This application is to renew a project focused on using mathematical models to understand and predict the emergence of drug resistance to antiretrovirals (ARVs) for the treatment of Human Immunodeficiency Virus (HIV). As the usage rate of ARVs in resource-poor regions is increasing, high levels of drug resistance potentially could emerge and have a devastating impact on public health worldwide, derailing global plans to provide this treatment to many millions of HIV-infected individuals. Our proposed projects will extend the work of the current award, which showed the value of using mathematical models to understand the temporal dynamics of drug-resistant strains of HIV in the United States (US), and for predicting the magnitude of resistance in this setting. In the renewal our work will be extended by combining mathematical modeling with statistical analysis of datasets collected by collaborating groups in the US, Europe and Africa. We will have access to data on drug resistance and important related variables from large scale epidemiological and treatment studies conducted in these three continents. In resource-poor settings, such as Africa, drugs will be limited and thus demand will often greatly exceed supply. We will investigate the problems of allocating ARVs in Africa by using operation research (OR) techniques. We have three Specific Aims.
Aim 1 : to understand the emergence, explain the present, and predict the evolution of, complex epidemics of drug-resistant strains of HIV in the US and Europe.
Aim 2 : to predict the evolution of epidemics of drug-resistant strains, as a result of first- line regimens and prophylactic use of ARVs, in Africa.
Aim 3 : to evaluate the consequences of allocation of scarce HIV healthcare resources in Africa. To achieve this aim we will use models to evaluate the epidemiological and ethical consequences of gender-inequities in access to treatment, assess the epidemiological and ethical impact of treatment priority criteria, and determine healthcare resource allocation strategies that ensure sustainability. Our studies in the renewal will link transmission modeling, OR techniques and statistical analyses;our analyses will take advantage of the extraordinary data sets provided by our collaborators in the US, Europe and Africa.

Public Health Relevance

The emergence and control of drug-resistant strains of HIV is now a global problem. The epidemiology of this problem is complex, and the future of the HIV epidemic is unknown. Our projects focus on using mathematical models to understand, explain, and predict, the evolution of complex epidemics composed of drug-resistant strains of HIV in the US, Europe and Africa. The rollout of antiretrovirals in Africa is just beginning;however demand for drugs greatly exceeds supply. We will, by using mathematical models, evaluate the epidemiological and ethical consequences of allocation of the scarce supply of antiretrovirals in Africa. Our studies are based upon both mathematical modeling and data analyses. Our analyses will take advantage of the extraordinary data sets provided by our collaborators in the US, Europe and Africa. Our results will have direct relevance for health policy makers.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI041935-14
Application #
8232132
Study Section
AIDS Clinical Studies and Epidemiology Study Section (ACE)
Program Officer
Mckaig, Rosemary G
Project Start
1998-05-01
Project End
2014-02-28
Budget Start
2012-03-01
Budget End
2014-02-28
Support Year
14
Fiscal Year
2012
Total Cost
$670,826
Indirect Cost
$204,807
Name
University of California Los Angeles
Department
None
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Coburn, Brian J; Blower, Sally (2014) Predicting the potential for within-flight transmission and global dissemination of MERS. Lancet Infect Dis 14:99
Okano, Justin T; Blower, Sally (2014) HIV treatment, preexposure prophylaxis, and drug resistance: reconciling conflicting predictions from mathematical models. J Infect Dis 209:163-4
Wagner, Bradley G; Coburn, Brian J; Blower, Sally (2013) Increasing survival time decreases the cost-effectiveness of using "test & treat'' to eliminate HIV epidemics. Math Biosci Eng 10:1673-86
El-Sadr, Wafaa M; Coburn, Brian J; Blower, Sally (2011) Modeling the impact on the HIV epidemic of treating discordant couples with antiretrovirals to prevent transmission. AIDS 25:2295-9
Gerberry, David J; Blower, Sally M (2011) Could we – should we – calculate a risk exposure score for an HIV-negative individual in a serodiscordant couple? AIDS 25:1119-21
Cohen, Myron S; Gay, Cynthia L (2010) Treatment to prevent transmission of HIV-1. Clin Infect Dis 50 Suppl 3:S85-95
Wagner, Bradley G; Kahn, James S; Blower, Sally (2010) Should we try to eliminate HIV epidemics by using a 'Test and Treat' strategy? AIDS 24:775-6
Supervie, Virginie; Garcia-Lerma, J Gerardo; Heneine, Walid et al. (2010) HIV, transmitted drug resistance, and the paradox of preexposure prophylaxis. Proc Natl Acad Sci U S A 107:12381-6
Smith, Robert J; Okano, Justin T; Kahn, James S et al. (2010) Evolutionary dynamics of complex networks of HIV drug-resistant strains: the case of San Francisco. Science 327:697-701
Coburn, Brian J; Blower, Sally (2010) A major HIV risk factor for young men who have sex with men is sex with older partners. J Acquir Immune Defic Syndr 54:113-4

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