Computes D_J, the number of deaths for each underlying cause J from population-level vital registration or mortality data. Optionally stratified by grouping variables such as age group, sex, year, or location.

Usage

calculate_deaths_by_cause(
  pop_data,
  cause_col = "cause_of_death",
  deaths_col = NULL,
  groupby_cols = NULL
)

Arguments

pop_data: Data frame. Population-level vital registration or mortality data. Required – this function does not accept facility-level data.
cause_col: Character. Column containing the underlying cause of death (cause J), e.g. an ICD-10 code or cause name. Default "cause_of_death".
deaths_col: Character. Column with pre-aggregated death counts. Set to NULL if each row represents one individual death record. Default NULL.
groupby_cols: Character vector. Additional stratification columns (e.g., c("Age_bin", "gender", "year")). Default NULL.

Value

Data frame with columns: cause_col, any groupby_cols, D_J (death count), D_J_method ("population"), D_J_confidence ("high").

Details

This function requires population-level data. If only facility-level data are available, use calculate_syndrome_deaths() with facility_data instead, which directly counts deaths by syndrome.

References

Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance in 2019. Lancet. 2022.

Examples

if (FALSE) { # \dontrun{
# One row per death record
d_j <- calculate_deaths_by_cause(
  pop_data  = vital_reg,
  cause_col = "icd10_cause"
)

# Pre-aggregated counts, stratified by age and sex
d_j <- calculate_deaths_by_cause(
  pop_data     = vital_reg,
  cause_col    = "icd10_cause",
  deaths_col   = "n_deaths",
  groupby_cols = c("Age_bin", "gender")
)
} # }