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Calculate 60-day follow-up of inadequate AFP cases by month of onset

Source: R/afp_quality.R
calc_afp_followup.Rd

For each month of onset in the window, and each unit at level, counts of cases with inadequate stools that are due for follow-up and where each stands. The window is the window_months months of onset ending with the last month holding a case already due, that is the month of as_of - due_days, so recent months with nothing yet due are not listed. The case flags are those of afp_followup_status().

Usage

calc_afp_followup(
  cases,
  as_of = Sys.Date(),
  window_months = 6,
  level = "adm0",
  due_days = 60,
  on_time_days = c(60, 90),
  adequacy = "followup",
  adequacy_args = list(),
  compatible_classes = "COMPATIBLE",
  review_classes = c("NPAFP", "PENDING", "LAB PENDING"),
  review_findings = c("Residual weakness/paralysis", "Died before follow-up",
    "Lost to follow-up"),
  review_max_age_months = 60,
  review_min_doses = 3,
  dose_unknown = 99,
  cols = list()
)

Arguments

cases

Cleaned AFP cases, one row per case (data.frame or tibble).

as_of

The reporting date, as a Date or a string that as.Date() reads. Defaults to Sys.Date(). Every day count runs to it.

window_months

Months of onset to report (default 6).

level

Administrative level to group by: "adm0" (country, the default), "adm1" (province) or "adm2" (district). Cases with no identifier at that level are left out.

due_days

Days after onset from which follow-up of an inadequate case is due (default 60).

on_time_days

First and last day after onset at which a follow-up is on time (default c(60, 90)).

adequacy

Stool adequacy definition passed to afp_stool_adequacy() (default "followup").

adequacy_args

Named list of further arguments for afp_stool_adequacy(), for example list(adequate_value = "YES").

compatible_classes

Classifications counted as compatible, matched ignoring case (default "COMPATIBLE").

review_classes

Classifications the review screen keeps, matched ignoring case (default c("NPAFP", "PENDING", "LAB PENDING")). A blank classification is always kept.

review_findings

Follow-up findings that keep a case under review (default residual weakness or paralysis, died before follow-up, and lost to follow-up, in POLIS wording).

review_max_age_months

Age in months at and above which the screen drops a case (default 60).

review_min_doses

Fewest doses that count as vaccinated when routine and campaign OPV counts are missing (default 3).

dose_unknown

Dose value that means unknown (default 99).

cols

Named list overriding default column names, in the style of calc_polio_indicators(), for example list(cases = list(stool1_condition = "s1_cond")). The defaults are the polished defaults plus the module columns listed under Details of calc_afp_timeliness().

Value

A tibble with one row per unit and month of onset: level, guid, name, onset_month, the counts above and partial. Every month of the window appears for every unit with a case, with zero counts where the month has none.

Details

  • records: cases with onset in the month.

  • inadequate: cases classed inadequate by adequacy.

  • due: inadequate cases at least due_days (default 60) days past onset.

  • completed: due cases followed up. Completion is completed / due.

  • mature: due cases more than on_time_days[2] (default 90) days past onset, whose follow-up window has closed; mature_completed is those followed up. Completion read as mature_completed / mature is not pulled down by recent months.

  • on_time: due cases followed up on_time_days[1] to on_time_days[2] days after onset. Timeliness is on_time / due.

  • no_followup and overdue: due cases not followed up, and those of them past on_time_days[2] days.

  • compatible and review: compatible cases, and cases the review screen keeps.

  • partial: the month's last day has not yet reached due_days.

This differs from fup_insa_cases_pct in calc_polio_indicators(), which takes every case with code 0 under the "polished" adequacy rule as its denominator whether or not follow-up is yet due, and counts a case as followed up when a follow-up interval is recorded, at any day.

Examples

cases <- tibble::tibble(
  adm0_guid = "G0",
  adm0 = "Country",
  paralysis_onset_date = as.Date(c("2025-03-10", "2025-04-02")),
  onset_to_stool1 = c(20, 2),
  onset_to_stool2 = c(21, 3),
  stool1_to_stool2 = 1,
  stool1condition = "Good",
  stool2condition = "Good",
  classification_all = "NPAFP",
  followup_date = as.Date(c("2025-05-20", NA)),
  followup_findings = NA_character_
)
calc_afp_followup(cases, as_of = "2025-07-15", window_months = 3)
#> # A tibble: 3 × 16
#>   level guid  name    onset_month records inadequate   due completed mature
#>   <chr> <chr> <chr>   <date>        <int>      <int> <int>     <int>  <int>
#> 1 adm0  G0    Country 2025-03-01        1          1     1         1      1
#> 2 adm0  G0    Country 2025-04-01        1          0     0         0      0
#> 3 adm0  G0    Country 2025-05-01        0          0     0         0      0
#> # ℹ 7 more variables: mature_completed <int>, on_time <int>, no_followup <int>,
#> #   overdue <int>, compatible <int>, review <int>, partial <lgl>