Loading…
Estimating county-level vaccination coverage using small area estimation with the National Immunization Survey-Child
•Produce estimates of county-level vaccination coverage for children up to age two.•Combine NIS-Child direct survey estimates with model-based estimates.•Provide more granular geographic estimates for policymaking and planning.•Models often have strong goodness-of-fit, reflecting predictive power of...
Saved in:
Published in: | Vaccine 2024-01, Vol.42 (3), p.418-425 |
---|---|
Main Authors: | , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | •Produce estimates of county-level vaccination coverage for children up to age two.•Combine NIS-Child direct survey estimates with model-based estimates.•Provide more granular geographic estimates for policymaking and planning.•Models often have strong goodness-of-fit, reflecting predictive power of covariates.•Selected model covariates often reflect measures of barriers to vaccination.
The National Immunization Survey-Child (NIS-Child) provides annual vaccination coverage estimates in the United States for children aged 19 through 35 months, nationally, for each state, and for select local areas and territories. There is a need for vaccination coverage estimates for smaller geographic areas to support local authority planning and identify counties with potentially low vaccination coverage for possible further intervention. We describe small area estimation methods using 2008-2018 NIS-Child data to generate county-level estimates for children up to two years of age born 2007-2011 and 2012-2016. We applied an empirical best linear unbiased prediction method to combine direct estimates of vaccination coverage with model-based prediction using county-level predictors regarding health and demographic characteristics. We review the predictors commonly selected for the small area models and note multiple predictors related to barriers to vaccination. |
---|---|
ISSN: | 0264-410X 1873-2518 |
DOI: | 10.1016/j.vaccine.2023.12.046 |