# Statistical Methods for Advancing HIV Prevention

> **NIH NIH R01** · FRED HUTCHINSON CANCER CENTER · 2024 · $412,018

## Abstract

Project Summary/Abstract
 Antiretroviral-based HIV prophylaxis is highly effective at preventing acquisition of HIV, yet there are many
implementation challenges. Population-based effectiveness studies seek to evaluate real-world impact of preventive
interventions. There is, however, a major limitation in our current ability to measure effectiveness of preventive
interventions at the population-level due to its requirement of resource-extensive longitudinal testing in a closed
cohort. HIV recency assays (assays that provide information on the timing of HIV acquisition) offer resource-
efficient estimates of incidence. However, the utility of such assays is currently limited due to lack of precision. In
addition, designing efficacy trials to evaluate new HIV preventive interventions is increasingly challenging when
effective prevention agents exist. To fill these gaps, we will advance statistical methodology to measure HIV
incidence and develop a new trial design to assess efficacy of an HIV preventive intervention. Specifically, we will
extend existing methods for estimating HIV incidence using recency assay data to accommodate covariate effects
on assay properties, temporal trends in HIV incidence, and to estimate HIV incidence with increased precision.
We will also develop a new class of HIV prevention efficacy trial design termed the ‘augmented active-controlled
design’ which will leverage additional information to infer HIV incidence absent intervention, i.e. ‘counterfactual
placebo’ HIV incidence. To extend and develop these methods, we will define a statistical framework; define
approaches to estimating and drawing inference about parameters given the data; derive and compare analytic
properties of the inferential methods; evaluate performance in simulation studies; and apply the methods to real
data to generate new scientific insights. These novel methods have direct application to evaluating the impact of
HIV preventive interventions in population-based effectiveness studies and randomized controlled efficacy trials,
and will be applicable to the study of other infectious diseases.
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## Key facts

- **NIH application ID:** 10798258
- **Project number:** 5R01AI177078-02
- **Recipient organization:** FRED HUTCHINSON CANCER CENTER
- **Principal Investigator:** Fei Gao
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $412,018
- **Award type:** 5
- **Project period:** 2023-03-01 → 2028-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10798258

## Citation

> US National Institutes of Health, RePORTER application 10798258, Statistical Methods for Advancing HIV Prevention (5R01AI177078-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10798258. Licensed CC0.

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