Literature DB >> 25637432

Geospatial patterns in influenza vaccination: evidence from uninsured and publicly insured children in North Carolina.

Justin G Trogdon1, Thomas Ahn2.   

Abstract

BACKGROUND: The purpose of this study was to explore geospatial patterns in influenza vaccination.
METHODS: We conducted an ecological analysis of publicly funded influenza vaccinations at the ZIP code tabulation area (ZCTA) level using secondary data for publicly funded influenza vaccinations among eligible school-aged children (age range, 5-17 years) for the 2010-2011 and 2011-2012 influenza seasons from the North Carolina Immunization Registry (NCIR). NCIR data were merged by ZCTA with other publicly available data. We tested for spatial autocorrelation in unadjusted influenza vaccination rates using choropleth maps and Moran's I. We estimated nonspatial and spatial negative binomial models with spatially correlated random effects adjusted for demographic, economic, and health care variables. The study was conducted at the University of North Carolina at Chapel Hill in the spring of 2014.
RESULTS: The NCIR demonstrated spatial autocorrelation in publicly funded influenza vaccinations among uninsured and means-tested, publicly insured school-aged children; ZCTAs tended to have influenza vaccination rates that were similar to their neighbors. This result was partially explained by included ZCTA characteristics, but not wholly.
CONCLUSION: To the extent that the geospatial clustering of vaccination rates is the result of social influences, targeting interventions to increase influenza vaccination among school-aged children in one area could also lead to increases in neighboring areas.
Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Influenza; Spatial analysis; Vaccination

Mesh:

Substances:

Year:  2015        PMID: 25637432     DOI: 10.1016/j.ajic.2014.11.022

Source DB:  PubMed          Journal:  Am J Infect Control        ISSN: 0196-6553            Impact factor:   2.918


  2 in total

1.  Predicting Areas with High Concentration of the Long-Term Uninsured and Their Association with Emergency Department Usage by Uninsured Patients in South Carolina.

Authors:  Khoa Truong; Julie Summey Bedi; Lingling Zhang; Brooke Draghi; Lu Shi
Journal:  Healthcare (Basel)       Date:  2022-04-21

Review 2.  Countering vaccine hesitancy through immunization information systems, a narrative review.

Authors:  Vincenza Gianfredi; Massimo Moretti; Pier Luigi Lopalco
Journal:  Hum Vaccin Immunother       Date:  2019-06-21       Impact factor: 3.452

  2 in total

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