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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).
| Version: | 0.7.8 |
| 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 |
| Published: | 2026-10-02 |
| DOI: | 10.32614/CRAN.package.mudnester (may not be active yet) |
| Author: | Nicolas Smoll |
| Maintainer: | Nicolas Smoll <nicolas.smoll at health.qld.gov.au> |
| BugReports: | https://github.com/nrsmoll/mudnester/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/nrsmoll/mudnester |
| NeedsCompilation: | no |
| Language: | en-GB |
| Citation: | mudnester citation info |
| CRAN checks: | mudnester results |
| Package source: | mudnester_0.7.8.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: mudnester_0.7.8.zip |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): mudnester_0.7.8.tgz, r-oldrel (x86_64): mudnester_0.7.8.tgz |
| Reverse suggests: | starling |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.