Click here to download a Microsoft Excel file containing the data used for the 2024 version of the Recovery Ecosystem Index (updated August 2024).

Click here to download a Microsoft Excel file containing the data used for the 2023 version of the Recovery Ecosystem Index (updated August 2023).

Click here to download a Microsoft Excel file containing the data used for the 2022 version of the Recovery Ecosystem Index (launched September 2022).

The team created this tool in JavaScript using the Leaflet library. We processed data using SAS and converted shapefiles to TopoJSONs using the sf library in R web client. The tables below describe the data sources and definitions for the base layer data and secondary overlays for the 2024 version of the Recovery Ecosystem Index.

*Note: Due to changes in data available through CDC Wonder, the 2024 update reports drug overdose mortality rates for all ages, not the population ages 15-64 as was included in the prior versions of the tool. These rates should not be compared to data from prior versions.

The Recovery Ecosystem Index provides a single numerical measure designed to reflect the strength of a county's recovery ecosystem. An overall score of 1 represents the strongest recovery ecosystem, and 5 represents the weakest. The ETSU/NORC Rural Health Equity Research Center and Fletcher Group, Inc. convened a Technical Expert Panel in 2021-2022 to support the initial development of the Recovery Ecosystem Index.

Technical Expert Panel members represented a diverse group of partners with a wide range of expertise, including Dr. Robert Ashford (Unity Recovery), Matt Boggs (Ryker Douglas), Dr. Anita Chandra (RAND Corporation), Dr. Kimberly Dash (Education Development Center), John Gale (University of Southern Maine, Cutler Institute), Peter Gaumond (Office of National Drug Control Policy), Carolyn Hardin (National Association of Drug Court Professionals), Christopher Hart (Unity Recovery), Sierra Helfrich (Centers for Disease Control and Prevention), Patrick Hibbard (JEAP Training Institute at Oregon Social Learning Institute), Pam Johnson (Fahe), Dr. John Kelly (Harvard Medical School, Recovery Research Institute), Dr. Ron Manderscheid (National Association for Rural Mental Health, National Association of County Behavioral Health and Developmental Disability Directors), and Robin Phillips (National Rural Transit Assistance Program).

The index aims to measure the strength of rural county-level recovery ecosystems throughout the United States and provide data to support community planning, programming, and technical assistance to strengthen them. The index consists of two components that impact the strength of a recovery ecosystem: Substance Use Disorder (SUD) Treatment and Continuum of SUD Support.

The Substance Use Disorder Treatment component includes substance use treatment facilities per capita, the average distance to the nearest medication-assisted therapy provider (miles), and mental health providers per capita.

The Continuum of SUD Support component includes the average distance to the nearest syringe services programs (miles), Narcotics Anonymous or SMART Recovery Meetings per capita, the presence of a drug-free communities coalition, the presence of an adult drug court, the state substance use disorder policy environment score, and social associations per 10k.

The team first conducted a literature review to determine the key components of a recovery ecosystem. Based on this review and input from the technical expert panel, we developed a list of all potential indicators and prioritized them. To be selected, the indicator needed to have publicly available data for all counties in the U.S.

The table below describes each of the data sources and definitions for the Policy Environment Score.

Variable	Data Source	Definition	Response Options
Parole Violation Protection	Prescription Drug Abuse Policy System (2023)	The law provides protection from probation or parole violations.	1 = Yes 0 = No 0 = No Data
Good Samaritan	Prescription Drug Abuse Policy System (2023)	The jurisdiction has a drug overdose Good Samaritan Law.	1 = Yes 0 = No 0 = No Data
Overdose Reporting and Sentencing	Prescription Drug Abuse Policy System (2023)	Reporting an overdose is considered a mitigating factor in sentencing.	1 = Yes 0 = No 0 = No Data
Commercial Required Coverage of Medications for Opioid Use Disorder	Prescription Drug Abuse Policy System (2020)	The state requires commercial insurers to provide coverage for medications for opioid use disorder.	1 = Yes 0 = No 0 = No Data
Behavioral Health Coverage of Medications for Opioid Use Disorder	Prescription Drug Abuse Policy System (2020)	The state Medicaid plan includes coverage for behavioral health supports for medications for opioid use disorder.	1 = Yes 0 = No 0 = No Data
Medications for Opioid Use Disorder Provision	Prescription Drug Abuse Policy System (2020)	The state has an approved Medicaid State Plan Amendment to facilitate the provision of medications for opioid use disorder.	1 = Yes 0 = No 0 = No Data
Licensed Substance Use Disorder Programs	Prescription Drug Abuse Policy System (2020)	Licensed substance use disorder programs are required to facilitate access to medications for opioid use disorder programs.	1 = Yes 0 = No 0 = No Data
Syringe Service Programs	Prescription Drug Abuse Policy System (2021)	State law allows for the operation of syringe service programs.	1 = Yes 0 = No 0 = No Data
Syringe Posession	Prescription Drug Abuse Policy System (2021)	State law allows syringe service program participants to possess syringes.	1 = Yes 0 = No 0 = No Data

