National HIV Prevention Conference | 2015
Issue: Epidemic and economic models for the United States can answer complex questions in the United States’ HIV epidemic. Yet if based solely on national data and perspectives, they may not serve the needs of local jurisdictions with different demographics, or where local data on some variables are missing. Engaging public health programs at the earliest stages of model design can optimize understanding of data gaps, local resource limitations, challenges in implementing recommendations, and the need for user-friendly modeling tools for local estimations.
Setting: In 2014, CDC/NCHHSTP awarded a competitive five-year cooperative agreement to design and adapt models for public health decision-making for HIV prevention and the other four Center focus areas. One of three awardees was Emory University (in partnership with Johns Hopkins University, NORC at the University of Chicago, and the University of Washington), which has become the Emory Coalition for Applied Modeling for Prevention (CAMP). In its first year of funding, Emory CAMP is developing models, manuscripts, and web tools to address 6 overarching scientific questions, 4 of which include Division of HIV/AIDS Prevention collaboration. Emory CAMP was distinct among the awardees in incorporating a Public Health Advisory (PHA) workgroup. The PHA workgroup consists of public health programs that are diverse geographically, in maturity of data systems and technical capacity, and in the population demographics served. Representatives from state and city health departments as well as non-profit organizations provide input to CAMP modeling projects via a variety of iterative means.
Project: In February 2015, the PHA workgroup met with Emory CAMP members and CDC/NCHHSTP colleagues in Atlanta to review Year 1 projects. For each of 6 proposals, researcher(s) provided a brief presentation, CDC subject matter experts described the specific national public health interest in the results, and a collective discussion regarding methods, data availability, implications of potential results and additional needs was held with PHA workgroup representatives. Ongoing discussion continues via conference calls and use of a project management website.
Results: Among the additional needs identified by the PHA workgroup were modifiable “spreadsheet” tools based on national HIV models that would allow entry of local data to generate area-specific results, and the cost estimates that include technical capacity. The PHA group emphasized jurisdiction-specific challenges that must be considered to create practical recommendations: varying availability of HIV clinical providers, assumptions that may not be appropriate locally, and the political will for HIV interventions. Other issues identified included varying data completeness, terminology consistency (e.g., the differing CDC and HRSA care continuum definitions), local laws (e.g., that may restrict Data To Care interventions), local public health analytical capacity, budgetary costs split among multiple entities, and the challenges of communicating uncertainty to decision-makers, all of which impact the translation of research into public health action.
Lessons Learned: There is immense value in including prevention programs from the beginning of question design to understand regional variations in data validity, completeness, and gaps; terminology used by funders; political sensitivity; human and structural resources, and sensitivity analyses to account for varying local conditions.