data-raw/transform_code_lists.R
In jason-p-pickering/data-pack-importer: Utilities for importing the ICPI Data pack into DATIM
require(dplyr)
require(stringr)
#' @title getCOPDataElements()
#'
#' @description Extracts DATIM dataElement/categoryOptionCombo code list for specified dataset & time period.
#' @param ds DATIM Dataset UID.
#' @param pd Code indicating which time period for which to query code list.
#' @param lvl Organization unit level related to code list in question (P=PSNU, C=Community, F=Facility)
#' @return Returns a dataframe ready for use in preparing source files.
#'
getCOPDataElements <- function(ds,pd,lvl) {
de <- read.csv(url(paste0(getOption("baseurl"),"api/sqlViews/DotdxKrNZxG/data.csv?var=dataSets:",ds)),stringsAsFactors=FALSE,header=TRUE) %>%
mutate(period = pd) %>%
mutate(level = lvl) %>%
mutate(pdLvl = paste("pd",period,level,sep="_",collapse=NULL)) %>%
mutate(indicator = str_trim(str_extract(str_replace_all(dataelement,"(?<=IMPATT)\\.","_"),"^\\w+\\s")))
return(de)
}
transformDEs <- function(de){
ds <- de %>%
#Prepare cross-period codes for each MER indicator
mutate(COPdeName = str_replace_all(str_replace_all(dataelement,"(\\) TARGET)|( v\\d)|\\:(.)*| T_PSNU|\\)|,|\\(","")," |/","_")) %>%
mutate(COPcocName = as.character(categoryoptioncombo)) %>%
mutate(COPuid = paste(dataelementuid,categoryoptioncombouid,sep=".",collapse=NULL)) %>%
#Break out dataElementName for helpful referencing
mutate(indicator = str_trim(str_extract(str_replace_all(dataelement,"IMPATT\\.",""),"^\\w+\\s"))) %>%
mutate(numeratorDenom = ifelse(str_detect(code,"_[ND]_"),
str_replace_all(str_extract(code,"_[ND]_"),"_",""),
"")) %>%
mutate(supportType = ifelse(str_detect(dataelement,"(DSD|TA)(?=\\W)"),
str_replace_all(str_extract(dataelement,"(DSD|TA)(?=\\W)"),"_",""),
"")) %>%
#Break out categoryOptionCombo for helpful referencing
##Modality
mutate(Modality=ifelse(str_detect(COPdeName,"HTS_TST(.)+(Emergency_Ward_|HomeMod_|Index_|IndexMod_|Inpat_|Malnutrition_|MobileMod_|OtherMod_|OtherPITC_|Pediatric_|PMTCT_ANC_|STI_Clinic_|TBClinic_|VCT_|VCTMod_|VMMC_)")
,str_extract(dataelement,"Emergency Ward|HomeMod|IndexMod|Index|Inpat|Malnutrition|MobileMod|OtherMod|OtherPITC|Pediatric|PMTCT ANC|STI Clinic|TBClinic|VCTMod|VCT|VMMC")
,"")) %>%
##Age
mutate(Age=case_when(str_detect(COPdeName,"Age") ~ str_trim(str_extract(COPcocName,"(?<!D)(<|<=)?( )?\\d{1,2}( months)?(( )?-( )?\\d{1,2}( months| years)?|\\+)?|Unknown Age"))
,str_detect(dataelement,"HTS_TST(.)+(Malnutrition|Pediatric)") ~ "<5"
,TRUE~"")) %>%
##AggregatedAge
mutate(AggregatedAge=Age)
word=c("< 2 months","<= 2 months","2 - 12 months","<1","<5","1-9","2 months - 9 years","<10","10-14","<15","15-17","15-19","18-24","20-24","25-29","15-29","30-34","35-39","40-49","30-49","25-49","15\\+","25\\+","30\\+","50\\+","Unknown Age")
tran=c(rep("<15",10),rep("15+",15),"Unknown Age")
dict=data.frame(word,tran,stringsAsFactors = FALSE)
for (k in 1:length(dict$word)){ds$AggregatedAge=str_replace_all(ds$AggregatedAge,paste0("^",dict$word[k],"$"),dict$tran[k])}
##Aggregated Age Flag (to distinguish otherwise identical indicators)
ds <- ds %>% mutate(AggregatedAgeFlag=ifelse(str_detect(dataelement,"Age Aggregated|(PLHIV|HIV_PREV)(.)+Age")
,"AgeAggregated"
,"")) %>%
##Sex
mutate(Sex=ifelse(str_detect(COPdeName,"Sex|HTS_TST(.)+VCT_Age_Result")
|str_detect(COPcocName,"Female PWID|Male PWID|MSM|FSW")
,str_extract(COPcocName,"Male|Female|Unknown Sex|MSM|FSW")
,""))
dict=data.frame(word=c("MSM","FSW"),tran=c("Male","Female"),stringsAsFactors = FALSE)
for (k in 1:length(dict$word)){ds$Sex<-str_replace_all(ds$Sex,dict$word[k],dict$tran[k])}
rm(dict)
ds <- ds %>%
mutate(Sex=case_when(str_detect(dataelement,"HTS_TST|OVC_SERV|PMTCT_EID|TB_ART|TX_(CURR|NEW|PVLS|RET)") & str_detect(Age,"(<1|1-9|<5)$") ~ "Unknown Sex",TRUE~Sex)) %>%
mutate(Sex=case_when(str_detect(dataelement,"HTS_TST(.)+VMMC|VMMC_CIRC") ~ "Male"
,str_detect(dataelement,"HTS_TST(.)+PMTCT|PMTCT_ART|PMTCT_STAT") ~ "Female"
,TRUE ~ Sex)) %>%
##HIVStatus
# Convert to "HIV Positive", "HIV Negative", "HIV Unknown"
mutate(HIVStatus=ifelse(str_detect(COPdeName,"_Result|_HIVStatus|_KnownNewResult|_KnownNewPosNeg|OVC_HIVSTAT_(.)+_ReportedStatus")
| (str_detect(COPdeName,"KP_PREV_(N|D)_(DSD|TA)_KeyPop_Status|PP_PREV_(N|D)_(DSD|TA)_Status") & str_detect(COPcocName,"Positive|Negative"))
,str_extract(COPcocName,"Positive|Negative|Unknown(?=($|,))|Undisclosed")
,"")) %>%
mutate(HIVStatus=str_replace(HIVStatus,"Undisclosed","Unknown")) %>%
