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Calculate Effective Coverage of Case Management from DHS Data

Source: R/indicator_case_management.R
calc_case_management_dhs.Rd

Computes the effective coverage of case management as the product of two survey-weighted proportions: $$Effective\;CM = CSB\;rate \times P(ACT \mid antimalarial)$$

Usage

calc_case_management_dhs(
  dhs_kr,
  survey_vars = list(cluster = "v021", weight = "v005", stratum = "v022", age = "hw1",
    fever = "h22", alive = "b5", act = "ml13e"),
  region_var = NULL
)

Arguments

dhs_kr

DHS children's recode (KR) dataset (data.frame or tibble).

survey_vars

Named list mapping DHS variable names. Required keys:

  • cluster: Cluster/PSU ID (default: "v021")

  • weight: Survey weight (default: "v005")

  • stratum: Stratum variable (default: "v022")

  • age: Child's age in months (default: "hw1")

  • fever: Had fever in last 2 weeks (default: "h22")

  • alive: Child survival status (default: "b5")

  • act: Received ACT treatment (default: "ml13e")

region_var

Optional column name in dhs_kr to use as grouping variable (e.g., "v024" for region).

Value

Named list of tibbles:

adm0

National-level estimates (always present)

adm1

Admin-1 estimates (when region_var provided)

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

Details

where CSB rate is the care-seeking rate for fever among children under 5, and P(ACT | antimalarial) is the proportion receiving ACT among febrile children who received any antimalarial treatment.

Two variants are produced:

  • EFF_CM_ANY: using any care-seeking (public or private)

  • EFF_CM_PUBLIC: using public sector care-seeking only

Returns results in standardized long format with list(adm0, adm1) structure.

The effective coverage indicator captures the probability that a febrile child both seeks care AND receives ACT (given they receive any antimalarial). CIs are approximated using the delta method assuming independence: $$SE(A \times B) \approx \sqrt{A^2 \cdot SE(B)^2 + B^2 \cdot SE(A)^2}$$

The antimalarial denominator includes any child receiving at least one drug from the ml13 series (or h37a-h fallback for older surveys). ACT is identified by ml13e (or h37e fallback).

See also

case_management_dictionary() for indicator definitions, calc_csb_dhs_core(), calc_act_dhs()

Examples

if (FALSE) { # \dontrun{
result <- calc_case_management_dhs(
  dhs_kr = kr_data,
  region_var = "v024"
)
} # }