Package: mudnester
Title: Surveillance Data Cleaning and Preparation for Public Health
Version: 0.7.8
Description: Clean, prepare, and aggregate surveillance data for public health analysis.
    Provides structural data cleaning and standardisation (clean_the_nest()),
    age categorisation against ~50 published schemes with publication-ready
    labelling (preening()), time-unit aggregation with zero-filling and
    seasonal awareness (roost()), joint aggregation of several linked event
    dates (e.g. onset, admission, ICU, complication, fatality) into one table of
    comparable rate columns (flyway()), under-ascertainment correction via a
    stratified, time-varying multiplier factor supplied directly, derived by the
    ratio (multiplier) method, or derived by inverting an externally sourced
    severity rate (e.g. an infection-fatality-rate anchor) against an observed
    severity ratio (corncrake()), comorbidity detection from ICD-10-AM
    clinical coding (plumage()), vaccine coverage data construction
    (brood()), hash-based de-identification (molting()), and relinking
    of previously de-identified data (homing()). brood() produces a
    brood_df object supporting two population models: pre-aggregated
    denominators (population_model = "pre_aggregated") and record-level cohort
    designs (population_model = "cohort"). The cohort model handles single
    time-point coverage snapshots, interrupted time series analysis via a
    built-in sweep returning monthly coverage rates (time_series = TRUE), and
    birth cohort designs with person-time computation. This cohort/time-series
    coverage model was applied in Roughan et al. (2026)
    <doi:10.33321/cdi.2026.50.031> to estimate infant immunisation coverage
    against respiratory syncytial virus over an 18-month period. Both wide
    format (one row per person with dose columns, from
    'starling'::murmuration()) and long format (one row per dose) are accepted.
    corncrake() returns both a point-corrected count and uncertainty bounds
    wherever they can be derived, including the inverse relationship between a
    severity-anchored factor and the bounds of its own reference rate. Built for
    Australian public health surveillance practice but not specific to it -- see
    individual function documentation for notes on non-Australian use (e.g.
    Northern Hemisphere season boundaries).
Authors@R: c(
    person("Nicolas", "Smoll", email = "nicolas.smoll@health.qld.gov.au",
        role = c("aut", "cre"),
        comment = c(ORCID = "0000-0002-6923-9701")),
    person("Moderna", role = "fnd",
        comment = "Support for this package's development was provided via the Moderna Global Research Fellowship")
    )
License: MIT + file LICENSE
Depends: R (>= 4.1)
Imports: dplyr (>= 1.1.0), tidyr (>= 1.3.0), lubridate (>= 1.9.0),
        stringr (>= 1.5.0), rlang (>= 1.1.0), tibble (>= 3.2.0), digest
        (>= 0.6.30), janitor (>= 2.2.0), utils, stats
Suggests: testthat (>= 3.0.0), knitr (>= 1.42), rmarkdown (>= 2.20),
        usethis (>= 2.1.0), gtsummary, ggplot2
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 8.0.0
VignetteBuilder: knitr
URL: https://github.com/nrsmoll/mudnester
BugReports: https://github.com/nrsmoll/mudnester/issues
NeedsCompilation: no
Author: Nicolas Smoll [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-6923-9701>),
  Moderna [fnd] (Support for this package's development was provided via
    the Moderna Global Research Fellowship)
Maintainer: Nicolas Smoll <nicolas.smoll@health.qld.gov.au>
Packaged: 2026-09-23 03:20:56 UTC; SmollN
Repository: CRAN
Date/Publication: 2026-10-02 11:50:02 UTC
Built: R 4.6.1; ; 2026-10-02 13:12:50 UTC; unix