mutate(HIVStatus=case_when(str_detect(COPdeName,"^(IMPATT.PLHIV|PMTCT_ART|TB_ART|TB_PREV|TX_CURR|TX_NEW|TX_PVLS|TX_RET|TX_TB)|OVC_HIVSTAT_(.)+_StatusPosART") & !(HIVStatus %in% ("Positive")) ~ "Positive"
,str_detect(COPdeName,"OVC_HIVSTAT(.)+StatusNotRep") & !(HIVStatus %in% ("Unknown")) ~ "Unknown"
,str_detect(COPdeName,"HTS_TST(.)+Positive") ~ "Positive"
,TRUE ~ HIVStatus)) %>%
##KeyPop
mutate(KeyPop=ifelse(str_detect(COPdeName,"_KeyPop")
,str_extract(COPcocName,"FSW|MSM(( not)? SW)?|TG(( not)? SW)?|PWID|People in prisons and other enclosed settings|Other Key Populations")
,"")) %>%
##KnownNewStatus
mutate(KnownNewStatus=ifelse(str_detect(COPcocName,"Known at Entry|Newly Tested or Testing Referred|Newly Identified|Declined Testing Or Testing Referral")
,str_extract(COPcocName,"Known|New|Declined")
,"")) %>%
##NewExistingART
mutate(NewExistingART=ifelse(str_detect(COPdeName,regex("NewExistingArt",ignore_case=T))
,str_extract(COPcocName,"New|Already")
,"")) %>%
##Indication
mutate(Indication=ifelse(str_detect(COPdeName,"TX_PVLS(.)+(Indication|RoutineTargeted)")
,str_extract(COPcocName,"Routine|Targeted|Undocumented Test Indication")
,"")) %>%
##TBStatus
mutate(TBStatus=ifelse(str_detect(COPdeName,"TX_NEW(.)+TB_Diagnosis|TB_STAT|TB_ART|TX_TB_(N|D(.)+(TBScreen|PositiveScreen))")
,ifelse(str_detect(COPdeName,"TX_TB_D")
,paste0("TB ",str_extract(COPcocName,"(?<=(TB Screen - |^))(Posi|Nega)tive"))
,"TB Positive")
,"")) %>%
##pregBF
mutate(pregBF=ifelse(str_detect(dataelement,"PMTCT_(ART|STAT)|TX_(NEW|RET|PVLS)(.)+PregnantOrBreastfeeding")
,ifelse(str_detect(dataelement,"PMTCT_(ART|STAT)")
,"Pregnant"
,str_extract(COPcocName,"Pregnant|Breastfeeding"))
,"")) %>%
##VMMCTechnique
mutate(VMMCTechnique=ifelse(str_detect(dataelement,"VMMC_CIRC(.)+Tech")
,str_extract(COPcocName,"Device based|Surgical Technique")
,""))
##otherDisagg
pattern=paste(ifelse(ds$KeyPop=="","0000",ds$KeyPop)
,ifelse(ds$Sex=="","0000",ds$Sex)
,ifelse(ds$Age=="","0000",paste0("\\Q",ds$Age,"\\E"))
,"TB Screen - (Posi|Nega)tive"
,ifelse(ds$HIVStatus=="","0000",ds$HIVStatus)
,"Declined Testing Or Testing Referral","Newly Tested or Testing Referred","Newly Identified","Known at Entry","Life-long ART"
,ifelse(ds$KnownNewStatus=="","0000",ds$KnownNewStatus)
,ifelse(ds$NewExistingART=="","0000",ds$NewExistingART)
,ifelse(ds$Indication=="","0000",ds$Indication)
,ifelse(ds$pregBF=="","0000",ds$pregBF)
,ifelse(ds$VMMCTechnique=="","0000",ds$VMMCTechnique)
,"default"
,sep="|")
ds <- ds %>%
mutate(otherDisagg=str_replace_all(COPcocName,pattern,"")) %>%
mutate(otherDisagg=ifelse(str_detect(COPdeName,"TX_TB(.)+Specimen_Sent"),"Specimen Sent",otherDisagg)) %>%
mutate(otherDisagg=str_trim(str_replace_all(otherDisagg,"^,( ,)?|(,( )?)+$|,( ,)+|\\(((,)?( )?)\\)",""))) %>%
mutate(otherDisagg=ifelse(str_detect(dataelement, "TX_TB(.)+PositiveScreen")
,str_replace(otherDisagg,"Negative","")
,otherDisagg)) %>%
###Fix otherDisaggs where necessary
mutate(otherDisagg=case_when(str_detect(COPdeName,"TB_PREV") ~ str_replace(otherDisagg,"Alternative Regimen","Alternative TPT Regimen")
####GEND_GBV(.)*PEP
,str_detect(COPdeName,"GEND_GBV(.)+PEP") ~ "PEP"
####TX_RET
,str_detect(COPdeName,"TX_RET(.)+") ~ ifelse(str_detect(COPdeName,"24mo|36mo"),str_extract(dataelement,"24mo|36mo"),"12mo")
####VMMC_CIRC
,str_detect(COPdeName,"VMMC_CIRC(.)+TechFollowUp") ~ "Followed up within 14 days"
,TRUE ~ otherDisagg)) %>%
##IMPATT
mutate(IMPATT = pdLvl=="pd_IMPT_P") %>%
mutate(COPidName=paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|"))
return(ds)
}
generateCodeListT <- function(){
##Define Datasets, Periods, and Levels for which to pull dataElement Code Lists
dataset = c(
#2019 Targets
#(Facility,Community,PSNU)
"eyI0UOWJnDk",
"l796jk9SW7q",
"msJImKkTJkV",
#IMPATT
"pTuDWXzkAkJ",
#2018 Targets
#(Facility, Community)
"AitXBHsC7RA",
"BuRoS9i851o",
#2017Q4
#(Facility,Community)
"uTvHPA1zqzi",
"O3VMNi8EZSV"
)
period = c(rep("19_T", 3), "IMPT", rep(c("18_T", "17_4"), each = 2))
level = c("F", "C", "P", "P", rep(c("F", "C"), 2))
tech_areas <-
c(
"TX_RET",
"TX_NEW",
"TX_CURR",
"TX_PVLS",
"PMTCT_STAT",
"PMTCT_ART",
"PMTCT_EID",
"TB_STAT",
"TB_ART",
"TB_PREV",
"TX_TB",
"HTS_TST",
"VMMC_CIRC",
"HTS_SELF",
"OVC_SERV",
"OVC_HIVSTAT",
"KP_PREV",
"PP_PREV",
"KP_MAT",
"GEND_GBV",
"GEND_GBV_PEP",
"PrEP_NEW",
"IMPATT_PLHIV"
)
COPdataElements<-NULL
for (i in 1:length(dataset)) {
COPdataElements=bind_rows(COPdataElements,getCOPDataElements(dataset[i],period[i],level[i]))
}
COP18deMapT <- COPdataElements %>%
unique %>% filter( indicator %in% tech_areas) %>%
transformDEs %>%
select(
COPidName,
indicator,
numeratorDenom,
supportType,
Modality,
KeyPop,
KnownNewStatus,
NewExistingART,
Indication,
