CROI 2018 Abstract eBook

Abstract eBook

Poster Abstracts

1153 DESIGNING HIV VACCINE DELIVERY STRATEGIES IN SOUTH AFRICA: A POLICY ANALYSIS Blythe J. Adamson 1 , Simon de Montigny 2 , Benoît R. Mâsse 2 , Louis Garrison 1 , James G. Kublin 3 , Peter Gilbert 3 , Dobromir Dimitrov 3 1 University of Washington, Seattle, WA, USA, 2 Université de Montréal, Montreal, QC, Canada, 3 Fred Hutchinson Cancer Research Center, Seattle, WA, USA Background: Promising multi-dose HIV vaccine regimens are being tested in trials in South Africa. Efficient delivery will be a crucial component of future HIV immunization policies. To inform policy design, we estimate the epidemiological and economic impact of HIV vaccine campaigns compared to continuous clinic-based delivery, assuming efficacy is transient and dependent on immune response. Methods: We used a dynamic mathematical model of HIV transmission calibrated to 2012 epidemiological data to simulate vaccination with anticipated antiretroviral treatment scale-up in South Africa. The model estimates new HIV infections, quality-adjusted life years (QALYs), and healthcare costs from a government perspective discounted 5% annually. We assume a price of $75 per 5-dose regimen in the base case and a range of prices in the sensitivity analysis. Vaccine delivery policy is simulated following three strategies: standard care with no HIV vaccine, continuous clinic-based delivery, and a mass campaign every two years. We compared costs and health outcomes across strategies, including the maximum vaccine price that remains cost-effective in South Africa. We explore outcome sensitivity in a range of scenarios. Results: We estimate that biennial vaccination with a 70% efficacious vaccine reaching 20% coverage of the sexually active population could prevent 0.48-0.65 million HIV infections (13.8%-15.3% of the projected infections under standard care) over 10 years. Implementation with this campaign delivery dominated clinic-based delivery due to lower costs and increase in QALYs gained. The campaign strategy had an incremental cost-effectiveness ratio of $13,746 per QALY compared to no vaccine. Using a willingness-to-pay threshold of 3xGDP per capita, we find vaccination to be cost-effective if the price remains less than $29 per dose for the 5-dose series. Increasing vaccination coverage to 50% is expected to prevent more HIV infections but is less likely to be cost-effective. Mass campaign vaccination is consistently more effective and less costly than continuous clinic-based vaccination achieving the same biennial coverage across scenarios. Conclusion: Our analysis suggests that a partially effective HIV vaccine will have substantial impact on the HIV epidemic in South Africa and will offer good value if priced less than $145 per five-dose series. Vaccination campaigns every two years may offer greater value for money than continuous vaccination reaching the same coverage level.

1154 FINE TUNING SPATIAL RESOLUTION OF HIV EPIDEMIOLOGIC DATA WHILE PROTECTING PRIVACY Marta M. Jankowska, Tommi O. Gaines, Susan J. Little, Sanjay R. Mehta, Antoine Chaillon University of California San Diego, La Jolla, CA, USA Background: Privacy is a major concern with HIV-associated data. These data are often aggregated into larger spatial units to preserve privacy. However, the absence of HIV data at finer geographic scales limits the utility of spatial analyses to optimally target HIV interventions. Dasymetric mapping (DASY) is an areal interpolation method where the target polygons are zones of relative homogeneity with the purpose of best portraying the underlying statistical surface of the data being mapped. Here, we developed a cartographic DASY approach coupled with probabilistic reweighting to identify clusters of new HIV infections in San Diego County. Methods: Age, sex, and ethnicity were collected for 657 HIV individuals enrolled in the San Diego Primary Resource Consortium (SDPIRC) across 6 SD Health and Human Services Agency (HHSA) regions. Transforming the data from HHSA region to a high resolution grid involved the following steps (Fig.): Generation of a background 500x500m grid surface combined with residential use data (step 1); DASY to interpolate data on residential land use, U.S. Census demographic data, and HIV prevalence data from Health Department into a 500x500m grid (step 2); finally, probabilistic reweighting was applied to the SDPRIC data to redistribute HIV new infection from HHSA regions to the 500x500m grid (step 3). Constraining variables (data from the SDPIRC cohort and grid cell map) were used to infer which grid cells HIV+ individuals were most likely to reside. A map was generated for each individual, and then aggregated for the full cohort to generate a final grid-based model of the distribution of the SDPIRC cohort. Results: The resolved grid map shows considerably more details of where clusters of new infections reside throughout the county compared to the map divided into the 6 HHSA regions. While the expected cluster of infection in central San Diego remains, two hot spots that are not visible at the HHSA region level map emerge in north SD County, and in east SD County (Fig., circled in blue). Furthermore, the final grid model shows increased resolution of hotspots of HIV new infections in central and south-central SD. Conclusion: The ability to identify and predict the spread of transmissible diseases, including HIV, is crucial to optimally target treatment and prevention programs. Downscaling health data without violating privacy and confidentiality restrictions can help to reveal spatial patterns at the local level that are not apparent in aggregated data sets.

Poster Abstracts

CROI 2018 447