Literature DB >> 28722190

Estimating population effects of vaccination using large, routinely collected data.

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.
Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Entities:  

Keywords:  causal inference; dependent happenings; herd immunity; indirect effects; potential outcome; surveillance; vaccination

Mesh:

Substances:

Year:  2017        PMID: 28722190      PMCID: PMC5735016          DOI: 10.1002/sim.7392

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  18 in total

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4.  Theoretical Basis of the Test-Negative Study Design for Assessment of Influenza Vaccine Effectiveness.

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5.  Randomization inference for treatment effects on a binary outcome.

Authors:  Joseph Rigdon; Michael G Hudgens
Journal:  Stat Med       Date:  2014-12-04       Impact factor: 2.373

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Authors:  Lan Liu; Michael G Hudgens
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8.  Causal inference in infectious diseases.

Authors:  M E Halloran; C J Struchiner
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9.  Rotavirus vaccine effectiveness in low-income settings: An evaluation of the test-negative design.

Authors:  Lauren M Schwartz; M Elizabeth Halloran; Ali Rowhani-Rahbar; Kathleen M Neuzil; John C Victor
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10.  The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement.

Authors:  Eric I Benchimol; Liam Smeeth; Astrid Guttmann; Katie Harron; David Moher; Irene Petersen; Henrik T Sørensen; Erik von Elm; Sinéad M Langan
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2.  Toward evaluation of disseminated effects of medications for opioid use disorder within provider-based clusters using routinely-collected health data.

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Journal:  Stat Med       Date:  2022-06-08       Impact factor: 2.497

3.  Estimating Population-Level Effects of the Acellular Pertussis Vaccine Using Routinely Collected Immunization Data.

Authors:  Madhura S Rane; M Elizabeth Halloran
Journal:  Clin Infect Dis       Date:  2021-12-06       Impact factor: 9.079

4.  Challenges of evaluating and modelling vaccination in emerging infectious diseases.

Authors:  Zachary J Madewell; Natalie E Dean; Jesse A Berlin; Paul M Coplan; Kourtney J Davis; Claudio J Struchiner; M Elizabeth Halloran
Journal:  Epidemics       Date:  2021-10-05       Impact factor: 5.324

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