LabCompass

Shaun J. Grannis

Medicine · Indiana University

OpenAlex ORCID
Data-Driven Disease SurveillanceElectronic Health Records SystemsData Quality and ManagementSARS-CoV-2 and COVID-19 ResearchVaccine Coverage and Hesitancy

Publications

306

Citations

7,179

Est. group size

—

Recurring co-author estimate

Active years

25

Publishing since 2002

Research summary
AI-generated

Shaun J. Grannis conducts research at the intersection of medicine and health informatics, focusing on how electronic health record data can be linked and used for large-scale disease surveillance. A major strand of the work evaluates how well vaccines (for COVID-19 and influenza) protect against hospital, emergency, and urgent care visits, using data drawn from multi-institution health networks. Another strand develops methods for privacy-preserving record linkage, joining patient data across different institutions without exposing personal identities.

Vaccine effectiveness studies (COVID-19 and influenza)Privacy-preserving record linkage across datasetsElectronic health records and learning health systemsData-driven disease surveillanceData quality and governance

Publication activity has been steady-to-growing over the past decade, averaging around 22 papers per year over the last five years with a peak in 2023.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence
Publications per year over the last 10 years — averaging 21.6/year recently
2017: 19 publications172018: 10 publications182019: 19 publications192020: 22 publications202021: 22 publications212022: 27 publications222023: 29 publications29232024: 18 publications242025: 21 publications252026: 13 publications26
Recent publications
Publishes in
  • MMWR Morbidity and Mortality Weekly Report×19
  • AMIA×14
  • Journal of the American Medical Informatics Association×11
  • Open Forum Infectious Diseases×9
  • JAMA Network Open×6

This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 11, 2026.

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