HIV incidence is the rate at which new HIV infections occur in populations. While HIV prevalence measures overall disease burden, HIV incidence tracks the leading edge of the HIV/AIDS epidemic. Accurate HIV incidence estimates are critical for monitoring the HIV/AIDS epidemic, identifying populations at high risk of HIV acquisition, targeting prevention efforts, and designing and evaluating HIV prevention trials. Current methods for cross-sectional HIV incidence determination are insufficiently accurate. Our goal is to develop and validate accurate, cost-effective methods for cross-sectional HIV incidence determination. Our hypothesis is that diverse laboratory assays and robust statistical modeling can be combined to improve the accuracy of cross-sectional HIV incidence estimates. We will focus on analysis of HIV incidence in both subtype B (the major subtype driving the HIV/AIDS epidemic in the United States) and subtype C (the major subtype driving the HIV/AIDS epidemic in sub-Saharan Africa);other subtypes prevalent in sub-Saharan Africa will also be analyzed.
The Specific Aims of the project are:
Aim 1 : Continue to build a repository of diverse, well-characterized samples with information on the duration of HIV infection. Analyze the samples using serologic HIV incidence assays.
Aim 2 : Further develop and validate a novel high resolution melting (HRM) assay for HIV diversity. Determine whether HIV diversity can be used as a biomarker to differentiate between individuals with recent vs. chronic HIV infection.
Aim 3 : Use statistical analysis and mathematical modeling to assess the accuracy of methods for HIV incidence determination. Apply those approaches to data from Aim 1 (CD4 cell count, HIV viral load, and data from serologic assays) and Aim 2 (data from the HRM assay) to identify methods for HIV incidence determination that perform well in a wide variety of settings, and to assess their relative costs. Our repository will include samples from at least 19 completed clinical trials, cohort studies, and research projects representing key geographic, demographic, and clinically-relevant populations. Over 10,000 of the samples are already in hand. We will integrate laboratory science with statistical analysis and mathematical modeling in all phases of the project, and will evaluate a broad range of design parameters, including use of individual assays versus multi-assay algorithms, use of different assay cutoffs, and sequential ordering of assays. We believe that this comprehensive approach will lead to identification of accurate and cost-effective methods for cross-sectional HIV incidence determination. ) )

Public Health Relevance

This project will evaluate and optimize methods that can be used to determine HIV incidence (the rate of new HIV infections) from cross sectional surveys of single blood samples collected from individuals. These methods are needed to monitor the HIV/AIDS epidemic, to identify populations at high risk of HIV infection, to target HIV prevention efforts, and to design and evaluate HIV prevention trials.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI095068-03
Application #
8507141
Study Section
AIDS Clinical Studies and Epidemiology Study Section (ACE)
Program Officer
Sharma, Usha K
Project Start
2011-08-01
Project End
2015-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
3
Fiscal Year
2013
Total Cost
$686,668
Indirect Cost
$149,546
Name
Johns Hopkins University
Department
None
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
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Brookmeyer, Ron; Konikoff, Jacob; Laeyendecker, Oliver et al. (2013) Estimation of HIV incidence using multiple biomarkers. Am J Epidemiol 177:264-72
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