TBStatus,
pregBF,
VMMCTechnique,
Age,
AggregatedAge,
AggregatedAgeFlag,
Sex,
HIVStatus,
otherDisagg,
IMPATT,
pdLvl,
COPuid
) %>%
spread(pdLvl, COPuid) %>%
mutate(
pd_2017 = case_when((is.na(pd_17_4_F) &
!is.na(pd_17_4_C)) ~ pd_17_4_C,
(is.na(pd_17_4_F) &
!is.na(pd_IMPT_P)) ~ pd_IMPT_P,
TRUE ~ pd_17_4_F
),
pd_2018 = case_when((is.na(pd_18_T_F) &
!is.na(pd_18_T_C)) ~ pd_18_T_C,
(is.na(pd_18_T_F) &
!is.na(pd_IMPT_P)) ~ pd_IMPT_P,
TRUE ~ pd_18_T_F
),
pd_2019_S = case_when(is.na(pd_19_T_F) ~ pd_19_T_C,
TRUE ~ pd_19_T_F),
pd_2019_P = case_when((is.na(pd_19_T_P) &
!is.na(pd_IMPT_P)) ~ pd_IMPT_P,
TRUE ~ pd_19_T_P)
) %>%
select(
-pd_17_4_C,
-pd_17_4_F,
-pd_18_T_C,
-pd_18_T_F,
-pd_19_T_C,
-pd_19_T_F,
-pd_19_T_P,
-pd_IMPT_P
) %>%
gather(Period, pd_2017_2018_S, pd_2017, pd_2018) %>%
mutate(FiscalYear = as.numeric(str_extract(Period, "\\d{4}"))) %>%
select(-Period) %>%
filter(!(is.na(pd_2019_S) &
is.na(pd_2019_P) & is.na(pd_2017_2018_S))) %>%
filter(!(IMPATT == TRUE & FiscalYear == 2017))
return(COP18deMapT)
}
mapDataPackCodes <- function(COP18deMapT) {
dp_codes_file<-"data-raw/DataPackCodeListKeysMatched.csv"
blankToNA<-function (x) {ifelse(x=="",NA,x)}
DataPackCodes <-
read.csv(dp_codes_file,
stringsAsFactors = FALSE,
header = TRUE) %>%
unique %>%
mutate(supportType = case_when(IMPATT == FALSE ~ "DSD", TRUE ~ "")) %>%
mutate(
DataPackCode = blankToNA(DataPackCode),
DataPackFilename = blankToNA(DataPackFilename),
DataPackTabName = blankToNA(DataPackTabName)
) %>%
bind_rows(mutate(filter(., IMPATT == FALSE), supportType = "TA"), .) %>%
mutate(
DataPackCode = case_when(
(!is.na(DataPackCode) & DataPackCode != "plhiv_fy19") ~ paste(DataPackCode, tolower(supportType), sep = "_"),
TRUE ~ DataPackCode)
) %>%
#Re-create COPidName using DSD/TA
mutate(
COPidName = paste(
indicator,
numeratorDenom,
supportType,
Modality,
KeyPop,
KnownNewStatus,
NewExistingART,
Indication,
TBStatus,
pregBF,
VMMCTechnique,
Age,
AggregatedAge,
AggregatedAgeFlag,
Sex,
HIVStatus,
otherDisagg,
sep = "|"
)
) %>%
#Select only necessary columns
select(DataPackCode,DataPackFilename,DataPackTabName,COPidName)
#Pull in Data Pack Codes
COP18deMapT <- COP18deMapT %>%
dplyr::full_join(DataPackCodes,by=c("COPidName"))
return(COP18deMapT)
}
generateCOP18deMap<-function(COP18deMapT) {
FY19deMap <- COP18deMapT %>%
mutate(matchCode = COPidName) %>%
select(matchCode,pd_2019_P,pd_2019_S) %>%
filter(!is.na(pd_2019_P)) %>%
unique()
rCOP18deMap <- COP18deMapT %>%
select(-pd_2019_S,-pd_2019_P) %>%
filter(!is.na(pd_2017_2018_S)) %>%
unique() %>%
mutate(matchCode=COPidName) %>%
#1) Many to One Combinations#
##TB_STAT (KnownNewStatus+HIVStatus+Sex+AgeAggregated -> Sex+AgeAggregated)
mutate(matchCode=case_when(indicator=="TB_STAT" & KnownNewStatus!="" & HIVStatus!="" ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,"",NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,"",otherDisagg,sep="|"),TRUE ~ matchCode)) %>%
##PMTCT_EID (Age+HIVStatus -> Age)
mutate(matchCode=case_when(indicator=="PMTCT_EID" & HIVStatus!="" ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,"",otherDisagg,sep="|"),TRUE ~ matchCode)) %>%
##OVC_HIVSTAT (HIVStatus+otherDisagg)
mutate(matchCode=case_when(indicator=="OVC_HIVSTAT" & HIVStatus!="" & otherDisagg %in% c("","Undisclosed to IP") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,"","",sep="|"),TRUE ~ matchCode))
##GEND_GBV (ViolenceServiceType/Age/Sex -> ViolenceServiceType)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="GEND_GBV" & FiscalYear==2017 & Age!="" & Sex!="" & otherDisagg %in% c('Physical and/or Emotional Violence','Sexual Violence (Post-Rape Care)')) %>%
mutate(matchCode=paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,"","",AggregatedAgeFlag,"",HIVStatus,otherDisagg,sep="|")) %>%
bind_rows(rCOP18deMap,.) %>%
#2) More Complicated
##TB_PREV
###(6-12 Month IPT|Continuous IPT --> IPT) & (NewExistingART="" --> NewExistingART="New")
mutate(matchCode=case_when(indicator=="TB_PREV" & otherDisagg %in% c("6-12 Month IPT","Continuous IPT") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,"New",Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,"IPT",sep="|")
,indicator=="TB_PREV" & otherDisagg %in% c("Alternative TPT Regimen") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,"New",Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|")
,TRUE ~ matchCode))
###(ADD ROWS for splitting out NewExistingART to include "Already")
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="TB_PREV" & otherDisagg !="") %>%
mutate(matchCode=str_replace(matchCode,"\\|New\\|","\\|Already\\|")) %>%
bind_rows(rCOP18deMap,.)
