The purpose of this FOA is to foster exploratory basic research to develop innovative HIV phylodynamic approaches that are specifically optimized to identify and interrogate newly emerging and rapidly expanding HIV transmission clusters in close to real-time. As a companion to PAR-17-048, “Phylodynamic Tracking of HIV Transmission (R01),” this FOA is specifically focused on supporting novel strategies for developing, optimizing, and implementing tools, methods, algorithms, models, and technologies to optimize HIV phylodynamic analyses of HIV genotyping data in near real-time to allow prioritization and targeting of the most rapidly expanding HIV transmission clusters. The R21 mechanism is intended to encourage exploratory and developmental research projects by providing support for the early and conceptual stages of these studies. Thus, this FOA may support preliminary and smaller basic science studies that may ultimately provide optimized approaches that could be used in epidemiology research such as that supported by PAR-17-048.
Current HIV phylogenetic analysis methods have not been specifically tailored to monitor changes in HIV transmission clusters over time. There is a critical need to develop novel methods for phylodynamic tracking and modeling of HIV transmission clusters in near real-time. These approaches should be optimized to allow clinical HIV genotyping sequence data to be analyzed as it is obtained to identify and prioritize the fastest growing HIV transmission clusters as they emerge or expand. Care will also need to be taken to ensure that the confidentiality of the data is maintained during analysis. The ultimate long-term goal is to develop effective strategies that can be implemented in the public health setting. Strategies will identify and target HIV transmission clusters at greatest risk as they emerge or begin to expand rapidly so that testing, prevention, and treatment interventions can be employed efficiently and effectively to stop further spread of HIV within a population.
Research projects may include, but are not limited to the following examples:
- Developing novel phylogenetic analysis tools for monitoring cluster dynamics and evolution in near real-time
- Developing innovative approaches/methods to quantitate HIV transmission cluster growth kinetics
- Optimizing methods to improve cluster precision, accuracy and/or compensating for cluster heterogeneity
- Utilizing sequencing to determine recency within transmission networks
- Optimizing bioinformatic processes for managing and rapidly reporting emerging cluster data
- Studying evolution of transmitted or pre-therapy drug-resistance within emerging/expanding clusters
- Molecular clock analysis of clusters and/or projection of cluster growth as a function of time
- Investigating how missing components and sampling biases affect cluster analysis
- Accounting for additional risk determinants (e.g., other metadata in addition to the HIV genotype) in transmission cluster and network analysis
- Studying HIV transmission networks over time to determine key parameters associated with rapid expansion
- Designing FAIR (findable, accessible, interoperable, reusable) data interfaces to enable public health officials to monitor HIV genotyping data for transmission cluster growth in near real-time
Deadlines: standard AIDS dates apply
Filed Under: Funding Opportunities