| Literature DB >> 28722190 |
M Elizabeth Halloran1,2, Michael G Hudgens3.
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.Entities:
Keywords: causal inference; dependent happenings; herd immunity; indirect effects; potential outcome; surveillance; vaccination
Mesh:
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Year: 2017 PMID: 28722190 PMCID: PMC5735016 DOI: 10.1002/sim.7392
Source DB: PubMed Journal: Stat Med ISSN: 0277-6715 Impact factor: 2.373