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NIH grant 1R01AI207138-01A1: Optimizing clinic-delivered HIV pre-exposure prophylaxis services with self-testing
Institute: {'code': 'AI', 'abbreviation': 'NIAID', 'name': 'National Institute of Allergy and Infectious Diseases', 'admin_org_id': '12500003', 'admin_funding_url': ''}. PI: Katrina Frances Ortblad. Award: $850388.
Start: 2026-09-24T00:00:00.
ABSTRACT
Kenya and other African countries are facing several challenges to delivering HIV pre-exposure prophylaxis
(PrEP)—many exacerbated by recent cuts to foreign aid. Simultaneously, governments are tasked with planning
for the introduction of new long-acting PrEP products, which are anticipated to increase demand and further
strain overburdened health systems. Numerous tools could potentially alleviate PrEP delivery burden and should
be tested at public clinics to see if they create efficiencies. Among these are HIV self-testing (HIVST)—
recommended by the World Health Organization for PrEP initiation and continuation; multi-month dispensing
(MMD) to reduce clients’ number of annual PrEP clinic visits; and artificial intelligence (AI) to support clients with
HIVST/PrEP use. A recent individual-level randomized controlled trial (RCT) conducted at one research clinic in
Kenya tested a model of 6-monthly MMD oral PrEP dispensing supported with HIVST between semiannual clinic
visits; compared to quarterly clinic visits, the intervention did not compromise clinical outcomes (PrEP
continuation and adherence), was acceptable to clients, and decreased PrEP delivery cost per client
(R01MH113572). We now propose to further optimize PrEP delivery by fully task-shifting HIV testing to clients
with HIVST at and between initiation and follow-up visits (for non-injectable PrEP products) and partially task-
shifting educational portions of HIVST/PrEP counseling to clients by availing to them a digital tool enhanced with
AI capabilities (an “AI companion”) that can: 1) guide HIVST, 2) answer basic HIV/PrEP queries, and 3) send
automated reminders for interim HIVST and PrEP refill visits. This will be the first study to test HIVST to support
PrEP delivery both at and between clinic visits, and among the first to test an AI companion in public clinics. In
a hybrid type I cluster-RCT, we will 1:1 randomize 20 public clinics to deliver using existing clinic staff either: 1)
optimized PrEP, with HIVST, an AI companion, and 6-monthly dispensing or 2) standard-of-care PrEP, with no
HIVST or AI companion and 3-monthly dispensing (Aim 1). Our primary clinical outcome is clinics’ volume of
active PrEP clients, measured cross-sectionally at 18 months post-implementation using clinic records.
Secondary clinical outcomes—including PrEP initiation and continuation—will be assessed using clinic records;
secondary implementation outcomes—including reach, efficiency, and intervention adoption and acceptability—
will be assessed using clinic records, survey data (n=400 clients and 40 providers), and time-and-motion
observations (n=200). To identify multi-level intervention challenges and success factors, we will interview PrEP
clients (n=48), providers (n=20), and stakeholders (n=10) and integrate findings with the Aim 1 outcomes to
generate implementation insights (Aim 2). We will estimate the intervention’s real-world programmatic costs and
budget-impact (Aim 3). Near study endline, we will host a stakeholder meeting to identify high-priority intervention
barriers and strategies for scale-up. This study will generate timely evidence for PrEP programs in Kenya and
globally, especially if the intervention enables clinics to serve more PrEP clients and is cost-saving.document fetched 2026-10-04 02:44