Evaluation of the indirect effects of a pneumococcal vaccine in a community-randomized study

Research output: Contribution to journalArticle

Abstract

When a sufficiently high proportion of a population is immunized with a vaccine, reduction in secondary transmission of disease can confer significant protection to unimmunized population members. We propose a straightforward method to estimate the degree of this indirect effect of vaccination in the context of a community-randomized vaccine trial. A conditional logistic regression model that accounts for within-randomization unit correlation over time is described, which models risk of disease as a function of community-level covariates. The approach is applied to an example data set from a pneumococcal conjugate vaccine study, with study arm and immunization levels forming the covariates of interest for the investigation of indirect effects.

Original languageEnglish (US)
Pages (from-to)453-462
Number of pages10
JournalJournal of Biopharmaceutical Statistics
Volume16
Issue number4
DOIs
StatePublished - Aug 1 2006

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Pneumococcal Vaccines
Vaccine
Vaccines
Logistic Models
Conjugate Vaccines
Covariates
Evaluation
Random Allocation
Conditional Logistic Regression
Population
Immunization
Vaccination
Logistic Regression Model
Randomisation
Proportion
Unit
Estimate
Community
Model
Datasets

Keywords

  • Community-randomized trial
  • Indirect effects
  • Pneumococcal vaccine

ASJC Scopus subject areas

  • Pharmacology (medical)
  • Pharmacology, Toxicology and Pharmaceutics(all)

Cite this

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AU - Santosham, Mathuram

AU - Siber, G. R.

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