Skip to contents

Generate a summary table for sample timeliness intervals

generate_int_data.Rd

The summary table will output timeliness intervals of samples from collection to lab testing. Lab timeliness will only be calculated if the lab data is attached. Otherwise, by default, the function will return only the timeliness intervals up to when the samples were sent to lab.

Usage

generate_int_data(
  afp_data,
  pop_data,
  start_date,
  end_date,
  spatial_scale,
  lab_data_summary = NULL,
  ctry.data = lifecycle::deprecated(),
  spatial.scale = lifecycle::deprecated(),
  lab.data = lifecycle::deprecated()
)

Arguments

afp_data

tibble AFP dataset.

pop_data

tibble Population dataset that matches the spatial scale.

start_date

str Start date of analysis.

end_date

str End date of analysis.

spatial_scale

str Scale to summarize to. Valid values are: "ctry", "prov", or "all". "dist" not available currently.

lab_data_summary

tibble Summarized lab data, if available. This parameter will calculate timeliness intervals in the lab. Otherwise, only the field component will be presented. This is the output of generate_lab_timeliness().

ctry.data

list [Deprecated]

spatial.scale

str [Deprecated] Renamed in favor of spatial_scale.

lab.data

tibble [Deprecated] Renamed in favor of lab_data_summary.

Passing ctry.data has been deprecated in favor of independently assigning the AFP dataset to afp.data and the population dataset to pop.data. This allows the function to run either on raw.data or ctry.data.

Value

tibble A table summarizing median days for different timeliness intervals.

See also

clean_ctry_data()

Examples

if (FALSE) { # \dontrun{
raw.data <- get_all_polio_data(attach.spatial.data = FALSE)
ctry.data <- extract_country_data("algeria", raw.data)
# lab data not attached
int.data <- generate_int_data(
  raw.data$afp, raw.data$ctry.pop,
  "2021-01-01", "2023-12-31", "ctry"
)

# If lab data is available. Assume ctry.data is loaded.
lab_path <- "C:/Users/ABC1/Desktop/algeria_lab.csv"
lab.data <- readr::read_csv(lab_path)
lab.data.summary <- generate_lab_timeliness(
  lab.data, "ctry",
  "2021-01-01", "2023-12-31"
)
int.data <- generate_int_data(
  ctry.data$afp.all.2, ctry.data$ctry.pop,
  "2021-01-01", "2023-12-31", "ctry",
  lab.data.summary
)
} # }