Vaccine Coverage in the United States
BASE MAP
NIS-Child
NIS-Teen
NIS-Flu
PROVIDERS
STATES
| 21.8 |
AAAA
|
| 23.5 | AAAA |
| 27.1 | AAAA |
| 27.1 | AAAA |
1 Estimate based solely on statistical modeling rather than combined NIS data and statistical modeling
2 Standard error for this estimate exceeds 7.5 percentage points
3 HP2020 target has been met for this variable
4 HP2020 target has not been met for this variable
Vaccination coverage rates are known to have a geographic component, with trends visible at the state and county level. The purpose of this tool is to allow the user to visualize vaccination coverage estimates while simultaneously seeing underlying demographic characteristics. The tool is designed so that the user can observe trends and relationships that may otherwise be hidden.
Vaccination coverage rates were estimated using a small area estimation methodology, combining direct survey estimates from the NIS with model based predictions incorporating variables related to vaccination coverage rates. Estimates were produced for children by age 24 months using NIS-Child, children age 13 to 17 years using NIS-Teen, and children age 6 months to 17 years using NIS-Flu.
For counties with sufficient NIS sample size, the small area estimation approach generated the county-level vaccination coverage rates using a weighted average of the direct survey estimate for the county and the model-based prediction of the county’s vaccination coverage rate. The direct survey estimate for a county is obtained from the NIS solely based on sample from the county. The model-based prediction is obtained by creating a linear statistical model relating the NIS direct survey estimates of vaccination coverage for large counties and county groupings to various explanatory variables. The direct survey estimate and the model-based prediction for a given county are combined in a weighted average, where the weights given to these two components are proportional to their estimated precision (the greater the precision for one component relative to the precision of the other component, the greater the weight assigned to that component).
For counties that did not have sufficient NIS sample size, the model-based prediction was used alone to estimate the vaccination coverage rate. Data from CDC’s Vaccine Tracking System (VTrckS) was provided to NORC by the National Center for Immunization and Respiratory Diseases and includes a normalized county-level measure of ordered doses from the Vaccines For Children program and other state-level programs.
Estimates for counties were aggregated to produce public health district estimates. Counties and districts are colored based on the county quantiles for each vaccine coverage variable and time period.
The interactive tool was created in JavaScript using the Leaflet library. Data were processed using SAS and converted from shapefile to TopoJSON using R.
The tables below present the data sources and definitions for the variables included in the tool.
NORC at the University of Chicago is an objective, non-partisan research institution that delivers reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions. Since 1941, NORC has conducted groundbreaking studies, created and applied innovative methods and tools, and advanced principles of scientific integrity and collaboration. Today, government, corporate, and nonprofit clients around the world partner with NORC to transform increasingly complex information into useful knowledge.
For more information please contact:
Eric Young
NORC Senior External Affairs Manager
young-eric@norc.org
(301) 634-9536
<iframe width="975" height="570" src="https://opioidmisusetool.norc.org/embed/map/map.html" frameborder="1" allowfullscreen></iframe>
Embed table for Menifee County, KY in 2011 - 2015
<iframe width="975" height="630" src="https://opioidmisusetool.norc.org\embed\D\T2\table21165.html" frameborder="1" allowfullscreen> </iframe>
This tool allows CDC and other researchers to create county-level maps illustrating the relationship between community and population demographics and vaccination coverage rates at multiple geographic levels in the United States. Insights derived from this tool can be used to target resources and interventions, and inform media coverage related to vaccination coverage rates.
The base layer shows vaccination coverage rates for the NIS-Child, NIS-Teen, and NIS-Flu surveys at two points in time. Darker-colored counties (or county equivalent) have higher vaccination coverage rates. Lighter-colored counties have lower vaccination coverage rates. You can use the List of Counties to link directly to data on a particular county, or click on it on the map.
Click on the dot in the “timeframe” slider in the upper-right section of the screen to change the years represented by the vaccination coverage layer.
To view district-level data, click the "county/district" drop down in the upper-right section of the screen and select "district".
Public health district information was identified through information collected from state department websites or through conversations with state health departments for 26 states (AL, AK, AR, FL, GA, ID, IL, IN, IW, KS, KY, LA, ME, MS, NE, NM, NY, NC, ND, OK, PA, TN, TX, UT, VA, and WI) . Sixteen states reported that they did not have official health districts but reported a county grouping that would work for use in the mapping tool (CA, CO, HI, MD, MI, MN, MO, MT, NV, NH, NJ, RI, SC, SD, WA, and WI). Only seven states declined to provide health district information (AZ, DE, MA, OH, OR, VT, WY). One state (CT) has public health districts that do not align with county boundaries, and thus health district-level vaccination coverage estimates were not produced. Not all states use the terminology “public health district”. Some states refer to this geographic level of organization as health regions (AK, IA, IL, MS, NC, OK, TN, TX, and WI), health units (AR, ND), health councils (FL), or parish health units (LA).
Use the urban/rural drop down to limit the map to either category and permit their comparison.
Choose variables from the left-hand column to layer county-level economic and demographic data on top of the baseline vaccination coverage data. By showing the variables as translucent circles of varying sizes, the tool allows users to clearly see how a given measure relates to the baseline vaccination coverage rate. For example, choosing “Persons Under 17 in Poverty” will demonstrate the relationship between an individual county’s poverty rate and its vaccination coverage rate.
Selecting providers on the left hand column will map them as a layer above the base vaccination coverage rate. It may be necessary to zoom in to an individual county to show the actual geocoded locations.
On the right hand side of the screen, there is a drop down for “Map overlays.” Currently, the tool includes a contextual overlay that shows the geolocation of Native American Reservations, Persistent Poverty Counties, and Major Highways. Map overlays can be added to the map while also selecting a county-level sociodemographic or economic overlay.