##New Age Bands
ageBands<-data.frame(Age=c(rep("25-49",4),rep("30-49",3))
,finererAge=c("25-29","30-34","35-39","40-49","30-34","35-39","40-49"),stringsAsFactors = FALSE)
rCOP18deMap <- rCOP18deMap %>%
filter(Age %in% c("30-49","25-49") & !indicator %in% c("TX_PVLS","TX_RET","TB_ART") & !str_detect(matchCode,"(\\|){3,}(Physical and\\/or Emotional Violence|Sexual Violence \\(Post-Rape Care\\))") ) %>%
left_join(ageBands,by=c("Age")) %>%
mutate(matchCode=paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,finererAge,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|")) %>%
select(names(rCOP18deMap)) %>%
bind_rows(rCOP18deMap,.) %>%
filter(!(str_detect(matchCode,"25-49|30-49") & !str_detect(matchCode,"TX_PVLS|TX_RET|TB_ART")))
rm(ageBands)
##TX_PVLS|TX_RET|TB_ART
###(ADD ROWS to split <1 & 1-9 Unknown to Male/Female)
rCOP18deMap <- rCOP18deMap %>%
mutate(matchCode=case_when(indicator %in% c("TX_PVLS","TX_RET","TB_ART") & Age %in% c("<1","1-9") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,AggregatedAge,AggregatedAge,"AgeAggregated","Male",HIVStatus,otherDisagg,sep="|")
,TRUE ~ matchCode))
rCOP18deMap <- rCOP18deMap %>%
filter(indicator %in% c("TX_PVLS","TX_RET","TB_ART") & Age %in% c("<1","1-9")) %>%
mutate(matchCode=str_replace(matchCode,"\\|Male\\|","\\|Female\\|")) %>%
bind_rows(rCOP18deMap,.) %>%
###(Convert Age bands from fine to coarse)
mutate(matchCode=case_when(indicator %in% c("TX_PVLS","TX_RET","TB_ART") & Age %in% c("10-14","15-19","20-24","25-49","50+") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,AggregatedAge,AggregatedAge,"AgeAggregated",Sex,HIVStatus,otherDisagg,sep="|")
,TRUE~matchCode))
#3) One to Many combinations
##A) New indicators
###HTS_TST Emergency Ward <- HTS_TST PITC
rCOP18deMap<-rCOP18deMap %>%
filter(indicator=="HTS_TST" & Modality=="OtherPITC") %>%
mutate(matchCode=str_replace(matchCode,"\\|OtherPITC\\|","\\|Emergency Ward\\|")) %>%
bind_rows(rCOP18deMap,.)
###HTS_TST STI Clinic <- HTS_TST PITC
rCOP18deMap<-rCOP18deMap %>%
filter(indicator=="HTS_TST" & str_detect(matchCode,"\\|Emergency Ward\\|")) %>%
mutate(matchCode=str_replace(matchCode,"\\|Emergency Ward\\|","\\|STI Clinic\\|")) %>%
bind_rows(rCOP18deMap,.)
##B) New Disaggs
###TX_TB (D) (Positive,Negative ->Positive-New,Positive-Already,Negative-New,Negative-Already)
rCOP18deMap<-rCOP18deMap %>%
mutate(matchCode=case_when(indicator=="TX_TB" & numeratorDenom=="D" & TBStatus!="" ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,"Already",Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|"),TRUE~matchCode))
rCOP18deMap<-rCOP18deMap %>%
filter(indicator=="TX_TB" & numeratorDenom=="D" & TBStatus!="") %>%
mutate(matchCode=str_replace(matchCode,"\\|Already\\|","\\|New\\|")) %>%
bind_rows(rCOP18deMap,.)
##C) OVC_SERV (10-14 Male,Female -> <1 Unknown, 1-9 Unknown)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="OVC_SERV" & Age=="10-14" & otherDisagg!="") %>%
mutate(matchCode=paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,"1-9",AggregatedAge,AggregatedAgeFlag,"Unknown Sex",HIVStatus,otherDisagg,sep="|")) %>%
bind_rows(rCOP18deMap,.)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="OVC_SERV" & otherDisagg!="" & str_detect(matchCode,"\\|1-9\\|")) %>%
mutate(matchCode=str_replace(matchCode,"\\|1-9\\|","\\|<1\\|")) %>%
bind_rows(rCOP18deMap,.)
#4) DO NOT DISTRIBUTE TO SITE (Below for moving to PSNU only. Need to re-adjust to not persist to Site to force manual redistribution)
##PrEP_NEW (Other Key Populations - not distributed to Site, but moved to PSNU level by following PrEP_NEW N)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="PrEP_NEW" & Sex=="" & Age=="" & KeyPop=="") %>%
mutate(matchCode=paste(indicator,numeratorDenom,supportType,Modality,"Other Key Populations",KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|")) %>%
bind_rows(rCOP18deMap,.)
##HTS_SELF (New indicator with no reliable model)
###KeyPops (Follow HTS_TST KeyPops to get to PSNU)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="HTS_TST" & KeyPop!="" & HIVStatus!="" & Modality=="" & Age=="") %>%
mutate(matchCode=paste("HTS_SELF",numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,"","Directly-Assisted",sep="|")) %>%
bind_rows(rCOP18deMap,.)
rCOP18deMap<- rCOP18deMap %>%
filter(str_detect(matchCode,"HTS_SELF(.)+Directly-Assisted")) %>%
mutate(matchCode=str_replace(matchCode,"Directly-Assisted","Unassisted")) %>%
bind_rows(rCOP18deMap,.)
###Disaggs: Testing Type, Age/Sex, Unassisted by use
HTS_SELF.Disaggs<-COP18deMapT %>%
filter(indicator=="HTS_SELF" & KeyPop=="") %>%
select(COPidName,supportType) %>%
unique() %>%
mutate(matchCode=paste0("HTS_TST|N|",supportType,"||||||||||||||")) %>%
select(-supportType)
rCOP18deMap <- rCOP18deMap %>%
filter(matchCode %in% c("HTS_TST|N|DSD||||||||||||||","HTS_TST|N|TA||||||||||||||")) %>%
left_join(HTS_SELF.Disaggs,by=c("matchCode")) %>%
select(-matchCode) %>%
mutate(matchCode=COPidName.y,
COPidName=COPidName.x) %>%
select(-COPidName.y,-COPidName.x) %>%
select(names(rCOP18deMap)) %>%
bind_rows(rCOP18deMap,.)
rCOP18deMap <- rCOP18deMap %>%
full_join(FY19deMap,by=c("matchCode")) %>%
select(COPidName,matchCode,indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,IMPATT,DataPackCode,DataPackFilename,DataPackTabName,FiscalYear,pd_2017_2018_S,pd_2019_S,pd_2019_P) %>%
arrange(COPidName)
return(rCOP18deMap)
}
jason-p-pickering/data-pack-importer documentation built on Oct. 27, 2019, 9:42 a.m.
