Nothing
R/CH_FEVR_C_FEV.R
In surveyPrev: Mapping the Prevalence of Binary Indicators using Survey Data in Small Areas
Defines functions
CH_FEVR_C_FEV
Documented in
CH_FEVR_C_FEV
##'CH_FEVR_C_FEV
#' @param KRdata data.frame from surveyPrev::getDHSdata
#'
#' @return A partially processed data.frame that will be used in surveyPrev::getDHSindicator. The whole function can be used as a parameter in surveyPrev::getDHSindicator
#'
#' @author Miaolei Bao, Yunhan Wu, Qianyu Dong
#' @examples
#' \dontrun{
#' dhsData <- getDHSdata(country = "Zambia", indicator = "CH_FEVR_C_FEV", year = 2018)
#' }
#'
#' @export
CH_FEVR_C_FEV <- function(KRdata){
# /*****************************************************************************************************
# Program: CH_ARI_FV.R
# Purpose: Code ARI and fever variables.
# Data inputs: KR dataset
# Data outputs: coded variables
# Author: Shireen Assaf
# Date last modified: July 29, 2022 by Shireen Assaf
# Notes: Check notes for ARI/fever care and treatment variables which are country specific.
# *****************************************************************************************************/
#
# /*----------------------------------------------------------------------------
# Variables created in this file:
# ch_ari "ARI symptoms in the 2 weeks before the survey"
# ch_ari_care "Advice or treatment sought for ARI symptoms"
# ch_ari_care_day "Advice or treatment sought for ARI symptoms on the same or next day"
#
# ch_ari_govh "ARI treatment sought from government hospital among children with ARI"
# ch_ari_govh_trt "ARI treatment sought from government hospital among children with ARI that sought treatment"
# ch_ari_govcent "ARI treatment sought from government health center among children with ARI"
# ch_ari_govcent_trt "ARI treatment sought from government health center among children with ARI that sought treatment"
# ch_ari_pclinc "ARI treatment sought from private hospital/clinic among children with ARI"
# ch_ari_pclinc_trt "ARI treatment sought from private hospital/clinic among children with ARI that sought treatment"
# ch_ari_pdoc "ARI treatment sought from private doctor among children with ARI"
# ch_ari_pdoc_trt "ARI treatment sought from private doctor among children with ARI that sought treatment"
# ch_ari_pharm "ARI treatment sought from pharmacy among children with ARI"
# ch_ari_pharm_trt "ARI treatment sought from pharmacy among children with ARI that sought treatment"
#
# ch_fever "Fever symptoms in the 2 weeks before the survey"
# ch_fev_care "Advice or treatment sought for fever symptoms"
# ch_fev_care_day "Advice or treatment sought for ARI symptoms on the same or next day"
# ch_fev_antib "Antibiotics taken for fever symptoms"
# ----------------------------------------------------------------------------*/
# weight variable
KRdata <- KRdata %>%
mutate(wt = v005/1000000)
# ** ARI indicators ***
# age of child. If b19 is not available in the data use v008 - b3
if ("TRUE" %in% (!("b19" %in% names(KRdata))))
KRdata [[paste("b19")]] <- NA
if ("TRUE" %in% all(is.na(KRdata$b19)))
{ b19_included <- 0} else { b19_included <- 1}
if (b19_included==1) {
KRdata <- KRdata %>%
mutate(age = b19)
} else {
KRdata <- KRdata %>%
mutate(age = v008 - b3)
}
# //ARI symptoms
# ARI definition differs by survey according to whether h31c is included or not
if ("TRUE" %in% (!("h31c" %in% names(KRdata))))
KRdata [[paste("h31c")]] <- NA
if ("TRUE" %in% all(is.na(KRdata$h31c)))
{ h31c_included <- 0} else { h31c_included <- 1}
if (h31c_included==1) {
KRdata <- KRdata %>%
mutate(ch_ari =
case_when(
h31b==1 & (h31c==1 | h31c==3) & b5==1 ~ 1,
b5==1 ~ 0 )) %>%
set_value_labels(ch_ari = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari = "ARI symptoms in the 2 weeks before the survey")
} else {
KRdata <- KRdata %>%
mutate(ch_ari =
case_when(
h31b==1 & (h31==2) & b5==1 ~ 1 ,
b5==1 ~ 0 )) %>%
set_value_labels(ch_ari = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari = "ARI symptoms in the 2 weeks before the survey")