*MOUD = Medications for opioid use disorder

In 2023 and 2024, the team solicited feedback on the Recovery Ecosystem Index Mapping Tool from key users of the tool. Based on the information provided, we decided to remove several indicators from the 2023 version, including Number of Providers licensed to Administer Buprenorphine per Capita, Number of Residential Treatment Facilities per Capita, Vehicle Availability, Severe Housing Cost Burden, and Broadband Access. The last three indicators were included in the Infrastructure and Social subcomponent, which we removed from the 2024 version of the Recovery Ecosystem Index. Data for these indicators are still available, but it no longer contributes to the overall Recovery Ecosystem Index score. We decided these indicators were not accurately representing the topics we intended to incorporate into the Recovery Ecosystem Index, such as access to transportation and recovery housing. We will continue to explore potential future indicators for these concepts in future versions of the Recovery Ecosystem Index.

The Recovery Ecosystem Index is calculated for each county in the United States using standardized values of 9 indicators belonging to one of two component classes associated with the recovery ecosystem. The components represented are Substance Use Disorder (SUD) Treatment and Continuum of SUD Support.

First, each indicator, also known as a subcomponent, was scaled to have a mean of 0 and a standard deviation of 1. This is referred to as the standardized subcomponent value and allows each subcomponent to affect the final index score equally.

At the component level, the subcomponent standardized values within the component are summed to create a component value. Then a clustering algorithm grouped all of the counties into five homogenous groups according to the sum of the standardized values thus creating a score for each county for each component.

Finally, all subcomponent values are summed for each county to create the recovery ecosystem value. The counties are then grouped into five classes with one representing the strongest recovery ecosystem and five representing the weakest ecosystem. This one-to-five score is the final Recovery Ecosystem Index score.

There are some limitations that should be considered when utilizing the Recovery Ecosystem Index. First, some indicators are intended to serve as proxies for aspects of a recovery ecosystem, but are not perfect indicators. It is often difficult to obtain valid data that is reported consistently at the county-level. While the index is designed to be as comprehensive as possible based on available data, the index may not assess all aspects of a strong recovery ecosystem. Additionally, the data represent a range of time periods. Therefore, the data provides a general sense of the overall recovery ecosystem, but will not capture more recent changes.

The term “recovery ecosystem” describes the community-level factors that support individuals in recovery from substance use disorder. This tool aims to help community organizations, policymakers, researchers, and the general public understand the recovery ecosystem strengths in their community and where additional resources and interventions are most needed.

Click here for an Action Guide on how to apply our tool to your work.

You can choose the Recovery Ecosystem Index score or drug overdose mortality rates in the left navigation column as the map’s base layer. The two Recovery Ecosystem Index components, Substance Use Disorder (SUD) Treatment and Continuum of SUD Support, consist of nine indicators. Both component scores and individual indicator data can also be used as a base map. Drug overdose mortality includes both drug and opioid overdose mortality rates for 2013-2027 and 2018-2022. Details on this data are described in more detail on the “Methodology & Data” tab at the bottom of the screen.

Overlay data is available below the base map options in the left navigation corner. In addition to the Recovery Ecosystem Index score, components scores, indicators, and drug overdose mortality rates, socio-demographic, economic, and housing and infrastructure data are provided. This feature allows you to layer secondary data over the base map. For example, the Substance Use Disorder Treatment base map could be overlayed with the opioid overdose mortality or poverty rates. The tool illustrates how a given measure relates to the base map data by showing the secondary data as translucent circles of varying sizes.

When overlay data has been added onto a base map, you can select “Open Correlation Graph” at the top of the left navigation column to see a graph of the relationship and correlation coefficient of the base layer and overlay data. 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, whereas 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 and Spearman’s correlation coefficients.