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require(dplyr)
require(stringr)
#' @title getCOPDataElements()
#'
#' @description Extracts DATIM dataElement/categoryOptionCombo code list for specified dataset & time period.
#' @param ds DATIM Dataset UID.
#' @param pd Code indicating which time period for which to query code list.
#' @param lvl Organization unit level related to code list in question (P=PSNU, C=Community, F=Facility)
#' @return Returns a dataframe ready for use in preparing source files.
#'
getCOPDataElements <- function(ds,pd,lvl) {
de <- read.csv(url(paste0(getOption("baseurl"),"api/sqlViews/DotdxKrNZxG/data.csv?var=dataSets:",ds)),stringsAsFactors=FALSE,header=TRUE) %>%
mutate(period = pd) %>%
mutate(level = lvl) %>%
mutate(pdLvl = paste("pd",period,level,sep="_",collapse=NULL)) %>%
mutate(indicator = str_trim(str_extract(str_replace_all(dataelement,"(?<=IMPATT)\\.","_"),"^\\w+\\s")))
return(de)
}
transformDEs <- function(de){
ds <- de %>%
#Prepare cross-period codes for each MER indicator
mutate(COPdeName = str_replace_all(str_replace_all(dataelement,"(\\) TARGET)|( v\\d)|\\:(.)*| T_PSNU|\\)|,|\\(","")," |/","_")) %>%
mutate(COPcocName = as.character(categoryoptioncombo)) %>%
mutate(COPuid = paste(dataelementuid,categoryoptioncombouid,sep=".",collapse=NULL)) %>%
#Break out dataElementName for helpful referencing
mutate(indicator = str_trim(str_extract(str_replace_all(dataelement,"IMPATT\\.",""),"^\\w+\\s"))) %>%
mutate(numeratorDenom = ifelse(str_detect(code,"_[ND]_"),
str_replace_all(str_extract(code,"_[ND]_"),"_",""),
"")) %>%
mutate(supportType = ifelse(str_detect(dataelement,"(DSD|TA)(?=\\W)"),
str_replace_all(str_extract(dataelement,"(DSD|TA)(?=\\W)"),"_",""),
"")) %>%
#Break out categoryOptionCombo for helpful referencing
##Modality
mutate(Modality=ifelse(str_detect(COPdeName,"HTS_TST(.)+(Emergency_Ward_|HomeMod_|Index_|IndexMod_|Inpat_|Malnutrition_|MobileMod_|OtherMod_|OtherPITC_|Pediatric_|PMTCT_ANC_|STI_Clinic_|TBClinic_|VCT_|VCTMod_|VMMC_)")
,str_extract(dataelement,"Emergency Ward|HomeMod|IndexMod|Index|Inpat|Malnutrition|MobileMod|OtherMod|OtherPITC|Pediatric|PMTCT ANC|STI Clinic|TBClinic|VCTMod|VCT|VMMC")
,"")) %>%
##Age
mutate(Age=case_when(str_detect(COPdeName,"Age") ~ str_trim(str_extract(COPcocName,"(?<!D)(<|<=)?( )?\\d{1,2}( months)?(( )?-( )?\\d{1,2}( months| years)?|\\+)?|Unknown Age"))
,str_detect(dataelement,"HTS_TST(.)+(Malnutrition|Pediatric)") ~ "<5"
,TRUE~"")) %>%
##AggregatedAge
mutate(AggregatedAge=Age)
word=c("< 2 months","<= 2 months","2 - 12 months","<1","<5","1-9","2 months - 9 years","<10","10-14","<15","15-17","15-19","18-24","20-24","25-29","15-29","30-34","35-39","40-49","30-49","25-49","15\\+","25\\+","30\\+","50\\+","Unknown Age")
tran=c(rep("<15",10),rep("15+",15),"Unknown Age")
dict=data.frame(word,tran,stringsAsFactors = FALSE)
for (k in 1:length(dict$word)){ds$AggregatedAge=str_replace_all(ds$AggregatedAge,paste0("^",dict$word[k],"$"),dict$tran[k])}
##Aggregated Age Flag (to distinguish otherwise identical indicators)
ds <- ds %>% mutate(AggregatedAgeFlag=ifelse(str_detect(dataelement,"Age Aggregated|(PLHIV|HIV_PREV)(.)+Age")
,"AgeAggregated"
,"")) %>%
##Sex
mutate(Sex=ifelse(str_detect(COPdeName,"Sex|HTS_TST(.)+VCT_Age_Result")
|str_detect(COPcocName,"Female PWID|Male PWID|MSM|FSW")
,str_extract(COPcocName,"Male|Female|Unknown Sex|MSM|FSW")
,""))
dict=data.frame(word=c("MSM","FSW"),tran=c("Male","Female"),stringsAsFactors = FALSE)
for (k in 1:length(dict$word)){ds$Sex<-str_replace_all(ds$Sex,dict$word[k],dict$tran[k])}
rm(dict)
ds <- ds %>%
mutate(Sex=case_when(str_detect(dataelement,"HTS_TST|OVC_SERV|PMTCT_EID|TB_ART|TX_(CURR|NEW|PVLS|RET)") & str_detect(Age,"(<1|1-9|<5)$") ~ "Unknown Sex",TRUE~Sex)) %>%
mutate(Sex=case_when(str_detect(dataelement,"HTS_TST(.)+VMMC|VMMC_CIRC") ~ "Male"
,str_detect(dataelement,"HTS_TST(.)+PMTCT|PMTCT_ART|PMTCT_STAT") ~ "Female"
,TRUE ~ Sex)) %>%
##HIVStatus
# Convert to "HIV Positive", "HIV Negative", "HIV Unknown"
mutate(HIVStatus=ifelse(str_detect(COPdeName,"_Result|_HIVStatus|_KnownNewResult|_KnownNewPosNeg|OVC_HIVSTAT_(.)+_ReportedStatus")
| (str_detect(COPdeName,"KP_PREV_(N|D)_(DSD|TA)_KeyPop_Status|PP_PREV_(N|D)_(DSD|TA)_Status") & str_detect(COPcocName,"Positive|Negative"))
,str_extract(COPcocName,"Positive|Negative|Unknown(?=($|,))|Undisclosed")
,"")) %>%
mutate(HIVStatus=str_replace(HIVStatus,"Undisclosed","Unknown")) %>%
mutate(HIVStatus=case_when(str_detect(COPdeName,"^(IMPATT.PLHIV|PMTCT_ART|TB_ART|TB_PREV|TX_CURR|TX_NEW|TX_PVLS|TX_RET|TX_TB)|OVC_HIVSTAT_(.)+_StatusPosART") & !(HIVStatus %in% ("Positive")) ~ "Positive"
