Calculate non-polio AFP rate

Calculate the NPAFP rate from POLIS data. Can either pass raw.data to calculate NPAFP rates on the global dataset, or a ctry.data dataset.

Usage

f.npafp.rate.01(
  afp.data,
  pop.data,
  start.date,
  end.date,
  spatial.scale,
  pending = T,
  missing_agemonths = F,
  rolling = F,
  sp_continuity_validation = T
)

Arguments

afp.data

tibble AFP data which includes GUID at a given spatial scale formatted as adm(0,1,2)guid, onset date as date and cdc.classification.all2 which includes "NPAFP", "PENDING", "LAB PENDING". This is either ctry.data$afp.all.2 of extract_country_data() or init_dr() or raw.data$afp of get_all_polio_data().

pop.data

tibble Under 15 population data by a given spatial scale including year, adm(0,1,2)guid, u15pop, and ctry/prov/dist as appropriate. This is part of the output of get_all_polio_data() and extract_country_data().

start.date

str Start date with the format "YYYY-MM-DD".

end.date

str Start date with the format "YYYY-MM-DD".

spatial.scale

str Spatial scale for analysis.

• "prov" Province level.

• "dist" District level.

• "ctry" Country level.

pending

logical Should cases classified as PENDING or LAB PENDING be included in calculations? Default TRUE.

missing_agemonths

logical Should cases with NA values for age.months be included? Default FALSE.

rolling

logical Should the analysis be performed on a rolling bases? Default FALSE.

sp_continuity_validation

logical Should we filter places that are not present for the entirety of the analysis dates? Default TRUE.

Value

tibble A table containing NPAFP rates as well as additional information relevant to each location analyzed.

Examples

if (FALSE) { # \dontrun{
raw.data <- get_all_polio_data()
npafp_ctry <- f.npafp.rate.01(raw.data$afp, raw.data$ctry.pop, "2022-01-01", "2024-12-31", "ctry")
} # }