Calculate Care-Seeking Behavior by Wealth Quintile from DHS Data

Estimates care-seeking behavior for febrile children under 5, stratified by wealth quintile. Uses WHO World Malaria Report methodology with survey-weighted estimates.

Usage

calc_csb_by_wealth_dhs(
  dhs_kr,
  survey_vars = list(cluster = "v021", weight = "v005", stratum = "v022", age = "hw1",
    fever = "h22", alive = "b5"),
  quintiles = 1:5,
  wealth_var = "v190",
  csb_priority_method = c("all", "first", "public", "private"),
  region_var = NULL,
  ci_method = "logit"
)

Arguments

dhs_kr

DHS children's recode (KR) dataset in tidy format.

survey_vars

Named list mapping DHS variable names. See calc_csb_dhs_core() for details.

quintiles

Numeric vector of wealth quintiles to include. Default: 1:5 (all quintiles). Use c(1) for poorest only, c(1,2) for poorest + poorer, etc.

wealth_var

Name of wealth quintile variable in dhs_kr. Default: "v190".

csb_priority_method

Character, one of "all" (default), "first", "public", or "private". Controls how overlapping care-seeking records are resolved so each individual is assigned to at most one sector. See calc_csb_mbg() for details. With non-"all" values, csb_public + csb_private + csb_none sums to 100% within each quintile.

region_var

Optional column name for regional grouping.

ci_method

Method for confidence intervals. Default: "logit".

Value

Named list of tibbles with two levels:

adm0

National-level estimates by wealth quintile (always present)

adm1

Admin-1 estimates by wealth quintile (when region_var provided)

Each tibble contains columns: survey_id, iso3, iso2, survey_type, survey_year, adm0, adm1 (if applicable), wealth_quintile, type, geo_source, point, ci_l, ci_u, numerator, denominator, indicator, indicator_code, numerator_description, denominator_description, denominator_code.

Details

This function extends calc_csb_dhs() to provide wealth-stratified estimates. Each wealth quintile produces separate survey-weighted estimates with confidence intervals.

Methodology: https://github.com/ahadi-analytics/sntmethods/blob/master/inst/methods/csb_dhs.yml

Indicators

The function calculates these indicators (overlapping, not mutually exclusive):

• csb_any: Sought care anywhere

• csb_public: Public sector (including CHW)

• csb_pub_nochw: Public sector excluding CHW

• csb_chw: Community health worker

• csb_private: Any private sector

• csb_priv_formal: Private formal sector

• csb_pharmacy: Pharmacy/drug shop

• csb_priv_informal: Private informal

• csb_priv_form_pha: Private formal or pharmacy

• csb_trained: Trained provider

• csb_none: Did not seek care

See also

• calc_csb_by_wealth_mbg() for wealth-stratified MBG cluster data

• calc_csb_dhs() for standard survey-weighted estimates

• calc_csb_mbg() for non-stratified MBG data

Examples

if (FALSE) { # \dontrun{
# Care-seeking for poorest quintile only
csb_poorest <- calc_csb_by_wealth_dhs(
  dhs_kr = kr_data,
  quintiles = 1
)

# Compare all quintiles nationally
csb_all <- calc_csb_by_wealth_dhs(
  dhs_kr = kr_data,
  quintiles = 1:5
)

# Regional estimates for poorest and richest
csb_regional <- calc_csb_by_wealth_dhs(
  dhs_kr = kr_data,
  quintiles = c(1, 5),
  region_var = "v024"
)
} # }