Nonlinear Trend Model for Vaccination Coverage in State and Local Areas, National Immunization Survey (NIS) 2000-2006

Learning Objectives for this Presentation:
By the end of the presentation participants will be able to:
1. Learn a method to model and predict trends in vaccination coverage.
2. Apply the approach to predict coverage in selected state and local areas.

Background:
The National Immunization Survey (NIS) has provided vaccination coverage estimates for children aged 19-35 months since 1995. However, prediction of vaccination coverage levels has not been investigated.

Objectives:
Describe a non-linear trend model method for predicting vaccination coverage, and apply the method to forecast 4:3:1:3:3 series coverage in near future.

Methods:
A logistic growth curve model method is adopted to predict vaccination coverage. SAS NLIN procedure (v9) is used to produce least squares parameter estimates of the model.

Results:
The predicted 4:3:1:3:3 coverage estimates with 95% confidence interval for 2000 to 2010 were obtained for Massachusetts, Delaware, and City of Chicago. The predicted coverage increases from 2000 through 2010 with logistic growth pattern. The models were fitted with F-value = 1527, 2893, 2257 respectively, and all 3 P-values < 0.0001. The least square estimates of the parameters are close to being unbiased, normally distributed, and minimum variance.

Conclusions:
By year 2010, the predicted 4:3:1:3:3 vaccination coverage for Massachusetts and Delaware will reach and exceed 90%, and the predicted 4:3:1:3:3 vaccination coverage for the City of Chicago will be close to 90%. From 2000 to 2006, the crude coverage estimates are closely around the predicting curve. This method can be applied to other areas and for other vaccines when a short-term forecast is needed.