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Calculate Fever Prevalence from DHS Data

Source: R/indicator_fever.R
calc_fever_dhs_core.Rd

Estimates fever prevalence among children under 5 using survey-weighted methods. This is step 0 of the case management cascade.

Usage

calc_fever_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")

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

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 fever estimates by grouping level, including:

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

  • dhs_fever: Proportion with fever among U5 children

  • dhs_fever_low, dhs_fever_upp: 95\

  • dhs_n_children: Number of U5 children (denominator)

  • dhs_n_fever: Number of febrile children

Details

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

This function calculates fever prevalence among alive U5 children. The denominator is ALL alive children under 5, not just febrile children. This differs from CSB/ACT which use febrile children as denominator.

Fever prevalence is the entry point (step 0) of the case management cascade: Fever -> Sought care -> Tested -> Any antimalarial -> ACT.

See also

calc_csb_dhs() for care-seeking behavior (step 1), calc_case_management_dhs() for the full cascade

Examples

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