,str_detect(COPdeName,"OVC_HIVSTAT(.)+StatusNotRep") & !(HIVStatus %in% ("Unknown")) ~ "Unknown"
,str_detect(COPdeName,"HTS_TST(.)+Positive") ~ "Positive"
,TRUE ~ HIVStatus)) %>%
##KeyPop
mutate(KeyPop=ifelse(str_detect(COPdeName,"_KeyPop")
,str_extract(COPcocName,"FSW|MSM(( not)? SW)?|TG(( not)? SW)?|PWID|People in prisons and other enclosed settings|Other Key Populations")
,"")) %>%
##KnownNewStatus
mutate(KnownNewStatus=ifelse(str_detect(COPcocName,"Known at Entry|Newly Tested or Testing Referred|Newly Identified|Declined Testing Or Testing Referral")
,str_extract(COPcocName,"Known|New|Declined")
,"")) %>%
##NewExistingART
mutate(NewExistingART=ifelse(str_detect(COPdeName,regex("NewExistingArt",ignore_case=T))
,str_extract(COPcocName,"New|Already")
,"")) %>%
##Indication
mutate(Indication=ifelse(str_detect(COPdeName,"TX_PVLS(.)+(Indication|RoutineTargeted)")
,str_extract(COPcocName,"Routine|Targeted|Undocumented Test Indication")
,"")) %>%
##TBStatus
mutate(TBStatus=ifelse(str_detect(COPdeName,"TX_NEW(.)+TB_Diagnosis|TB_STAT|TB_ART|TX_TB_(N|D(.)+(TBScreen|PositiveScreen))")
,ifelse(str_detect(COPdeName,"TX_TB_D")
,paste0("TB ",str_extract(COPcocName,"(?<=(TB Screen - |^))(Posi|Nega)tive"))
,"TB Positive")
,"")) %>%
##pregBF
mutate(pregBF=ifelse(str_detect(dataelement,"PMTCT_(ART|STAT)|TX_(NEW|RET|PVLS)(.)+PregnantOrBreastfeeding")
,ifelse(str_detect(dataelement,"PMTCT_(ART|STAT)")
,"Pregnant"
,str_extract(COPcocName,"Pregnant|Breastfeeding"))
,"")) %>%
##VMMCTechnique
mutate(VMMCTechnique=ifelse(str_detect(dataelement,"VMMC_CIRC(.)+Tech")
,str_extract(COPcocName,"Device based|Surgical Technique")
,""))
##otherDisagg
pattern=paste(ifelse(ds$KeyPop=="","0000",ds$KeyPop)
,ifelse(ds$Sex=="","0000",ds$Sex)
,ifelse(ds$Age=="","0000",paste0("\\Q",ds$Age,"\\E"))
,"TB Screen - (Posi|Nega)tive"
,ifelse(ds$HIVStatus=="","0000",ds$HIVStatus)
,"Declined Testing Or Testing Referral","Newly Tested or Testing Referred","Newly Identified","Known at Entry","Life-long ART"
,ifelse(ds$KnownNewStatus=="","0000",ds$KnownNewStatus)
,ifelse(ds$NewExistingART=="","0000",ds$NewExistingART)
,ifelse(ds$Indication=="","0000",ds$Indication)
,ifelse(ds$pregBF=="","0000",ds$pregBF)
,ifelse(ds$VMMCTechnique=="","0000",ds$VMMCTechnique)
,"default"
,sep="|")
ds <- ds %>%
mutate(otherDisagg=str_replace_all(COPcocName,pattern,"")) %>%
mutate(otherDisagg=ifelse(str_detect(COPdeName,"TX_TB(.)+Specimen_Sent"),"Specimen Sent",otherDisagg)) %>%
mutate(otherDisagg=str_trim(str_replace_all(otherDisagg,"^,( ,)?|(,( )?)+$|,( ,)+|\\(((,)?( )?)\\)",""))) %>%
mutate(otherDisagg=ifelse(str_detect(dataelement, "TX_TB(.)+PositiveScreen")
,str_replace(otherDisagg,"Negative","")
,otherDisagg)) %>%
###Fix otherDisaggs where necessary
mutate(otherDisagg=case_when(str_detect(COPdeName,"TB_PREV") ~ str_replace(otherDisagg,"Alternative Regimen","Alternative TPT Regimen")
####GEND_GBV(.)*PEP
,str_detect(COPdeName,"GEND_GBV(.)+PEP") ~ "PEP"
####TX_RET
,str_detect(COPdeName,"TX_RET(.)+") ~ ifelse(str_detect(COPdeName,"24mo|36mo"),str_extract(dataelement,"24mo|36mo"),"12mo")
####VMMC_CIRC
,str_detect(COPdeName,"VMMC_CIRC(.)+TechFollowUp") ~ "Followed up within 14 days"
,TRUE ~ otherDisagg)) %>%
##IMPATT
mutate(IMPATT = pdLvl=="pd_IMPT_P") %>%
mutate(COPidName=paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|"))
return(ds)
}
generateCodeListT <- function(){
##Define Datasets, Periods, and Levels for which to pull dataElement Code Lists
dataset = c(
#2019 Targets
#(Facility,Community,PSNU)
"eyI0UOWJnDk",
"l796jk9SW7q",
"msJImKkTJkV",
#IMPATT
"pTuDWXzkAkJ",
#2018 Targets
#(Facility, Community)
"AitXBHsC7RA",
"BuRoS9i851o",
#2017Q4
#(Facility,Community)
"uTvHPA1zqzi",
"O3VMNi8EZSV"
)
period = c(rep("19_T", 3), "IMPT", rep(c("18_T", "17_4"), each = 2))
level = c("F", "C", "P", "P", rep(c("F", "C"), 2))
tech_areas <-
c(
"TX_RET",
"TX_NEW",
"TX_CURR",
"TX_PVLS",
"PMTCT_STAT",
"PMTCT_ART",
"PMTCT_EID",
"TB_STAT",
"TB_ART",
"TB_PREV",
"TX_TB",
"HTS_TST",
"VMMC_CIRC",
"HTS_SELF",
"OVC_SERV",
"OVC_HIVSTAT",
"KP_PREV",
"PP_PREV",
"KP_MAT",
"GEND_GBV",
"GEND_GBV_PEP",
"PrEP_NEW",
"IMPATT_PLHIV"
)
COPdataElements<-NULL
for (i in 1:length(dataset)) {
COPdataElements=bind_rows(COPdataElements,getCOPDataElements(dataset[i],period[i],level[i]))
}
COP18deMapT <- COPdataElements %>%
unique %>% filter( indicator %in% tech_areas) %>%
transformDEs %>%
select(
COPidName,
indicator,
numeratorDenom,
supportType,
Modality,
KeyPop,
KnownNewStatus,
NewExistingART,
Indication,
TBStatus,
pregBF,
VMMCTechnique,
