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) 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: ), Moderna [fnd] (Support for this package's development was provided via the Moderna Global Research Fellowship) Maintainer: Nicolas Smoll Packaged: 2026-10-02 13:10:15 UTC; root Repository: https://cran.r-universe.dev Date/Publication: 2026-10-02 12:52:35 UTC RemoteUrl: https://github.com/cran/mudnester RemoteRef: HEAD RemoteSha: f7d9bb56bde2a1a502fd8e0c9a8080ab0044f216