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Estimating population effects of vaccination using large, routinely collected data
Author(s) -
Halloran M Elizabeth,
Hudgens Michael G.
Publication year - 2017
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.7392
Subject(s) - vaccination , generalizability theory , environmental health , medicine , public health , population , computer science , demography , immunology , statistics , mathematics , nursing , sociology
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.