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Protecting Privacy and Transforming COVID-19 Case Surveillance Datasets for Public Use.
Lee, Brian; Dupervil, Brandi; Deputy, Nicholas P; Duck, Wil; Soroka, Stephen; Bottichio, Lyndsay; Silk, Benjamin; Price, Jason; Sweeney, Patricia; Fuld, Jennifer; Weber, J Todd; Pollock, Dan.
Afiliación
  • Lee B; COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Dupervil B; Office of the Chief Operations Officer, Office of the Chief Information Officer, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Deputy NP; COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Duck W; National Center for Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Soroka S; COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Bottichio L; National Center for Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Silk B; US Public Health Service, Rockville, MD, USA.
  • Price J; COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Sweeney P; Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Fuld J; COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Weber JT; National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Pollock D; COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Public Health Rep ; 136(5): 554-561, 2021.
Article en En | MEDLINE | ID: mdl-34139910
OBJECTIVES: Federal open-data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, tribal, local, and territorial partners. These initiatives advance understanding of health conditions and diseases by providing data to researchers, scientists, and policymakers for analysis, collaboration, and use outside the Centers for Disease Control and Prevention (CDC), particularly for emerging conditions such as COVID-19, for which data needs are constantly evolving. Since the beginning of the pandemic, CDC has collected person-level, de-identified data from jurisdictions and currently has more than 8 million records. We describe how CDC designed and produces 2 de-identified public datasets from these collected data. METHODS: We included data elements based on usefulness, public request, and privacy implications; we suppressed some field values to reduce the risk of re-identification and exposure of confidential information. We created datasets and verified them for privacy and confidentiality by using data management platform analytic tools and R scripts. RESULTS: Unrestricted data are available to the public through Data.CDC.gov, and restricted data, with additional fields, are available with a data-use agreement through a private repository on GitHub.com. PRACTICE IMPLICATIONS: Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect the privacy of de-identified people allow for improved data use. Automating data-generation procedures improves the volume and timeliness of sharing data.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Centers for Disease Control and Prevention, U.S. / Confidencialidad / Anonimización de la Información / COVID-19 Tipo de estudio: Prognostic_studies / Screening_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Public Health Rep Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
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XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Centers for Disease Control and Prevention, U.S. / Confidencialidad / Anonimización de la Información / COVID-19 Tipo de estudio: Prognostic_studies / Screening_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Public Health Rep Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos