mudnester - Surveillance Data Cleaning and Preparation for Public Health
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 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. 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 its reference rate's own bounds.
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).
