If you’re capable of applying Big Data science methods and analyses to HIV viral suppression and transmission in the United States using population-level epidemiology, consider applying for a new opportunity from NIAID: Getting To Zero: Understanding HIV Viral Suppression and Transmission in the United States (R01, Clinical Trial Not Allowed). Your research can draw data from clinical care, laboratory measures, clinical trials, observational research, human behavior surveys, viral phylogenetics, bioinformatics, sexual networks, transmission clusters, geospatial mapping, and the larger human and environmental digital footprint.
Beyond analyzing available data, grantees will find approaches to increase the precision and timeliness of measures along the treatment cascade and determine critical components of rapid and sustained viral suppression at the individual and population level. To do so, propose strategies in your application that lead to:
- Improved accuracy and speed to describe the epidemiology of HIV care indicators: testing, linkage, engagement, suppression of viral load at a jurisdictional or national population level
- Evaluations of the epidemiology of HIV care to monitor progress overall and in sub-populations, such as by gender, transmission risk, race, age, or geographic region
- Research to uncover novel correlates and predictors of initial and sustained HIV viral suppression capitalizing on a rich understanding of the contextual factors impacting suppression
- Measurements of long-term viral suppression and the correlates and predictors of success
- Implementation strategies addressing coverage, service delivery systems, barriers to service delivery, and stigma that can be obtained from existing data or estimated in modeling applications
Ultimately, this research will lead to more focused and effective approaches to achieving HIV viral suppression.
A Note on Common Data Elements
NIH institutes have identified common data elements for many clinical domains, types of studies, types of outcomes, and patient registries. Before you apply, go to Common Data Element (CDE) Resource Portal and consider how your research can best meet and leverage the data standards relevant to your proposed research. Describe in your application how you will make use of common data elements.
Your proposed project period cannot exceed five years. This opportunity does not set a budget cap, but your proposed budget must reflect the actual needs of your project.
You cannot propose a clinical trial. Nor can you propose to establish a new cohort, use data sources from outside the United States, or conduct implementation science trials.
Applications are due once annually; the first due date is March 18, 2018.
Direct questions to Dr. Robin Huebner, the opportunity’s scientific/research contact.