• Pearson’s correlation coefficient – Pearson’s correlation coefficient is used here when examining two continuous variables (i.e., numerical in scale). It is specific to evaluating the linear association between the two continuous variables. Pearson’s correlation coefficient ranges from -1 to +1 and describes the linear (straight line) relationship between the chosen variables. A value of 0 describes no linear relationship, while -1 represents a perfectly inverse (decreasing) linear relationship, and +1 represents a perfect (increasing) linear relationship.
• Spearman’s correlation coefficient – Spearman’s correlation coefficient is used when at least one of the variables (or both) is not continuous (e.g., categorical or ordinal). It does not require a linear relationship, merely an increasing (or decreasing) association between the variables. Spearman’s correlation coefficient ranges from -1 to +1 and describes the general relationship (not necessarily linear) between the chosen variables. A value of 0 describes no relationship between the two variables, while a -1 represents an inverse (decreasing) relationship, and +1 represents an increasing relationship.

Additional map context that can be added to the map include the geolocations of Native American Reservations, the outline of persistent poverty counties, the location of major highways, and Federally Defined Regions (e.g., Appalachia, Delta, and the U.S.-Mexico border region).

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.

To view your county’s fact sheet, search for your county in the left navigation column or click on your county on the map and select “View Details.” Fact sheets provide the county’s Recovery Ecosystem Index and component scores, indicator data, population, urban/rural designation, drug overdose mortality, and socio-demographic, economic, and housing and infrastructure data. Data tables include county, state, and national data as data benchmarks.

The Recovery Ecosystem Index (REI) was developed with support from a Technical Expert Panel (TEP) convened by the ETSU/NORC Rural Health Equity Research Center (RHERC) and Fletcher Group, Inc. TEP members represented a diverse group of stakeholders with a wide range of expertise. The TEP included: Dr. Robert Ashford (Unity Recovery), Matt Boggs (Ryker Douglas), Dr. Anita Chandra (RAND Corporation), Dr. Kimberly Dash (Education Development Center), John Gale (University of Southern Maine, Cutler Institute), Peter Gaumond (Office of National Drug Control Policy), Carolyn Hardin (National Association of Drug Court Professionals), Christopher Hart (Unity Recovery), Sierra Helfrich (Centers for Disease Control and Prevention), Patrick Hibbard (JEAP Training Institute at Oregon Social Learning Institute), Pam Johnson (FAHE), Dr. John Kelly (Harvard Medical School, Recovery Research Institute), Dr. Ron Manderscheid (National Association for Rural Mental Health, National Association of County Behavioral Health and Developmental Disability Directors), and Robin Phillips (National Rural Transit Assistance Program).

The Recovery Ecosystem Index provides a single numerical measure designed to reflect the strength of the recovery ecosystem of a county. For the overall Recovery Ecosystem Index score, 1 represents the strongest and 5 represents the weakest recovery ecosystem.

The index was designed to measure the strength of rural county-level recovery ecosystems, and provide data to support community planning, programming and technical assistance designed to strengthen recovery ecosystems throughout the rural United States. The index is broken down into three components that impact the strength of a recovery ecosystem: Substance Use Disorder (SUD) Treatment; Continuum of SUD Support; and Infrastructure and Social.

The SUD Treatment component includes the number of substance use treatment facilities per capita, number of providers licensed to administer buprenorphine per capita, average distance to nearest medication-assisted treatment (MAT) provider, and the number of mental health providers per capita.

The Continuum of SUD Support component includes the number of residential treatment facilities per capita, average distance to nearest syringe-service program (SSP), number of Narcotics Anonymous (NA) or Self-Management and Recovery Training (SMART) meetings per Capita, drug court presence, Drug-Free Communities Coalition grant presence, and policy environment score.

The Infrastructure and Social component includes vehicle availability, severe housing cost burden, broadband access, and social associations per capita.

To select the indicators, we first conducted a literature review to determine the key components of a recovery ecosystem. We developed a list of all potential indicators based on this review and input from the TEP. We then prioritized a list of indicators based on TEP feedback, and ultimately included the following list of indicators. In order to be selected, the indicator had to have publicly available data for all counties in the U.S.

Component	Indicator	Data Source	Definition
SUD Treatment	Number of Substance Use Treatment Facilities Per Capita	SAMHSA (N-SSATS Data) (As of February 2022)	Number of substance use treatment facilities per 10,000 residents
	Substance Use Disorder (SUD) Treatment score	See Recovery Ecosystem Index page	Substance Use Disorder (SUD) Treatment score
	Continuum of SUD Support score	See Recovery Ecosystem Index page	Continuum of SUD Support score
	Infrastructure and Social Factors score	See Recovery Ecosystem Index page	Infrastrucutre and Social Factors score