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Compute Marginal Resistance Rates from Preprocessed Wide Data

Source: R/daly_resistance_profiles.R
compute_marginals_from_data.Rd

Takes the wide-format tibble produced by preprocess_for_profiles() and computes marginal resistance rates per pathogen x antibiotic class, optionally stratified by geography, year, and/or patient outcome. The counting unit is always isolate_id: a patient with multiple isolates contributes one count per isolate.

Usage

compute_marginals_from_data(
  data_wide,
  col_map,
  panel_map,
  stratify_by = NULL,
  outcome_col = NULL,
  min_n_tested = 30L,
  external_marginals = NULL,
  ext_col_map = list(pathogen_col = "pathogen", class_col = "antibiotic_class",
    geography_col = "geography", year_col = "year", rate_col = "resistance_prevalence")
)

Arguments

data_wide

Tibble. Output of preprocess_for_profiles()$data_wide. One row per isolate; antibiotic-class columns contain "S", "R", or NA (not tested).

col_map

Named list. col_map_resolved from preprocess_for_profiles().

panel_map

Named list. Same panel used in preprocess_for_profiles().

stratify_by

Character vector or NULL. Dimensions to stratify over. Valid: "geography", "year". Default NULL.

outcome_col

Character or NULL. Column name for patient outcome. When supplied, separate marginals are computed for each outcome value (e.g. Died vs Discharged). Default NULL.

min_n_tested

Integer. Minimum tested-isolate count per (stratum x pathogen x class) cell. Cells below this threshold are dropped with a logged reason. Default 30L.

external_marginals

Data frame or NULL. Pre-modelled marginal resistance rates (e.g. GBD ST-GPR estimates). When provided, locally computed rates are replaced where a match exists on pathogen x class [x geography x year]. Must have columns matching ext_col_map. Default NULL.

ext_col_map

Named list. Column names in external_marginals. Default list(pathogen_col="pathogen", class_col="antibiotic_class", geography_col="geography", year_col="year", rate_col="resistance_prevalence").

Value

Tibble with columns: pathogen, antibiotic_class, [stratum columns], n_tested, n_resistant, marginal_resistance, marginal_source ("computed" or "external").

Details

Optionally, externally modelled marginals (e.g. from GBD ST-GPR) can be supplied to override the locally computed values while retaining the pairwise correlation structure from the local data.