}
# survey specific changes
# if survey is "IAKR23" or "PHKR31"
# KRdata <- KRdata %>%
# mutate(ch_ari =
# case_when(
# h31b==1 & (h31==2|h31==1) ~ 1 ,
# b5==1 ~ 0 )) %>%
# set_value_labels(ch_ari = c("Yes" = 1, "No"=0)) %>%
# set_variable_labels(ch_ari = "ARI symptoms in the 2 weeks before the survey")
#
# //ARI care-seeking
# This is country specific and the footnote for the final table needs to be checked to see what sources are included.
# The code below only excludes traditional practitioner (usually h32t).
# The variable for traditional healer may be different for different surveys (you can check this by checking all the h32* variables).
# Some surveys also exclude pharmacies, shop, or other sources.
# If you want to also remove pharmacy for example as a source of treatment (country specific condition) you can remove
# h32k from the code below.
KRdata <- KRdata %>%
mutate(ch_ari_care =
case_when(
(ch_ari==1 & b5==1) &
(h32a == 1 | h32b == 1 | h32c == 1 | h32d == 1 | h32e == 1 | h32f == 1 |
h32g == 1 | h32h == 1 | h32i == 1 | h32j == 1 | h32k == 1 | h32l == 1 |
h32m == 1 | h32n == 1 | h32o == 1 | h32p == 1 | h32q == 1 | h32r == 1 |
h32s == 1 | h32u == 1 | h32v == 1 | h32w == 1 | h32x == 1 ) ~ 1 ,
b5==1 & ch_ari==1 ~ 0)) %>%
set_value_labels(ch_ari_care = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_care = "Advice or treatment sought for ARI symptoms")
# //ARI care-seeking same or next day
# some surveys do not have the variable needed to code this indicator which is h46b
if ("TRUE" %in% (!("h46b" %in% names(KRdata))))
KRdata [[paste("h46b")]] <- NA
if ("TRUE" %in% all(is.na(KRdata$h46b)))
{h46b_included <- 0} else {h46b_included <- 1}
if (h46b_included==1) {
KRdata <- KRdata %>%
mutate(ch_ari_care_day =
case_when(
ch_ari==1 & h46b<2 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_care_day = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_care_day = "Advice or treatment sought for ARI symptoms on the same or next day")
} else {
KRdata <- KRdata %>%
mutate(ch_ari_care_day = NA)
