# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "starling" in publications use:' type: software license: GPL-3.0-or-later title: 'starling: Link Infectious Disease Cases to Vaccination and Hospitalization Records' version: 0.6.5 doi: 10.32614/CRAN.package.starling abstract: '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) and Sayers et al. (2016) . 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).' authors: - family-names: Smoll given-names: Nicolas email: nrsmoll@gmail.com orcid: https://orcid.org/0000-0002-6923-9701 repository: https://nrsmoll.r-universe.dev commit: edbc6f4aae3c5ddf79247fbe0be265629b6d9e85 date-released: '2026-01-26' contact: - family-names: Smoll given-names: Nicolas email: nrsmoll@gmail.com orcid: https://orcid.org/0000-0002-6923-9701