https://grants.nih.gov/grants/guide/pa-files/PAR-17-048.html

Application Due Date: March 15, 2017

The purpose of this FOA is to support innovative research to develop strategies to identify and target emerging or expanding HIV transmission clusters in near real-time using phylodynamic tracking and modeling. The long-term objective is to leverage existing HIV genotyping databases to monitor HIV transmission network dynamics in near real-time within a localized area or region and thereby enable more precise and efficient targeting of testing, treatment and prevention interventions to key populations.

The 2020 UNAIDS 90-90-90 goal is to have 90% of people living with HIV diagnosed, 90% of people diagnosed to be on sustained antiretroviral treatment, and 90% of people on treatment to maintain viral suppression. Achieving these 90-90-90 targets will require knowledge of who and where to test for HIV, how to target treatment and prevention interventions most effectively, and where drug resistance is occurring (to ensure viral suppression).

In the United States, once an individual tests positive for HIV, genotyping of HIV pol sequences is performed as standard-of-care to determine whether any HIV drug resistance mutations are present that may affect the choice of antiretroviral regimens. As a result, HIV sequence data are accumulated every day that have the potential to inform public health officials about the nature of the current epidemic within a localized population and how it is evolving over time.

Phylogenetic analysis of HIV pol sequence data has been used to infer partial local transmission networks. While such phylogenetic network analyses have been informative in identifying transmission clusters in a given geographic area, most of these studies have been limited to retrospective analysis of archival HIV sequence databases. These retrospective studies are less informative for predicting future transmission events. Moreover, traditional phylogenetic methods have typically required extensive computational and data analysis resources.

In contrast to traditional phylogenetics, phylodynamics incorporates a time element to identify transmission clusters as they emerge and begin to expand at a rapid rate. Phylodynamic tracking of HIV transmission networks in near real-time would enable more precise and efficient targeting of testing, prevention, and treatment interventions to key populations that are driving the current epidemic. This, in turn, would allow resources to be focused more efficiently on populations and locations where new infections are occurring at the highest rate. For the purposes of this FOA, near real-time is expected to be in the range of a few days to a few weeks from the time of initiation of genotyping. While proof-of-concept and significant progress towards this goal have already been established in some countries with centralized health care systems where genotyping is performed as standard of care, phylodynamic tracking in near real-time remains a significant challenge in the United States.

Applicants are expected to establish interdisciplinary collaborations that include public health departments, HIV genotyping laboratories, or other entities engaged in public health within a localized area of interest. Studies must involve populations in the United States where genotyping is routinely performed as standard of care. Studies involving key populations with high rates of HIV transmission are of greatest interest.

Examples of appropriate research topics may include but are not limited to:

• Optimization of phylogenetic data analysis and mathematical modeling to permit more rapid identification of emerging or expanding transmission clusters and to predict the future trajectory of such clusters
• Collaboration of academic phylogeneticists and bioinformaticians with sequencing laboratories and/or public health entities to analyze evolving HIV genotyping databases in near real-time
• The development of automated systems that would analyze incoming HIV genotyping data and generate HIV transmission cluster and drug resistance reports for use by public health officials
• Proof-of-concept studies leveraging phylodynamic data to inform HIV prevention efforts, testing, drug resistance, and/or adherence monitoring and to track the impact on HIV transmission clusters and networks

NIDA Interest Statement: The National Institute on Drug Abuse is particularly interested in phylodynamic tracking of HIV transmission in populations with high rates of intravenous drug use and/or substance use disorders.

NIMH Interest Statement: The National Institute of Mental Health is specifically interested in applications that combine phylodynamic data with socio-behavioral data, which may include HIV-negative high-risk persons, such as social or sexual network data, socio-environmental data, and/or qualitative data to help describe the psychosocial and behavioral contexts at the level of the transmission cluster to complement the phylogenetic data.

Applications proposing any of the following research topics will NOT be supported under this FOA:

• Studies exclusively limited to non-U.S. populations
• Studies lacking collaboration(s) with public health entities or testing laboratories
• Studies exclusively utilizing retrospective HIV sequence databases without innovation towards near real-time analysis
• Studies not focused on HIV transmission networks (e.g., other STI transmission networks without HIV)
• Clinical trials: applications that propose interventions and/or outcomes research that meet the NIH definition of a clinical trial (see http://osp.od.nih.gov/office-clinical-research-and-bioethics-policy/clinical-research-policy/clinical-trials for a definition of clinical trials

Applicants are highly encouraged to contact the program officials listed under Scientific/Research Contact(s) listed in Section VII to discuss their applications prior to submission to ensure research topics could be supported under this FOA.

See Section VIII. Other Information for award authorities and regulations.