}
# *** ARI treatment by source ***
# Two population bases: 1. among children with ARI symptoms, 2. among children with ARI symptoms that sought treatment
# This is country specific and needs to be checked to produce the specific source of interest.
# Some sources are coded below and the same logic can be used to code other sources. h32a-z indicates the source.
# //ARI treatment in government hospital
KRdata <- KRdata %>%
mutate(ch_ari_govh =
case_when(
ch_ari==1 & h32a==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_govh = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_govh = "ARI treatment sought from government hospital among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_govh_trt =
case_when(
ch_ari_care==1 & h32a==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_govh_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_govh_trt = "ARI treatment sought from government hospital among children with ARI that sought treatment")
# //ARI treamtment in government health center
KRdata <- KRdata %>%
mutate(ch_ari_govcent =
case_when(
ch_ari==1 & h32b==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_govcent = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_govcent = "ARI treatment sought from government health center among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_govcent_trt =
case_when(
ch_ari_care==1 & h32b==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_govcent_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_govcent_trt = "ARI treatment sought from government health center among children with ARI that sought treatment")
# //ARI treatment from a private hospital/clinic
KRdata <- KRdata %>%
mutate(ch_ari_pclinc =
case_when(
ch_ari==1 & h32j==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pclinc = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pclinc = "ARI treatment sought from private hospital/clinic among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_pclinc_trt =
case_when(
ch_ari_care==1 & h32j==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pclinc_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pclinc_trt = "ARI treatment sought from private hospital/clinic among children with ARI that sought treatment")
# //ARI treatment from a private doctor
KRdata <- KRdata %>%
mutate(ch_ari_pdoc =
case_when(
ch_ari==1 & h32l==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pdoc = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pdoc = "ARI treatment sought from private doctor among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_pdoc_trt =
case_when(
ch_ari_care==1 & h32l==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pdoc_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pdoc_trt = "ARI treatment sought from private doctor among children with ARI that sought treatment")
# //ARI treatment from a pharmacy
KRdata <- KRdata %>%
mutate(ch_ari_pharm =
case_when(
ch_ari==1 & h32k==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pharm = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pharm = "ARI treatment sought from a pharmacy among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_pharm_trt =
case_when(
ch_ari_care==1 & h32k==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pharm_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pharm_trt = "ARI treatment sought from a pharmacy among children with ARI that sought treatment")
# *** Fever indicators ***
# //Fever
KRdata <- KRdata %>%
mutate(ch_fever =
case_when(
h22==1 & b5==1 ~ 1,
b5==1 ~ 0 )) %>%
set_value_labels(ch_fever = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_fever = "Fever symptoms in the 2 weeks before the survey")
colnames(KRdata)[colnames(KRdata) == 'ch_fever'] <- 'value'
return(KRdata)
}
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surveyPrev documentation built on June 19, 2026, 5:06 p.m.
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Defines functions CH_FEVR_C_FEV
Documented in CH_FEVR_C_FEV
##'CH_FEVR_C_FEV
#' @param KRdata data.frame from surveyPrev::getDHSdata
#'
#' @return A partially processed data.frame that will be used in surveyPrev::getDHSindicator. The whole function can be used as a parameter in surveyPrev::getDHSindicator
#'
#' @author Miaolei Bao, Yunhan Wu, Qianyu Dong
#' @examples
#' \dontrun{
#' dhsData <- getDHSdata(country = "Zambia", indicator = "CH_FEVR_C_FEV", year = 2018)
#' }
#'
