Estimating population effects of vaccination using large, routinely collected data. (19th July 2017)

• Record Type: Journal Article
• Authors: Halloran, M Elizabeth; Hudgens, Michael G.
• Other Names: Gezmu Misrak guestEditor.; Qin Jing guestEditor.
• Is Part Of: Statistics in medicine. Volume 37:Number 2(2018)
• Page Start: 294
• Page End: 301
• Publication Date: 2017-07-19
• Subjects: causal inference -- dependent happenings -- herd immunity -- indirect effects -- potential outcome -- surveillance -- vaccination; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.7392
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : Vaccination in populations can have several kinds of effects. Establishing that vaccination produces population‐level effects beyond the direct effects in the vaccinated individuals can have important consequences for public health policy. Formal methods have been developed for study designs and analysis that can estimate the different effects of vaccination. However, implementing field studies to evaluate the different effects of vaccination can be expensive, of limited generalizability, or unethical. It would be advantageous to use routinely collected data to estimate the different effects of vaccination. We consider how different types of data are needed to estimate different effects of vaccination. The examples include rotavirus vaccination of young children, influenza vaccination of elderly adults, and a targeted influenza vaccination campaign in schools. Directions for future research are discussed. Copyright © 2017 John Wiley & Sons, Ltd.