Age,
AggregatedAge,
AggregatedAgeFlag,
Sex,
HIVStatus,
otherDisagg,
IMPATT,
pdLvl,
COPuid
) %>%
spread(pdLvl, COPuid) %>%
mutate(
pd_2017 = case_when((is.na(pd_17_4_F) &
!is.na(pd_17_4_C)) ~ pd_17_4_C,
(is.na(pd_17_4_F) &
!is.na(pd_IMPT_P)) ~ pd_IMPT_P,
TRUE ~ pd_17_4_F
),
pd_2018 = case_when((is.na(pd_18_T_F) &
!is.na(pd_18_T_C)) ~ pd_18_T_C,
(is.na(pd_18_T_F) &
!is.na(pd_IMPT_P)) ~ pd_IMPT_P,
TRUE ~ pd_18_T_F
),
pd_2019_S = case_when(is.na(pd_19_T_F) ~ pd_19_T_C,
TRUE ~ pd_19_T_F),
pd_2019_P = case_when((is.na(pd_19_T_P) &
!is.na(pd_IMPT_P)) ~ pd_IMPT_P,
TRUE ~ pd_19_T_P)
) %>%
select(
-pd_17_4_C,
-pd_17_4_F,
-pd_18_T_C,
-pd_18_T_F,
-pd_19_T_C,
-pd_19_T_F,
-pd_19_T_P,
-pd_IMPT_P
) %>%
gather(Period, pd_2017_2018_S, pd_2017, pd_2018) %>%
mutate(FiscalYear = as.numeric(str_extract(Period, "\\d{4}"))) %>%
select(-Period) %>%
filter(!(is.na(pd_2019_S) &
is.na(pd_2019_P) & is.na(pd_2017_2018_S))) %>%
filter(!(IMPATT == TRUE & FiscalYear == 2017))
return(COP18deMapT)
}
mapDataPackCodes <- function(COP18deMapT) {
dp_codes_file<-"data-raw/DataPackCodeListKeysMatched.csv"
blankToNA<-function (x) {ifelse(x=="",NA,x)}
DataPackCodes <-
read.csv(dp_codes_file,
stringsAsFactors = FALSE,
header = TRUE) %>%
unique %>%
mutate(supportType = case_when(IMPATT == FALSE ~ "DSD", TRUE ~ "")) %>%
mutate(
DataPackCode = blankToNA(DataPackCode),
DataPackFilename = blankToNA(DataPackFilename),
DataPackTabName = blankToNA(DataPackTabName)
) %>%
bind_rows(mutate(filter(., IMPATT == FALSE), supportType = "TA"), .) %>%
mutate(
DataPackCode = case_when(
(!is.na(DataPackCode) & DataPackCode != "plhiv_fy19") ~ paste(DataPackCode, tolower(supportType), sep = "_"),
TRUE ~ DataPackCode)
) %>%
#Re-create COPidName using DSD/TA
mutate(
COPidName = paste(
indicator,
numeratorDenom,
supportType,
Modality,
KeyPop,
KnownNewStatus,
NewExistingART,
Indication,
TBStatus,
pregBF,
VMMCTechnique,
Age,
AggregatedAge,
AggregatedAgeFlag,
Sex,
HIVStatus,
otherDisagg,
sep = "|"
)
) %>%
#Select only necessary columns
select(DataPackCode,DataPackFilename,DataPackTabName,COPidName)
#Pull in Data Pack Codes
COP18deMapT <- COP18deMapT %>%
dplyr::full_join(DataPackCodes,by=c("COPidName"))
return(COP18deMapT)
}
generateCOP18deMap<-function(COP18deMapT) {
FY19deMap <- COP18deMapT %>%
mutate(matchCode = COPidName) %>%
select(matchCode,pd_2019_P,pd_2019_S) %>%
filter(!is.na(pd_2019_P)) %>%
unique()
rCOP18deMap <- COP18deMapT %>%
select(-pd_2019_S,-pd_2019_P) %>%
filter(!is.na(pd_2017_2018_S)) %>%
unique() %>%
mutate(matchCode=COPidName) %>%
#1) Many to One Combinations#
##TB_STAT (KnownNewStatus+HIVStatus+Sex+AgeAggregated -> Sex+AgeAggregated)
mutate(matchCode=case_when(indicator=="TB_STAT" & KnownNewStatus!="" & HIVStatus!="" ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,"",NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,"",otherDisagg,sep="|"),TRUE ~ matchCode)) %>%
##PMTCT_EID (Age+HIVStatus -> Age)
mutate(matchCode=case_when(indicator=="PMTCT_EID" & HIVStatus!="" ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,"",otherDisagg,sep="|"),TRUE ~ matchCode)) %>%
##OVC_HIVSTAT (HIVStatus+otherDisagg)
mutate(matchCode=case_when(indicator=="OVC_HIVSTAT" & HIVStatus!="" & otherDisagg %in% c("","Undisclosed to IP") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,"","",sep="|"),TRUE ~ matchCode))
##GEND_GBV (ViolenceServiceType/Age/Sex -> ViolenceServiceType)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="GEND_GBV" & FiscalYear==2017 & Age!="" & Sex!="" & otherDisagg %in% c('Physical and/or Emotional Violence','Sexual Violence (Post-Rape Care)')) %>%
mutate(matchCode=paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,"","",AggregatedAgeFlag,"",HIVStatus,otherDisagg,sep="|")) %>%
bind_rows(rCOP18deMap,.) %>%
#2) More Complicated
##TB_PREV
###(6-12 Month IPT|Continuous IPT --> IPT) & (NewExistingART="" --> NewExistingART="New")
mutate(matchCode=case_when(indicator=="TB_PREV" & otherDisagg %in% c("6-12 Month IPT","Continuous IPT") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,"New",Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,"IPT",sep="|")
,indicator=="TB_PREV" & otherDisagg %in% c("Alternative TPT Regimen") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,"New",Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|")
,TRUE ~ matchCode))
###(ADD ROWS for splitting out NewExistingART to include "Already")
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="TB_PREV" & otherDisagg !="") %>%
mutate(matchCode=str_replace(matchCode,"\\|New\\|","\\|Already\\|")) %>%
bind_rows(rCOP18deMap,.)
