M
M. Elizabeth Halloran
Researcher at Fred Hutchinson Cancer Research Center
Publications - 270
Citations - 19557
M. Elizabeth Halloran is an academic researcher from Fred Hutchinson Cancer Research Center. The author has contributed to research in topics: Vaccination & Population. The author has an hindex of 56, co-authored 248 publications receiving 15685 citations. Previous affiliations of M. Elizabeth Halloran include University of Washington & Washington University in St. Louis.
Papers
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Journal ArticleDOI
The Effect of Disease Prior to an Outbreak on Estimates of Vaccine Efficacy Following the Outbreak
TL;DR: This paper examines the effects of including and excluding pre-outbreak disease cases from the calculation of vaccine efficacy based on the cumulative incidence at the end of an outbreak, using a five-stage model.
Journal ArticleDOI
Bayesian estimation of vaccine efficacy.
Haitao Chu,M. Elizabeth Halloran +1 more
TL;DR: Bayesian estimation of protective vaccine efficacy, its highest probability density credible set, and the vaccine efficacy acceptability curve through Markov chain Monte Carlo (MCMC) methods are presented.
Journal ArticleDOI
Meningococcal carriage within households in the African meningitis belt: A longitudinal pilot study
Nicole E. Basta,Abdoulaye Berthe,Mahamadou Keita,Uma Onwuchekwa,Boubou Tamboura,Awa Traore,Musa Hassan-King,Olivier Manigart,Olivier Manigart,Maria Claudia Nascimento,James M. Stuart,Caroline Trotter,Jayne Blake,Anthony D. Carr,Stephen J. Gray,Lynne S. Newbold,Yangqing Deng,Julian Wolfson,M. Elizabeth Halloran,M. Elizabeth Halloran,Brian Greenwood,Ray Borrow,Samba O. Sow +22 more
TL;DR: The feasibility of conducting a longitudinal, household-based study of meningococcal carriage in the African meningitis belt was demonstrated and it was demonstrated that the carriage prevalence was 5% during the cross-sectional screening visit.
Journal ArticleDOI
Modeling Competing Infectious Pathogens from a Bayesian Perspective: Application to Influenza Studies with Incomplete Laboratory Results.
Yang Yang,M. Elizabeth Halloran,M. Elizabeth Halloran,Michael J. Daniels,Ira M. Longini,Ira M. Longini,Donald S. Burke,Derek A. T. Cummings +7 more
TL;DR: Using the proposed Bayesian competing-risk model for multiple cocirculating pathogens for inference on transmissibility and intervention efficacies, it is found that a nonpharmaceutical intervention is marginally protective against transmission of influenza A in a study conducted in elementary schools.
Book ChapterDOI
Binomial and Stochastic Transmission Models
TL;DR: This chapter and the next are introduced transmission models necessary for estimating and understanding the effects of vaccination, including the binomial model and the chain binomialmodel.