Filter surveillance data by standard epidemiological dimensions

Applies a set of standard include/exclude filters to a database table or data frame using the conventional surveillance field names. Each NULL argument is a no-op, so callers only need to supply the dimensions they actually want to restrict.

Usage

mandatory_db_filter(
  .data,
  granularity_time = NULL,
  granularity_time_not = NULL,
  granularity_geo = NULL,
  granularity_geo_not = NULL,
  country_iso3 = NULL,
  location_code = NULL,
  age = NULL,
  age_not = NULL,
  sex = NULL,
  sex_not = NULL
)

Arguments

.data

A data frame, data.table, or remote database table (e.g. the result of dplyr::tbl()) that contains the standard surveillance columns.

granularity_time

Character vector. Values of granularity_time to keep. NULL (default) applies no filter.

granularity_time_not

Character vector. Values of granularity_time to drop. NULL (default) applies no filter.

granularity_geo

Character vector. Values of granularity_geo to keep. NULL (default) applies no filter.

granularity_geo_not

Character vector. Values of granularity_geo to drop. NULL (default) applies no filter.

country_iso3

Character vector. Values of country_iso3 to keep. NULL (default) applies no filter.

location_code

Character vector. Values of location_code to keep. NULL (default) applies no filter.

age

Character vector. Values of age to keep. NULL (default) applies no filter.

age_not

Character vector. Values of age to drop. NULL (default) applies no filter.

sex

Character vector. Values of sex to keep. NULL (default) applies no filter.

sex_not

Character vector. Values of sex to drop. NULL (default) applies no filter.

Value

The filtered object in the same class as .data.

Examples

if (FALSE) { # \dontrun{
# Inside a data_selector function, filter a remote table before collecting:
d <- schema$anon_covid_cases$tbl() |>
  mandatory_db_filter(
    granularity_time = "isoweek",
    granularity_geo  = "county",
    age_not          = "total"
  ) |>
  dplyr::collect()
} # }