An increasing number of HIV prevention interventions and strategies have been shown to reduce HIV incidence, with various degrees of protective efficacy, effectiveness, and cost-effectiveness. This raises critical questions: Which of these should be implemented and in what combinations? How does this differ for different highly affected populations and settings? The randomized clinical trials (RCTs) needed to answer these questions for both the US and international epidemics and sub-epidemics require large sample sizes and substantial funding. Modeling and simulation offer a strategy for down-selecting prevention interventions and combination packages and optimizing those that go into RCTs.
Modeling and simulation have proven to be useful in the study of many infectious diseases, including HIV. The NIH funded MIDAS (Models of Infectious Disease Agent Study) program (PA-16-107) has led to recommendations for pandemic flu preparedness and continues to guide ongoing flu research. These methods have also been used to simulate the community-level impact of combination HIV prevention strategies, considering all available information on sexual network characteristics, mixing within and between communities, coverage levels for different prevention modalities, and other variables. Social media data and geospatial mapping have also been used to identify HIV hotspots and to predict transmission trends.
There are two major goals of this FOA. The first is to support research that utilizes multiple HIV data sources to develop and validate modeling and simulation tools that can be used to examine HIV transmission dynamics and estimate the impact of HIV prevention interventions and combination strategies. Once the modeling and simulation tools have been developed, the second goal is to develop a mechanism and platform for making these tools available to other investigators.
These objectives will be accomplished through milestone-driven Go/No-Go criterion incorporated into the design of the research projects. It is expected the modeling and simulation objectives can be achieved in a three-year project period. NIAID recognizes, however, that making the modeling and simulation tools available to other investigators, together with one or more data sets used to validate these tools, will require additional time and effort. and require a fourth year of funding.
To fulfil these goals, applicants are required to provide Go/No-Go decision criteria for the transition from the development of modeling and simulation tools to the development of a platform for making the tools available to other investigators. These criteria will be referenced in the Notice of Award and used to determine funding for the fourth year to complete the project and make resources available to other investigators. Achievement of the stated goals (“Go” decision criteria) will enable a total of 4 years of support, while failure to achieve the stated goals (“No-Go” decision criteria) will result in negotiation of a reduced budget for year 4.
Specific Areas of Research Interest
Examples of research projects that are responsive to this FOA include but are not limited to those that:
- Propose to develop and validate methods that incorporate local and regional epidemiologic drivers and transmission dynamics of HIV to optimize local and regional prevention strategies in sub-Saharan Africa (SSA).
- Propose to develop and validate methods to optimize combination strategies for future trials in high-priority populations and settings (e.g. MSM, transgender persons, adolescent girls and young women (AGYW), migrants, and sex workers). The prevention interventions selected should have demonstrated acceptability and be suitable for scale-up in the populations targeted. –
- Use phylogenetic methods to examine patterns of HIV transmission on a population level, identify factors associated with HIV transmission, and assess the impact of targeted HIV prevention interventions, focusing on highly affected communities.
- Use network research methods to examine patterns of HIV transmission in sexual networks, identify factors associated with high-risk nodes, and assess the impact of targeted HIV prevention strategies.
- Use multiple, large data sources to develop and validate synthetic populations for major risk groups (MSM in North America or Europe, general populations in SSA, and others) to optimize regional prevention strategies.
Deadline: November 13, 2018 (letters of intent); December 13, 2018 (full proposals)
URL: https://grants.nih.gov/grants/guide/rfa-files/RFA-AI-18-026.html
Filed Under: Funding Opportunities