#' @export
CH_FEVR_C_FEV <- function(KRdata){
# /*****************************************************************************************************
# Program: CH_ARI_FV.R
# Purpose: Code ARI and fever variables.
# Data inputs: KR dataset
# Data outputs: coded variables
# Author: Shireen Assaf
# Date last modified: July 29, 2022 by Shireen Assaf
# Notes: Check notes for ARI/fever care and treatment variables which are country specific.
# *****************************************************************************************************/
#
# /*----------------------------------------------------------------------------
# Variables created in this file:
# ch_ari "ARI symptoms in the 2 weeks before the survey"
# ch_ari_care "Advice or treatment sought for ARI symptoms"
# ch_ari_care_day "Advice or treatment sought for ARI symptoms on the same or next day"
#
# ch_ari_govh "ARI treatment sought from government hospital among children with ARI"
# ch_ari_govh_trt "ARI treatment sought from government hospital among children with ARI that sought treatment"
# ch_ari_govcent "ARI treatment sought from government health center among children with ARI"
# ch_ari_govcent_trt "ARI treatment sought from government health center among children with ARI that sought treatment"
# ch_ari_pclinc "ARI treatment sought from private hospital/clinic among children with ARI"
# ch_ari_pclinc_trt "ARI treatment sought from private hospital/clinic among children with ARI that sought treatment"
# ch_ari_pdoc "ARI treatment sought from private doctor among children with ARI"
# ch_ari_pdoc_trt "ARI treatment sought from private doctor among children with ARI that sought treatment"
# ch_ari_pharm "ARI treatment sought from pharmacy among children with ARI"
# ch_ari_pharm_trt "ARI treatment sought from pharmacy among children with ARI that sought treatment"
#
# ch_fever "Fever symptoms in the 2 weeks before the survey"
# ch_fev_care "Advice or treatment sought for fever symptoms"
# ch_fev_care_day "Advice or treatment sought for ARI symptoms on the same or next day"
# ch_fev_antib "Antibiotics taken for fever symptoms"
# ----------------------------------------------------------------------------*/
# weight variable
KRdata <- KRdata %>%
mutate(wt = v005/1000000)
# ** ARI indicators ***
# age of child. If b19 is not available in the data use v008 - b3
if ("TRUE" %in% (!("b19" %in% names(KRdata))))
KRdata [[paste("b19")]] <- NA
if ("TRUE" %in% all(is.na(KRdata$b19)))
{ b19_included <- 0} else { b19_included <- 1}
if (b19_included==1) {
KRdata <- KRdata %>%
mutate(age = b19)
} else {
KRdata <- KRdata %>%
mutate(age = v008 - b3)
}
# //ARI symptoms
# ARI definition differs by survey according to whether h31c is included or not
if ("TRUE" %in% (!("h31c" %in% names(KRdata))))
KRdata [[paste("h31c")]] <- NA
if ("TRUE" %in% all(is.na(KRdata$h31c)))
{ h31c_included <- 0} else { h31c_included <- 1}
if (h31c_included==1) {
KRdata <- KRdata %>%
mutate(ch_ari =
case_when(
h31b==1 & (h31c==1 | h31c==3) & b5==1 ~ 1,
b5==1 ~ 0 )) %>%
set_value_labels(ch_ari = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari = "ARI symptoms in the 2 weeks before the survey")
} else {
KRdata <- KRdata %>%
mutate(ch_ari =
case_when(
h31b==1 & (h31==2) & b5==1 ~ 1 ,
b5==1 ~ 0 )) %>%
set_value_labels(ch_ari = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari = "ARI symptoms in the 2 weeks before the survey")
}
# survey specific changes
# if survey is "IAKR23" or "PHKR31"
# KRdata <- KRdata %>%
# mutate(ch_ari =
# case_when(
# h31b==1 & (h31==2|h31==1) ~ 1 ,
# b5==1 ~ 0 )) %>%
# set_value_labels(ch_ari = c("Yes" = 1, "No"=0)) %>%
# set_variable_labels(ch_ari = "ARI symptoms in the 2 weeks before the survey")
#
# //ARI care-seeking
# This is country specific and the footnote for the final table needs to be checked to see what sources are included.
# The code below only excludes traditional practitioner (usually h32t).
# The variable for traditional healer may be different for different surveys (you can check this by checking all the h32* variables).
