4 / 365))
 
 
severity.ill.treat.Crypt <- data.frame(ill.treat = c("Untreated", "General practitioner", "Hospitalised"), sev.ill = c(0.067,
 
    0.393, 0.393))
 
 
daly.ill.treat.Crypt <- merge(P.treat.ill.g.inf.Crypt, duration.ill.treat.Crypt)
 
daly.ill.treat.Crypt <- merge(daly.ill.treat.Crypt, severity.ill.treat.Crypt)
 
daly.ill.treat.Crypt$dalys <- daly.ill.treat.Crypt$P.treat.g.inf * daly.ill.treat.Crypt$dur.ill *
 
    daly.ill.treat.Crypt$sev.ill
 
 
P.death.Crypt <- data.frame(Age = 0:81, P.death.g.ill = c(rep(9.95e-007, 5), rep(0, 10), rep(2.09e-005, 50), rep(1.64e-003, 17)))
 
P.death.Crypt$P.death.g.inf <- P.death.Crypt$P.death.g.ill * P.ill.g.inf$P.ill.g.inf[P.ill.g.inf$Pathogen == "Cryptosporidium"]
 
P.death.Crypt$Life.lost <- odotettu.elinika - P.death.Crypt$Age
 
daly.death.Crypt <- data.frame(Age = P.death.Crypt$Age, dalys = P.death.Crypt$P.death.g.inf * P.death.Crypt$Life.lost)
 
 
# Giardia
 
 
P.treat.g.ill.Giardia <- data.frame(Pathogen = "Giardia", ill.treat = c("Untreated",
 
    "General practitioner", "Hospitalised")[rep(1:3, each = 82)], Age = rep(0:81, 3), P.treat.g.ill = c(rep(0.9376,5),
 
    rep(0.91034, 5), rep(0.72642, 5), rep(0.92486, 50), 0.54596, rep(0.5365, 16), rep(0.0609,5), rep(0.0852, 5), rep(0.272, 5),
 
    rep(0.0721, 50), rep(0.451, 17), rep(1.5e-003,5), rep(4.46e-003, 5), rep(1.58e-003, 5), rep(3.04e-003, 51), rep(0.0125, 16)))
 
 
P.treat.ill.g.inf.Giardia <- merge(P.treat.g.ill.Giardia, P.ill.g.inf)
 
P.treat.ill.g.inf.Giardia$P.treat.g.inf <- P.treat.ill.g.inf.Giardia$P.ill.g.inf * P.treat.ill.g.inf.Giardia$P.treat.g.ill
 
 
duration.ill.treat.Giardia <- data.frame(ill.treat = c("Untreated", "General practitioner","Hospitalised"), dur.ill = c(10 / 365,
 
    10 /365, 30 / 365))
 
 
severity.ill.treat.Giardia <- data.frame(ill.treat = c("Untreated", "General practitioner", "Hospitalised"), sev.ill = c(0.067,
 
    0.393, 0.393))
 
 
daly.ill.treat.Giardia <- merge(P.treat.ill.g.inf.Giardia, duration.ill.treat.Giardia)
 
daly.ill.treat.Giardia <- merge(daly.ill.treat.Giardia, severity.ill.treat.Giardia)
 
daly.ill.treat.Giardia$dalys <- daly.ill.treat.Giardia$P.treat.g.inf * daly.ill.treat.Giardia$dur.ill *
 
    daly.ill.treat.Giardia$sev.ill
 
 
# yhteenveto DALYistä
 
 
Health.effects <- vaesto[,c("Age","Populaatio")]
 
 
Health.effects$Untreated.Gastr.Kamp <- daly.ill.treat.Kamp.Gastr[daly.ill.treat.Kamp.Gastr$ill.treat == "Untreated", c("dalys")]
 
Health.effects$GP.Gastr.Kamp <- daly.ill.treat.Kamp.Gastr[daly.ill.treat.Kamp.Gastr$ill.treat == "General practitioner", c("dalys")]
 
