starling: Link Infectious Disease Cases to Vaccination and Hospitalization Records

Facilitates probabilistic record linkage between infectious disease surveillance datasets (notifiable disease registers, outbreak line-lists), vaccination registries, and hospitalization records using methods based on Fellegi and Sunter (1969) <doi:10.1080/01621459.1969.10501049> and Sayers et al. (2016) <doi:10.1093/ije/dyv322>. The package provides core functions for data preparation, linkage, and analysis: clean_the_nest() standardizes variable names and formats across heterogeneous datasets; murmuration() performs machine learning-based record linkage using blocking variables and similarity metrics; molting() deidentifies datasets for secure sharing; homing() re-identifies previously deidentified datasets; plumage() identifies and categorizes comorbidities; and preening() creates analysis-ready variables including age categories and temporal groupings. Designed for epidemiological research linking acute and post-acute disease outcomes to vaccination status and healthcare utilization. Supports multiple linkage scenarios including case-to-vaccination, case-to-hospitalization, and event-based vaccination status determination (e.g., outbreak attendees, flight passengers, exposure site visitors).

Version:	0.6.5
Depends:	R (≥ 3.5.0)
Imports:	dplyr, lubridate, janitor, stringr, tidyr, reclin2, datawizard, digest, rlang, magrittr
Suggests:	testthat (≥ 3.0.0), knitr, gtsummary, rmarkdown
Published:	2026-01-26
DOI:	10.32614/CRAN.package.starling
Author:	Nicolas Smoll [aut, cre]
Maintainer:	Nicolas Smoll <nrsmoll at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	no
Language:	en-US
CRAN checks:	starling results

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