Estimating county-level vaccination coverage using small area estimation with the National Immunization Survey-Child

Area of Science:

• Public Health
• Biostatistics
• Epidemiology

Background:

• The National Immunization Survey-Child (NIS-Child) offers vaccination coverage estimates for children aged 19-35 months at national and state levels.
• There is a critical need for granular, county-level vaccination coverage data to support local public health planning and targeted interventions.
• Identifying geographic areas with potentially low vaccination coverage is essential for effective public health strategies.

Approach:

• This study employed small area estimation methods using 2008-2018 NIS-Child data.
• An empirical best linear unbiased prediction (EBLUP) approach was used, combining direct survey estimates with model-based predictions.
• County-level health and demographic characteristics were utilized as predictors in the statistical models.

Key Points:

• The methods generated county-level vaccination coverage estimates for children born between 2007-2011 and 2012-2016.
• Analysis identified common predictors for small area models, many of which relate to known barriers to vaccination.
• This approach allows for more precise identification of areas with suboptimal vaccination rates.

Conclusions:

• Small area estimation provides valuable county-level vaccination coverage data, enhancing public health surveillance.
• The findings support the use of demographic and health predictors to model vaccination coverage at a granular level.
• This methodology can aid local authorities in planning interventions and improving childhood immunization rates in underserved areas.