An approach for estimating vaccination coverage for communities using school-level data and population mobility information
Childhood vaccination data are made available at a school level in some U.S. states. These data can be geocoded and may be considered as having a high spatial resolution. However, a school only represents the destination location for the set of students who actually reside and interact within some larger areal region, creating a spatial mismatch. Public school districts are often used to represent these regions, but fail to account for private schools and school of choice programs. We offer a new approach for estimating childhood vaccination coverage rates at a community level by integrating school level data with population commuting information. The resulting mobility-adjusted vaccine coverage estimates resolve the spatial mismatch problem and are more aligned with the geographic scale at which public health policies are implemented. We illustrate the utility of our approach using a case study on diphtheria, tetanus, and pertussis (DTP) vaccination coverage for kindergarten students in California. The modeled community-level DTP coverage estimates yield a statewide coverage of 92.37%, which is highly similar to the 92.44% coverage rate calculated from the original school-level data.
Copyright © 2016, ScienceDirect.
Delamater PL, Leslie TF, Yang YT, Jacobsen KH. An approach for estimating vaccination coverage for communities using school-level data and population mobility information. Applied Geography. 2016 June; 71: 123–132.