Utilizing virus genomic surveillance to predict vaccine effectiveness.

Saved in:
Bibliographic Details
Title: Utilizing virus genomic surveillance to predict vaccine effectiveness.
Authors: Kwon J; Department of Epidemiology of Microbial Diseases, Yale School of Public Health; New Haven, CT, USA.; Public Health Modeling Unit, Yale School of Public Health; New Haven, CT, USA., Li K; Department of Epidemiology of Microbial Diseases, Yale School of Public Health; New Haven, CT, USA.; Public Health Modeling Unit, Yale School of Public Health; New Haven, CT, USA., Warren JL; Public Health Modeling Unit, Yale School of Public Health; New Haven, CT, USA.; Department of Biostatistics, Yale School of Public Health; New Haven, CT, USA., Pandya S; Department of Laboratory Medicine, Yale School of Medicine; New Haven, CT, USA.; Yale School of Medicine Biorepository, Yale University; New Haven, CT, USA., Hahn AM; Department of Epidemiology of Microbial Diseases, Yale School of Public Health; New Haven, CT, USA.; Department of Microbiology and Immunology, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity; Melbourne, VIC, Australia., Pitzer VE; Department of Epidemiology of Microbial Diseases, Yale School of Public Health; New Haven, CT, USA.; Public Health Modeling Unit, Yale School of Public Health; New Haven, CT, USA., Weinberger DM; Department of Epidemiology of Microbial Diseases, Yale School of Public Health; New Haven, CT, USA.; Public Health Modeling Unit, Yale School of Public Health; New Haven, CT, USA., Grubaugh ND; Department of Epidemiology of Microbial Diseases, Yale School of Public Health; New Haven, CT, USA.; Public Health Modeling Unit, Yale School of Public Health; New Haven, CT, USA.; Department of Ecology and Evolutionary Biology, Yale University; New Haven, CT, USA.
Corporate Authors: Yale SARS-CoV-2 Genomic Surveillance Initiative
Source: MedRxiv : the preprint server for health sciences [medRxiv] 2025 Jun 22. Date of Electronic Publication: 2025 Jun 22.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101767986 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: medRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
DOI:10.1101/2025.06.20.25329795