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Prepare Fever Prevalence Data for MBG Analysis

Source: R/indicator_fever.R
calc_fever_mbg.Rd

Prepares cluster-level fever prevalence data for MBG analysis. Calculates counts of alive children under 5 who had fever in the last 2 weeks, at each survey cluster.

Usage

calc_fever_mbg(
  dhs_kr,
  gps_data,
  indicators = "fever",
  survey_vars = list(cluster = "v001", age = "hw1", fever = "h22", alive = "b5"),
  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:

  • "fever": Fever prevalence among alive U5 children

Default: "fever".

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")

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

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 with fever)

  • samplesize: Denominator count (all alive U5 children)

  • x: Longitude

  • y: Latitude

Details

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

See also

calc_fever_dhs_core() for survey-weighted estimates, calc_csb_mbg() for care-seeking behavior

Examples

if (FALSE) { # \dontrun{
fever_mbg <- calc_fever_mbg(
  dhs_kr = kr_data,
  gps_data = gps_data
)
} # }