Health.effects$Hospitalised.Gastr.Kamp <- daly.ill.treat.Kamp.Gastr[daly.ill.treat.Kamp.Gastr$ill.treat == "Hospitalised", c("dalys")]
 
Health.effects$Death.Gastr.Kamp <- daly.death.Kamp.Gastr
 
 
Health.effects$Clinical.GBS.Kamp <- daly.Kamp.gbs$dalys[1]
 
Health.effects$Residual.GBS.Kamp <- daly.Kamp.gbs$dalys[2]
 
Health.effects$Death.GBS.Kamp <- daly.death.Kamp.gbs
 
 
Health.effects$Arth.Kamp <- daly.Kamp.arth
 
 
Health.effects$WD.Ecoli <- daly.wd.Ecoli
 
Health.effects$HC.Ecoli <- daly.hc.Ecoli
 
Health.effects$Death.Ecoli <- daly.death.Ecoli
 
 
Health.effects$HUS.Ecoli <- daly.hus.Ecoli
 
Health.effects$Death.HUS.Ecoli <- daly.death.hus.Ecoli
 
 
Health.effects$ESRD.Ecoli <- daly.esrd.Ecoli
 
Health.effects$Death.ESRD.Ecoli <- daly.death.esrd.Ecoli
 
 
Health.effects <- merge(Health.effects, daly.ill.treat.Rotavirus[daly.ill.treat.Rotavirus$ill.treat == "Untreated", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "Untreated.Rotavirus"
 
Health.effects <- merge(Health.effects, daly.ill.treat.Rotavirus[daly.ill.treat.Rotavirus$ill.treat == "General practitioner", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "GP.Rotavirus"
 
Health.effects <- merge(Health.effects, daly.ill.treat.Rotavirus[daly.ill.treat.Rotavirus$ill.treat == "Hospitalised", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "Hospitalised.Rotavirus"
 
Health.effects <- merge(Health.effects, daly.death.Rotavirus)
 
colnames(Health.effects)[ncol(Health.effects)] <- "Death.Rotavirus"
 
 
Health.effects <- merge(Health.effects, daly.ill.treat.Norovirus[daly.ill.treat.Norovirus$ill.treat == "Untreated", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "Untreated.Norovirus"
 
Health.effects <- merge(Health.effects, daly.ill.treat.Norovirus[daly.ill.treat.Norovirus$ill.treat == "General practitioner", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "GP.Norovirus"
 
Health.effects <- merge(Health.effects, daly.ill.treat.Norovirus[daly.ill.treat.Norovirus$ill.treat == "Hospitalised", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "Hospitalised.Norovirus"
 
Health.effects <- merge(Health.effects, daly.death.Norovirus)
 
colnames(Health.effects)[ncol(Health.effects)] <- "Death.Norovirus"
 
 
Health.effects <- merge(Health.effects, daly.ill.treat.Crypt[daly.ill.treat.Crypt$ill.treat == "Untreated", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "Untreated.Crypt"
 
Health.effects <- merge(Health.effects, daly.ill.treat.Crypt[daly.ill.treat.Crypt$ill.treat == "General practitioner", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "GP.Crypt"
 
Health.effects <- merge(Health.effects, daly.ill.treat.Crypt[daly.ill.treat.Crypt$ill.treat == "Hospitalised", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "Hospitalised.Crypt"
 
Health.effects <- merge(Health.effects, daly.death.Crypt)
 
colnames(Health.effects)[ncol(Health.effects)] <- "Death.Crypt"
 
 
Health.effects <- merge(Health.effects, daly.ill.treat.Giardia[daly.ill.treat.Giardia$ill.treat == "Untreated", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "Untreated.Giardia"
 
Health.effects <- merge(Health.effects, daly.ill.treat.Giardia[daly.ill.treat.Giardia$ill.treat == "General practitioner", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "GP.Giardia"
 
