Rural Health Mapping Tool
Causes of Death
The mortality rate for counties with 10 to 19 deaths during the time period is considered unreliable and therefore not presented. The mortality rate for counties with fewer than 10 deaths during the time period is suppressed.
Click on a variable in the leftmost column of the data table to see it's definition.
|Component||Score||Sub-Component||Elbert County||Colorado||United States|
|Economic - Risk||2||4.8%||10.3%||13.4%|
|Economic - Resilience||1||8.4%||5.0%||3.6%|
|Social - Risk||1||1.0||1.6||1.8|
|Social - Resilience||2||34.6||69.3||43.7|
Click here to download a Microsoft Excel file containing the data used in the Rural Health Mapping Tool.
The tables below present the data sources and definitions for the variables included in the tool. All data has been collected from publicly available data sources. CDC COVID Data Tracker and CDC AdultVaxView data will be updated regularly as new data is released by CDC. The 2013 NCHS Urban-Rural Classification Scheme is used to distinguish rural and urban counties. Additional information on the prosperity index methodology can be found on the Opioid Misuse Community Assessment Tool
This initiative is supported by the Centers for Disease Control and Prevention (CDC).
NORC at the University of Chicago conducts research and analysis that decision-makers trust. As a nonpartisan research organization and a pioneer in measuring and understanding the world, we have studied almost every aspect of the human experience and every major news event for more than eight decades. Today, we partner with government, corporate, and nonprofit clients around the world to provide the objectivity and expertise necessary to inform the critical decisions facing society.
For more information please contact:
Megan Heffernan, MPH
Research Scientist, Public Health Research, NORC at the University of Chicago
email@example.com | (301) 310-5089
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Embed table for Menifee County, KY in 2011 - 2015
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This tool allows CDC, other researchers, community organizations, local policymakers, and the public to create county-level maps illustrating the relationship between COVID-19 vaccination coverage rates and other health outcomes, socio-demographic, and economic variables across all counties of the United States. Insights derived from this tool can be used to target resources and interventions, and inform efforts, particularly in rural areas, related to vaccination coverage rates.
The base layer shows COVID-19 outcomes (including new cases, hospitalizations, and deaths), COVID-19 vaccination coverage rates, prosperity index scores, and mortality rates for leading causes of death. Darker-colored counties have higher rates. Lighter-colored counties have lower rates. You can click on “Search List of Counties” to link directly to data on a particular county, or click on it on the map.
To view state-level data, click the "County/State" drop down in the upper-left section of the screen and select "state”. To choose a specific state, select using the drop-down for “Filter by state”. The shading of the map will adjust to the quantiles for the chosen state.
Use the urban/rural drop down to limit the map to either category.
Choose variables from the left-hand column to layer county-level socio-demographic and economic 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 “Childhood Poverty Rate” will demonstrate the relationship between an individual county’s childhood poverty rate and its vaccination coverage rate.
When second-layer data has been added onto a base map, users can select “Open Correlation Graph” to see a graph that shows the correlation between the two indicators, including the correlation coefficient. Correlation coefficients are typically used to evaluate the association between two variables. These coefficients range from -1 to +1 and represent the strength of the relationship between the two variables. Values of 0 indicate no meaningful associations between the two variables. As the correlation values approach either end (-1 or +1) of the range, the association becomes stronger, where values closer to 0 indicate weaker relationships. Negative values (those less than 0) indicate decreasing or inverse relationships (as one variable increases, the other decreases), and positive values (greater than 0) demonstrate increasing relationships (as one variable increases, the other also increases). The two types of correlation coefficients used for this tool include Pearson’s correlation coefficient and Spearman’s correlation coefficient. Pearson’s correlation coefficient is used here when examining two continuous variables (numerical in scale). Spearman’s correlation coefficient is used when at least one of the variables (or possibly both) are not continuous (i.e., categorical or ordinal in nature). Pearson’s correlation coefficient is specific to evaluating the linear association between the two continuous variables, while Spearman’s correlation coefficient does not require a linear relationship, merely an increasing (or decreasing) association between the variables.
On the left-hand side of the screen, there is a drop down for “Add Map Overlay” Available map overlays include: geolocations of Native American Reservations; outline of persistent poverty counties; location of major highways; and Federally Defined Regions (e.g., Appalachia, Delta, U.S.-Mexico border region). A map overlay can also be added for HHS Regions.
A county fact sheet is available for every county in the United States. The fact sheet shows all data included in the tool for a specific county, compared to state and national averages. The fact sheet in available by clicking on the “View Details” link on the main map page for a specific county. The county fact sheet also includes a list of providers in the selected county, including pharmacies, primary care providers, National Health Service Corps sites, Federally Qualified Health Centers (FQHCs), and Rural Health Clinics.