The Research Centers in Minority Institutions (RCMI) Translational Research Network: Building and Sustaining Capacity for Multi-Site Basic Biomedical, Clinical and Behavioral Research.

The Research Centers in Minority Institutions (RCMI) program was established by the US Congress to support the development of biomedical research infrastructure at minority-serving institutions granting doctoral degrees in the health professions or in a health-related science. RCMI institutions also conduct research on diseases that disproportionately affect racial and ethnic minorities (ie, African Americans/Blacks, American Indians and Alaska Natives, Hispanics, Native Hawaiians and Other Pacific Islanders), those of low socioeconomic status, and rural persons. Quantitative metrics, including the numbers of doctoral science degrees granted to underrepresented students, NIH peer-reviewed research funding, peer-reviewed publications, and numbers of racial and ethnic minorities participating in sponsored research, demonstrate that RCMI grantee institutions have made substantial progress toward the intent of the Congressional legislation, as well as the NIH/NIMHD-linked goals of addressing workforce diversity and health disparities. Despite this progress, nationally, many challenges remain, including persistent disparities in research and career development awards to minority investigators. The continuing underrepresentation of minority investigators in NIH-sponsored research across multiple disease areas is of concern, in the face of unrelenting national health inequities. With the collaborative network support by the RCMI Translational Research Network (RTRN), the RCMI community is uniquely positioned to address these challenges through its community engagement and strategic partnerships with non-RCMI institutions. Funding agencies can play an important role by incentivizing such collaborations, and incorporating metrics for research funding that address underrepresented populations, workforce diversity and health equity.

Community health status indicators: adding a geospatial component.

An Internet mapping application is being introduced in conjunction with the release of the second version of the Community Health Status Indicators (CHSI) Report. The CHSI Geographic Information Systems (GIS) Analyst is an easy-to-use Web-based mapping application that provides new opportunities for the visualization, exploration, and understanding of the indicators. Indicators can be mapped and compared visually to other areas, including peer counties and neighboring counties. The Web site is accessible from a link on the CHSI Report Web site or directly from an Internet Web browser. In this paper, we discuss the conceptualization and implementation of this public health mapping application.

County-Level Vulnerability Assessment for Rapid Dissemination of HIV or HCV Infections Among Persons Who Inject Drugs, United States.

OBJECTIVE: A recent HIV outbreak in a rural network of persons who inject drugs (PWID) underscored the intersection of the expanding epidemics of opioid abuse, unsterile injection drug use (IDU), and associated increases in hepatitis C virus (HCV) infections. We sought to identify US communities potentially vulnerable to rapid spread of HIV, if introduced, and new or continuing high rates of HCV infections among PWID. DESIGN: We conducted a multistep analysis to identify indicator variables highly associated with IDU. We then used these indicator values to calculate vulnerability scores for each county to identify which were most vulnerable. METHODS: We used confirmed cases of acute HCV infection reported to the National Notifiable Disease Surveillance System, 2012-2013, as a proxy outcome for IDU, and 15 county-level indicators available nationally in Poisson regression models to identify indicators associated with higher county acute HCV infection rates. Using these indicators, we calculated composite index scores to rank each county's vulnerability. RESULTS: A parsimonious set of 6 indicators were associated with acute HCV infection rates (proxy for IDU): drug-overdose deaths, prescription opioid sales, per capita income, white, non-Hispanic race/ethnicity, unemployment, and buprenorphine prescribing potential by waiver. Based on these indicators, we identified 220 counties in 26 states within the 95th percentile of most vulnerable. CONCLUSIONS: Our analysis highlights US counties potentially vulnerable to HIV and HCV infections among PWID in the context of the national opioid epidemic. State and local health departments will need to further explore vulnerability and target interventions to prevent transmission.