There has been a huge shift in the HIV prevention field, in which biomedical interventions have been elevated to the forefront of research and practice. This has re-energized efforts to expand global access to antiretroviral therapy and support treatment as prevention (TasP), as well as to expand targeted access to pre-exposure prophylaxis (PrEP). While there is enthusiasm about the prospect of ending HIV, it is critical to consider how our intervention efforts will interact with the complex demographic and biological systems in which they are placed. Our project brings together experienced social and biomedical scientists for a unique interdisciplinary project: to build an integrated methodological framework to study the multi-level biological and behavioral foundations of the population dynamics of HIV. We will combine newly developed stochastic models for representing the dynamics of human partnership networks with models that represent viral evolutionary dynamics within and between hosts. The result will be a comprehensive framework for studying the impact of biomedical interventions on HIV evolution and drug resistance under different transmission network conditions.
Our specific aims are: 1) To create a new public software package that integrates models for viral transmission networks and intra- and inter-host viral dynamics and evolution;2) To determine how transmission network structure and biomedical interventions influence trends in population-level measures of HIV viral load, including set point viral load (as a proxy for HIV virulence) and community viral load (as a potential metric for intervention impact evaluation);and 3) To investigate the interaction of transmission network structure and biomedical interventions on the emergence and spread of HIV drug resistance mutations.

Public Health Relevance

We will create a novel methodological framework that integrates the social dynamics of sexual networks with the evolutionary dynamics of HIV. This unique integrative framework will lead to critical insights on HIV epidemiology and prevention, and provide new tools for a wide range of basic research areas, including virology, evolutionary biology, epidemiology, and network analysis.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Project (R01)
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AIDS Clinical Studies and Epidemiology Study Section (ACE)
Program Officer
Flanagan, Elizabeth
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University of Washington
Schools of Medicine
United States
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Vandormael, Alain; de Oliveira, Tulio; Tanser, Frank et al. (2018) High percentage of undiagnosed HIV cases within a hyperendemic South African community: a population-based study. J Epidemiol Community Health 72:168-172
Herbeck, Joshua T; Peebles, Kathryn; Edlefsen, Paul T et al. (2018) HIV population-level adaptation can rapidly diminish the impact of a partially effective vaccine. Vaccine 36:514-520
Vandormael, Alain; Bärnighausen, Till; Herbeck, Joshua et al. (2018) Longitudinal Trends in the Prevalence of Detectable HIV Viremia: Population-Based Evidence From Rural KwaZulu-Natal, South Africa. Clin Infect Dis 66:1254-1260
Kerani, Roxanne P; Herbeck, Joshua T; Buskin, Susan E et al. (2017) Evidence of Local HIV Transmission in the African Community of King County, Washington. J Immigr Minor Health 19:891-896
Wolf, Elizabeth; Herbeck, Joshua T; Van Rompaey, Stephen et al. (2017) Short Communication: Phylogenetic Evidence of HIV-1 Transmission Between Adult and Adolescent Men Who Have Sex with Men. AIDS Res Hum Retroviruses 33:318-322
Herbeck, Joshua; Tanser, Frank (2016) Community viral load as an index of HIV transmission potential. Lancet HIV 3:e152-4
Blanquart, François; Grabowski, Mary Kate; Herbeck, Joshua et al. (2016) A transmission-virulence evolutionary trade-off explains attenuation of HIV-1 in Uganda. Elife 5:
Herbeck, Joshua; Celum, Connie (2014) The changing virulence of HIV. Lancet HIV 1:e99-e100
Herbeck, Joshua T; Mittler, John E; Gottlieb, Geoffrey S et al. (2014) An HIV epidemic model based on viral load dynamics: value in assessing empirical trends in HIV virulence and community viral load. PLoS Comput Biol 10:e1003673