Prepare Antimalarial Treatment Data for MBG Analysis

Prepares cluster-level antimalarial treatment data for MBG analysis. Uses a dictionary-driven approach matching the indicator codes from calc_antimalarial_dhs.

Usage

calc_antimalarial_mbg(
  dhs_kr,
  gps_data,
  indicators = "antimalarial",
  survey_vars = list(cluster = "v001", age = "hw1", fever = "h22"),
  gps_vars = list(cluster = "DHSCLUST", lat = "LATNUM", lon = "LONGNUM")
)

Arguments

dhs_kr

DHS Children's Recode (KR) dataset.

gps_data

DHS GPS dataset with cluster coordinates.

indicators

Character vector of indicators to calculate. See .antimalarial_mbg_dictionary() for the full list of standardized indicator codes. Default: "antimalarial".

survey_vars

Named list mapping DHS variable names:

• cluster: Cluster ID (default: "v001")

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

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

gps_vars

Named list for GPS variable mapping.

Value

A named list of data.tables (one per indicator), each with columns:

• cluster_id: Cluster identifier

• indicator: Numerator count (children receiving antimalarial)

• samplesize: Denominator count (febrile U5 children)

• x: Longitude

• y: Latitude

Details

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

All dictionary-based indicators share the same data preparation pipeline:

1. Filter to febrile U5 children (via .prepare_antimalarial_data())

2. Classify care-seeking sectors if needed (via .classify_csb_from_h32())

3. Apply per-indicator filters and aggregate to cluster-level counts

See also

calc_antimalarial_dhs() for survey-weighted estimates, calc_act_mbg() for ACT-specific treatment

Examples

if (FALSE) { # \dontrun{
am_mbg <- calc_antimalarial_mbg(
  dhs_kr = kr_data,
  gps_data = gps_data,
  indicators = c("antimalarial", "antimalarial_public")
)
} # }