##New Age Bands
ageBands<-data.frame(Age=c(rep("25-49",4),rep("30-49",3))
,finererAge=c("25-29","30-34","35-39","40-49","30-34","35-39","40-49"),stringsAsFactors = FALSE)
rCOP18deMap <- rCOP18deMap %>%
filter(Age %in% c("30-49","25-49") & !indicator %in% c("TX_PVLS","TX_RET","TB_ART") & !str_detect(matchCode,"(\\|){3,}(Physical and\\/or Emotional Violence|Sexual Violence \\(Post-Rape Care\\))") ) %>%
left_join(ageBands,by=c("Age")) %>%
mutate(matchCode=paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,finererAge,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|")) %>%
select(names(rCOP18deMap)) %>%
bind_rows(rCOP18deMap,.) %>%
filter(!(str_detect(matchCode,"25-49|30-49") & !str_detect(matchCode,"TX_PVLS|TX_RET|TB_ART")))
rm(ageBands)
##TX_PVLS|TX_RET|TB_ART
###(ADD ROWS to split <1 & 1-9 Unknown to Male/Female)
rCOP18deMap <- rCOP18deMap %>%
mutate(matchCode=case_when(indicator %in% c("TX_PVLS","TX_RET","TB_ART") & Age %in% c("<1","1-9") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,AggregatedAge,AggregatedAge,"AgeAggregated","Male",HIVStatus,otherDisagg,sep="|")
,TRUE ~ matchCode))
rCOP18deMap <- rCOP18deMap %>%
filter(indicator %in% c("TX_PVLS","TX_RET","TB_ART") & Age %in% c("<1","1-9")) %>%
mutate(matchCode=str_replace(matchCode,"\\|Male\\|","\\|Female\\|")) %>%
bind_rows(rCOP18deMap,.) %>%
###(Convert Age bands from fine to coarse)
mutate(matchCode=case_when(indicator %in% c("TX_PVLS","TX_RET","TB_ART") & Age %in% c("10-14","15-19","20-24","25-49","50+") ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,AggregatedAge,AggregatedAge,"AgeAggregated",Sex,HIVStatus,otherDisagg,sep="|")
,TRUE~matchCode))
#3) One to Many combinations
##A) New indicators
###HTS_TST Emergency Ward <- HTS_TST PITC
rCOP18deMap<-rCOP18deMap %>%
filter(indicator=="HTS_TST" & Modality=="OtherPITC") %>%
mutate(matchCode=str_replace(matchCode,"\\|OtherPITC\\|","\\|Emergency Ward\\|")) %>%
bind_rows(rCOP18deMap,.)
###HTS_TST STI Clinic <- HTS_TST PITC
rCOP18deMap<-rCOP18deMap %>%
filter(indicator=="HTS_TST" & str_detect(matchCode,"\\|Emergency Ward\\|")) %>%
mutate(matchCode=str_replace(matchCode,"\\|Emergency Ward\\|","\\|STI Clinic\\|")) %>%
bind_rows(rCOP18deMap,.)
##B) New Disaggs
###TX_TB (D) (Positive,Negative ->Positive-New,Positive-Already,Negative-New,Negative-Already)
rCOP18deMap<-rCOP18deMap %>%
mutate(matchCode=case_when(indicator=="TX_TB" & numeratorDenom=="D" & TBStatus!="" ~ paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,"Already",Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|"),TRUE~matchCode))
rCOP18deMap<-rCOP18deMap %>%
filter(indicator=="TX_TB" & numeratorDenom=="D" & TBStatus!="") %>%
mutate(matchCode=str_replace(matchCode,"\\|Already\\|","\\|New\\|")) %>%
bind_rows(rCOP18deMap,.)
##C) OVC_SERV (10-14 Male,Female -> <1 Unknown, 1-9 Unknown)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="OVC_SERV" & Age=="10-14" & otherDisagg!="") %>%
mutate(matchCode=paste(indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,"1-9",AggregatedAge,AggregatedAgeFlag,"Unknown Sex",HIVStatus,otherDisagg,sep="|")) %>%
bind_rows(rCOP18deMap,.)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="OVC_SERV" & otherDisagg!="" & str_detect(matchCode,"\\|1-9\\|")) %>%
mutate(matchCode=str_replace(matchCode,"\\|1-9\\|","\\|<1\\|")) %>%
bind_rows(rCOP18deMap,.)
#4) DO NOT DISTRIBUTE TO SITE (Below for moving to PSNU only. Need to re-adjust to not persist to Site to force manual redistribution)
##PrEP_NEW (Other Key Populations - not distributed to Site, but moved to PSNU level by following PrEP_NEW N)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="PrEP_NEW" & Sex=="" & Age=="" & KeyPop=="") %>%
mutate(matchCode=paste(indicator,numeratorDenom,supportType,Modality,"Other Key Populations",KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,sep="|")) %>%
bind_rows(rCOP18deMap,.)
##HTS_SELF (New indicator with no reliable model)
###KeyPops (Follow HTS_TST KeyPops to get to PSNU)
rCOP18deMap <- rCOP18deMap %>%
filter(indicator=="HTS_TST" & KeyPop!="" & HIVStatus!="" & Modality=="" & Age=="") %>%
mutate(matchCode=paste("HTS_SELF",numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,"","Directly-Assisted",sep="|")) %>%
bind_rows(rCOP18deMap,.)
rCOP18deMap<- rCOP18deMap %>%
filter(str_detect(matchCode,"HTS_SELF(.)+Directly-Assisted")) %>%
mutate(matchCode=str_replace(matchCode,"Directly-Assisted","Unassisted")) %>%
bind_rows(rCOP18deMap,.)
###Disaggs: Testing Type, Age/Sex, Unassisted by use
HTS_SELF.Disaggs<-COP18deMapT %>%
filter(indicator=="HTS_SELF" & KeyPop=="") %>%
select(COPidName,supportType) %>%
unique() %>%
mutate(matchCode=paste0("HTS_TST|N|",supportType,"||||||||||||||")) %>%
select(-supportType)
rCOP18deMap <- rCOP18deMap %>%
filter(matchCode %in% c("HTS_TST|N|DSD||||||||||||||","HTS_TST|N|TA||||||||||||||")) %>%
left_join(HTS_SELF.Disaggs,by=c("matchCode")) %>%
select(-matchCode) %>%
mutate(matchCode=COPidName.y,
COPidName=COPidName.x) %>%
select(-COPidName.y,-COPidName.x) %>%
select(names(rCOP18deMap)) %>%
bind_rows(rCOP18deMap,.)
rCOP18deMap <- rCOP18deMap %>%
full_join(FY19deMap,by=c("matchCode")) %>%
select(COPidName,matchCode,indicator,numeratorDenom,supportType,Modality,KeyPop,KnownNewStatus,NewExistingART,Indication,TBStatus,pregBF,VMMCTechnique,Age,AggregatedAge,AggregatedAgeFlag,Sex,HIVStatus,otherDisagg,IMPATT,DataPackCode,DataPackFilename,DataPackTabName,FiscalYear,pd_2017_2018_S,pd_2019_S,pd_2019_P) %>%
arrange(COPidName)
return(rCOP18deMap)
}
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