Surveillance Data Cleaning and Preparation for Public Health R package mudnester version 0.7.8 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). Software 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 Nicolas Smoll <nicolas.smoll@health.qld.gov.au> Comprehensive R Archive Network (CRAN) 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) MIT + file LICENSE (https://CRAN.R-project.org/package=mudnester/LICENSE) 2026-10-02 application/tgz https://CRAN.R-project.org/package=mudnester doi:10.32614/CRAN.package.mudnester en-GB