Water guide

Water guide is a model for calculating health risks of contaminated raw water in a waterworks. There is a Finnish version that is more flexible about the input values.

Situation Classification of raw water: Surface water - low contamination Surface water - medium contamination Surface water - high contamination Ground water - clean Gound water - surface water contamination Size of the exposed population: Water cleaning: Cleaning process and chlorination Water cleaning methods in use: Traditional cleaning Well working cleaning Enhanced cleaning Slow sand filtration Lime stone filtration Active carbon filtration UV filtration Ozone treatment Chlorine dose (mg/l): + Show code- Hide code library(OpasnetUtils) library(reshape2) # Nämä arvot kysytään käyttäjältä täysverisessä mallissa Kampylo <- 'Luokituksen mukainen' Ecoli <- 'Luokituksen mukainen' Rota <- 'Luokituksen mukainen' Noro <- 'Luokituksen mukainen' Crypto <- 'Luokituksen mukainen' Giardia <- 'Luokituksen mukainen' Kaupunki <- 'Custom' IVedenkulutus <- 1153 IRaakaPitoisuus <- list(Kampylo, Ecoli, Rota, Noro, Crypto, Giardia) # Vedenkulutus if (!is.na(suppressWarnings(as.numeric(IVedenkulutus)))) { InpVedenkulutus = data.frame(VedenkulutusResult = IVedenkulutus) InpVedenkulutus = Ovariable("Vedenkulutus", output = InpVedenkulutus) } # Patogeenien pitoisuudet objects.latest("Op_fi2655", "muuttuja") # RaakaPitoisuus, customoitia varten RaakaPitoisuus <- EvalOutput(RaakaPitoisuus) temp <- RaakaPitoisuus@output temp <- temp[as.character(temp$Raakavesilähde) == RaakaLuokka, ] temp <- merge( temp, data.frame( Patogeeni = c("Kampylobakteeri","E.coli O157:H7","Rotavirus","Norovirus","Cryptosporidium","Giardia"), TempResult = suppressWarnings(as.numeric(IRaakaPitoisuus)) ) ) temp$RaakaPitoisuusResult <- ifelse( is.na(temp$TempResult), temp$RaakaPitoisuusResult, temp$TempResult ) RaakaPitoisuus@output <- temp[, !colnames(temp) %in% c("TempResult", "Raakavesilähde")] temp <- rep(FALSE,9) # vaihtoehdot + klooraus joka on mallin rakenteesta johtuen aina epätosi temp[Puhdistus] <- TRUE Puhdistus <- temp if (!is.na(suppressWarnings(as.numeric(IKlooriAnnos)))) if (IKlooriAnnos > 0) { InpKlooriAnnos <- Ovariable("KlooriAnnos", output = data.frame(KlooriAnnosResult = IKlooriAnnos)) } # Käsitellään puhdistusmenetelmät käsin tätä mallia varten riippuvuudet <- data.frame( Name = c("RaakaPitoisuus", "Desinfiointi", "PuhdistusTeho", "KloorausTeho"), Ident = c("Op_fi2655/muuttuja", "Op_fi2993/muuttuja", "Op_fi2656/muuttuja", "Op_fi2667/tehokkuus") ) objects.latest("Op_fi2993", "muuttuja") # Desinfiointi objects.latest("Op_fi2656", "muuttuja") # PuhdistusTeho PuhdistusTeho <- EvalOutput(PuhdistusTeho) Desinfiointi <- EvalOutput(Desinfiointi) Puhdistus <- data.frame( Käytössä = Puhdistus, Puhdistusmenetelmä = c("Perinteinen puhdistus", "Hyvin toimva puhdistus", "Tehostettu puhdistus" ,"Hidas hiekkasuodatus", "Kalkkikivisuodatus", "Aktiivihiilisuodatus", "UV", "Otsonointi", "Klooraus") ) PuhdistusTeho@output <- merge(PuhdistusTeho@output, Puhdistus[1:6,]) # Vedenkäsittelymenetelmät Desinfiointi@output <- merge(Desinfiointi@output, Puhdistus[7:9,]) # Desinfiointimenetelmät