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Calculate Antimalarial Treatment from DHS Data

Source: R/indicator_antimalarial.R
calc_antimalarial_dhs_core.Rd

Estimates the proportion of febrile children under 5 who received any antimalarial drug using survey-weighted methods. This is step 3 of the case management cascade.

Usage

calc_antimalarial_dhs_core(
  dhs_kr,
  survey_vars = list(cluster = "v021", weight = "v005", stratum = "v022", age = "hw1",
    fever = "h22", alive = "b5"),
  region_var = NULL,
  gps_data = NULL,
  gps_vars = list(cluster = "DHSCLUST", lat = "LATNUM", lon = "LONGNUM"),
  shapefile = NULL,
  admin_level = NULL,
  join_nearest = TRUE
)

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")

region_var

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

gps_data

Optional DHS GPS dataset with cluster coordinates.

gps_vars

Named list for GPS variables (cluster, lat, lon).

shapefile

Optional sf object with administrative boundaries.

admin_level

Character vector of admin columns from shapefile (e.g., c("adm1", "adm2")).

join_nearest

Logical; if TRUE, assigns clusters outside polygons to nearest admin unit. Default: TRUE.

Value

Tibble with antimalarial estimates by grouping level, including:

  • Grouping variables (region, admin level, or national)

  • dhs_antimalarial: Proportion receiving any antimalarial

  • dhs_antimalarial_low, dhs_antimalarial_upp: 95\

  • dhs_n_febrile: Number of febrile children (denominator)

  • dhs_n_antimalarial: Number receiving any antimalarial

Details

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

Auto-detects the available drug series at runtime: ml13* variables (ml13a through ml13g, ml13aa, etc.) are preferred. If absent, falls back to the h37a-h series used in older DHS surveys (e.g. BFA 2021). received_antimalarial = 1 if ANY detected drug variable equals 1. ACT (ml13e / h37e) is a subset.

See also

calc_act_dhs() for ACT-specific treatment (step 4), calc_case_management_dhs() for the full cascade

Examples

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