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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "mudnester" in publications use:'
type: software
license: MIT
title: 'mudnester: Surveillance Data Cleaning and Preparation for Public Health'
version: 0.7.8
abstract: '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) <https://doi.org/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:
- family-names: Smoll
  given-names: Nicolas
  email: nicolas.smoll@health.qld.gov.au
  orcid: https://orcid.org/0000-0002-6923-9701
preferred-citation:
  type: manual
  title: 'mudnester: Surveillance Data Cleaning and Preparation for Public Health'
  authors:
  - family-names: Smoll
    given-names: Nicolas
    email: nicolas.smoll@health.qld.gov.au
    orcid: https://orcid.org/0000-0002-6923-9701
  year: '2026'
  notes: R package version 0.7.2
  url: https://github.com/nrsmoll/mudnester
repository: https://cran.r-universe.dev
repository-code: https://github.com/nrsmoll/mudnester
commit: f7d9bb56bde2a1a502fd8e0c9a8080ab0044f216
url: https://github.com/nrsmoll/mudnester
date-released: '2026-10-02'
contact:
- family-names: Smoll
  given-names: Nicolas
  email: nicolas.smoll@health.qld.gov.au
  orcid: https://orcid.org/0000-0002-6923-9701