PuhdistusTeho@output$PuhdistusTehoResult <- ifelse( PuhdistusTeho@output$Käytössä, PuhdistusTeho@output$PuhdistusTehoResult, 0 ) Desinfiointi@output$DesinfiointiResult <- ifelse( Desinfiointi@output$Käytössä, Desinfiointi@output$DesinfiointiResult, 0 ) # Poistetaan "Käytössä" kolumin PuhdistusTeho@output <- PuhdistusTeho@output[, !colnames(PuhdistusTeho@output) == "Käytössä"] Desinfiointi@output <- Desinfiointi@output[, !colnames(Desinfiointi@output) == "Käytössä"] objects.latest("Op_fi1759", "muuttuja") # Vaste Vaste <- EvalOutput(Vaste, substitute = TRUE) ################################################################################# dose.response = Vaste@output Pathogen <- c("Kampylobakteeri","E.coli O157:H7","Rotavirus","Norovirus","Cryptosporidium","Giardia") vaesto <- opbase.data("Op_fi2652")[,c("Ikä","Result")] colnames(vaesto) <- c("Age", "Osuus") vaesto$Populaatio <- vaesto$Osuus * Vaestonkoko odotettu.elinika <- 81 colnames(dose.response)[colnames(dose.response) == "Patogeeni"] <- "Pathogen" colnames(dose.response)[colnames(dose.response) == "VasteResult"] <- "P.inf" colnames(dose.response)[colnames(dose.response) == "AltistuminenResult"] <- "Exp.pat" P.ill.g.inf <- data.frame(Pathogen, P.ill.g.inf = c(0.33, 1 - (270 / 1540), 0.9, 0.7, 0.71, 1)) # todennäköisyys sairastua kun saa infektion # Kampylobakteeri, DALYt per infektio P.treat.g.ill.Kamp.Gastr <- data.frame(Pathogen = Pathogen[c(1,1,1)], Outcome = "Gastroenteritis", ill.treat = c("Untreated", "General practitioner", "Hospitalised", "Unspecified")[c(1,2,3)], P.treat.g.ill = c(0.7627, 0.2373, 0.0097)) P.treat.ill.g.inf.Kamp.Gastr <- merge(P.treat.g.ill.Kamp.Gastr, P.ill.g.inf) P.treat.ill.g.inf.Kamp.Gastr$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) ############# EXTRA ########################################### MikrobienLogVähenemä <- combine(Desinfiointi, PuhdistusTeho, KloorausTeho, name = "MikrobienLogVähenemä") MikrobienLogVähenemä@output[["Puhdistusmenetelmä"]][ MikrobienLogVähenemä@output[["MikrobienLogVähenemäSource"]] == "KloorausTehoFormula" ] <- "Klooraus" #MikrobienLogVähenemä <- oapply(MikrobienLogVähenemä, cols = c("Puhdistusmenetelmä", "KlooriAnnosSource"), FUN = sum, na.rm = TRUE) #MikrobienLogVähenemä@output <- fillna(MikrobienLogVähenemä@output, colnames(MikrobienLogVähenemä@output)[MikrobienLogVähenemä@marginal]) ############# TULOKSET ######################################################################################################### #cat("Pathogen concentration in the raw water\n") #oprint(RaakaPitoisuus) # Patogeenien konsentraatio raakavedessä #cat("Pathogen log reduction in the treatment\n") #oprint(MikrobienLogVähenemä) temp2 <- Vaste@output temp2$VasteResult <- temp2$VasteResult * 1000 cat("Probability of infection caused by water pathogens for an individual (per mille per day)\n") oprint(temp2[,c("Patogeeni", "VasteResult")], digits = 4) # Patogeeneille altistuminen ja infektion todennäköisyys (vaste) cat("Estimated health impact\n") cat(sum((1 - (1 - temp$P.ill.g.inf * temp$P.inf)^365) * Vaestonkoko, na.rm = TRUE), " gastroenterisis cases per year\n") cat(sum(Health.effects$DALYs, na.rm = TRUE), " DALYs because of gastroenteritis \n")