# Some surveys also exclude pharmacies, shop, or other sources.
# If you want to also remove pharmacy for example as a source of treatment (country specific condition) you can remove
# h32k from the code below.
KRdata <- KRdata %>%
mutate(ch_ari_care =
case_when(
(ch_ari==1 & b5==1) &
(h32a == 1 | h32b == 1 | h32c == 1 | h32d == 1 | h32e == 1 | h32f == 1 |
h32g == 1 | h32h == 1 | h32i == 1 | h32j == 1 | h32k == 1 | h32l == 1 |
h32m == 1 | h32n == 1 | h32o == 1 | h32p == 1 | h32q == 1 | h32r == 1 |
h32s == 1 | h32u == 1 | h32v == 1 | h32w == 1 | h32x == 1 ) ~ 1 ,
b5==1 & ch_ari==1 ~ 0)) %>%
set_value_labels(ch_ari_care = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_care = "Advice or treatment sought for ARI symptoms")
# //ARI care-seeking same or next day
# some surveys do not have the variable needed to code this indicator which is h46b
if ("TRUE" %in% (!("h46b" %in% names(KRdata))))
KRdata [[paste("h46b")]] <- NA
if ("TRUE" %in% all(is.na(KRdata$h46b)))
{h46b_included <- 0} else {h46b_included <- 1}
if (h46b_included==1) {
KRdata <- KRdata %>%
mutate(ch_ari_care_day =
case_when(
ch_ari==1 & h46b<2 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_care_day = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_care_day = "Advice or treatment sought for ARI symptoms on the same or next day")
} else {
KRdata <- KRdata %>%
mutate(ch_ari_care_day = NA)
}
# *** ARI treatment by source ***
# Two population bases: 1. among children with ARI symptoms, 2. among children with ARI symptoms that sought treatment
# This is country specific and needs to be checked to produce the specific source of interest.
# Some sources are coded below and the same logic can be used to code other sources. h32a-z indicates the source.
# //ARI treatment in government hospital
KRdata <- KRdata %>%
mutate(ch_ari_govh =
case_when(
ch_ari==1 & h32a==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_govh = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_govh = "ARI treatment sought from government hospital among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_govh_trt =
case_when(
ch_ari_care==1 & h32a==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_govh_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_govh_trt = "ARI treatment sought from government hospital among children with ARI that sought treatment")
# //ARI treamtment in government health center
KRdata <- KRdata %>%
mutate(ch_ari_govcent =
case_when(
ch_ari==1 & h32b==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_govcent = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_govcent = "ARI treatment sought from government health center among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_govcent_trt =
case_when(
ch_ari_care==1 & h32b==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_govcent_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_govcent_trt = "ARI treatment sought from government health center among children with ARI that sought treatment")
# //ARI treatment from a private hospital/clinic
KRdata <- KRdata %>%
mutate(ch_ari_pclinc =
case_when(
ch_ari==1 & h32j==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pclinc = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pclinc = "ARI treatment sought from private hospital/clinic among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_pclinc_trt =
case_when(
ch_ari_care==1 & h32j==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pclinc_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pclinc_trt = "ARI treatment sought from private hospital/clinic among children with ARI that sought treatment")
# //ARI treatment from a private doctor
KRdata <- KRdata %>%
mutate(ch_ari_pdoc =
case_when(
ch_ari==1 & h32l==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pdoc = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pdoc = "ARI treatment sought from private doctor among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_pdoc_trt =
case_when(
ch_ari_care==1 & h32l==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pdoc_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pdoc_trt = "ARI treatment sought from private doctor among children with ARI that sought treatment")
# //ARI treatment from a pharmacy
KRdata <- KRdata %>%
mutate(ch_ari_pharm =
case_when(
ch_ari==1 & h32k==1 & b5==1 ~ 1 ,
ch_ari==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pharm = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pharm = "ARI treatment sought from a pharmacy among children with ARI")
KRdata <- KRdata %>%
mutate(ch_ari_pharm_trt =
case_when(
ch_ari_care==1 & h32k==1 & b5==1 ~ 1 ,
ch_ari_care==1 & b5==1 ~ 0 )) %>%
set_value_labels(ch_ari_pharm_trt = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_ari_pharm_trt = "ARI treatment sought from a pharmacy among children with ARI that sought treatment")
# *** Fever indicators ***
# //Fever
KRdata <- KRdata %>%
mutate(ch_fever =
case_when(
h22==1 & b5==1 ~ 1,
b5==1 ~ 0 )) %>%
set_value_labels(ch_fever = c("Yes" = 1, "No"=0)) %>%
set_variable_labels(ch_fever = "Fever symptoms in the 2 weeks before the survey")
colnames(KRdata)[colnames(KRdata) == 'ch_fever'] <- 'value'
return(KRdata)
}
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