Health.effects <- merge(Health.effects, daly.ill.treat.Giardia[daly.ill.treat.Giardia$ill.treat == "Hospitalised", c("Age", "dalys")])
 
colnames(Health.effects)[ncol(Health.effects)] <- "Hospitalised.Giardia"
 
 
Health.effects <- reshape(Health.effects, idvar = c("Age"), times = colnames(Health.effects)[-c(1,2)], timevar = "Outcome",
 
    varying = list(colnames(Health.effects)[-c(1,2)]), direction = "long")
 
colnames(Health.effects)[4] <- "P.daly.g.inf"
 
   
 
Health.effects$Pathogen <- NA
 
Health.effects$Pathogen[grep(".Kamp", Health.effects$Outcome)] <- Pathogen[1]
 
Health.effects$Pathogen[grep(".Ecoli", Health.effects$Outcome)] <- Pathogen[2]
 
Health.effects$Pathogen[grep(".Rotavirus", Health.effects$Outcome)] <- Pathogen[3]
 
Health.effects$Pathogen[grep(".Norovirus", Health.effects$Outcome)] <- Pathogen[4]
 
Health.effects$Pathogen[grep(".Crypt", Health.effects$Outcome)] <- Pathogen[5]
 
Health.effects$Pathogen[grep(".Giardia", Health.effects$Outcome)] <- Pathogen[6]
 
 
Health.effects <- merge(Health.effects, dose.response[,c("Pathogen", "P.inf")])
 
Health.effects$DALYs <- (1 - (1 - Health.effects$P.inf * Health.effects$P.daly.g.inf)^365) * Health.effects$Populaatio
 
 
 
 
temp <- merge(dose.response, P.ill.g.inf)
 
 
############# TULOKSET #########################################################################################################
 
 
cat("<span style='font-size: 1.2em;font-weight:bold;'>Patogeenien konsentraatio raakavedessä</span>\n")
 
print(xtable(RaaPatPitLuo@output), type='html') # Patogeenien konsentraatio raakavedessä
 
cat("<span style='font-size: 1.2em;font-weight:bold;'>Patogeenien log vähenemä puhdistuksessa</span>\n")
 
print(xtable(VedKasTeh@output), type='html') # Patogeenien log vähenemä puhdistuksessa
 
print(xtable(VedDesTeh@output), type='html') # Patogeenien log vähenemä desinfioinnissa
 
cat("<span style='font-size: 1.2em;font-weight:bold;'>Patogeeneille altistuminen ja infektion todennäköisyys</span>\n")
 
cat(colnames(dose.response), "\n")
 
#cat(colnames(ExpoPatAnn@output), "\n")
 
print(xtable(dose.response[,c("Pathogen", "Exp.pat", "P.inf", "VedDesTehSource")]), type="html") # Patogeeneille altistuminen ja infektion todennäköisyys
 
 
cat("<span style='font-size: 1.2em;font-weight:bold;'>Estimated health effects</span>\n")
 
 
cat(sum((1 - (1 - temp$P.ill.g.inf * temp$P.inf)^365) * Vaestonkoko, na.rm = TRUE), " stomach flus per year \n")
 
 
cat(sum(Health.effects$DALYs, na.rm = TRUE), " DALY's from stomach flus \n")   
 
 
</rcode>
 
</rcode>

Revision as of 12:38, 24 August 2012

Polygons on dynamic Google Maps

This example plots municipalities of Finland on Google Maps using data from National Land Survey of Finland.

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Points on dynamic Google Maps

This examples plots buildings of Kuopio on Google Maps. User can give the minimum age of buildings to plot as an input parameter.


Building minimum age:

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Large quantity of points on a static Google Maps

This example plots large number of point data on static Google Maps. The map produced in this example shows the age (in years) distribution of buildings within Kuopio. User can select the number of age classes (4,6 or 8) and the type of classification.

Number of classes:

Type of classification:

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