Abstract
Background: The Sabes study, a treatment as prevention intervention in Peru, tested the hypothesis that initiating antiretroviral therapy (ART) early in HIV infection when viral load is high, would markedly reduce onward HIV transmission among high-risk men who have sex with men (MSM) and transgender women (TW). We investigated the potential population-level benefits of detection of HIV early after acquisition and rapid initiation of ART. Methods: We designed a transmission dynamic model to simulate the HIV epidemic among MSM and TW in Peru, calibrated to data on HIV prevalence and ART coverage from 2004 to 2011. We assessed the impact of an intervention starting in 2018 in which up to 50% of the new infections were diagnosed within three months of acquisition and initiated on ART within 1 month of diagnosis. We estimated the impact of the intervention over 20 years using the cumulative prevented fraction of new HIV infections compared to scenarios without intervention. Findings: Our model suggests that only 19% of the infected MSM and TW are virally suppressed in 2018 and 35%–40% of the new HIV infections are transmitted from contacts with acutely-infected partners. An intervention reaching 10% of all acutely infected MSM and TW is projected to prevent 13.3% [Uncertainty interval: 11.9%–14.3%] of the new infections over 20 years and reduce HIV incidence in 2038 by 24%. Reaching 50% of all acutely infected MSM and TW will increase the prevalence of viral suppression in 2038 to 59% and prevent 41% of expected infections over 20 years. Reaching 50% of the high-risk MSM and TW in acute phase would reduce HIV incidence in 2038 by 60% and prevent 36% of new infections between 2018 and 2038. Conclusions: Early detection of HIV infections and rapid initiation of ART among MSM is desirable as it would increase the effectiveness of the HIV prevention program in Peru. Targeting high-risk MSM and TW will be highly efficient.
Original language | English (US) |
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Pages (from-to) | 73-82 |
Number of pages | 10 |
Journal | Infectious Disease Modelling |
Volume | 4 |
DOIs | |
State | Published - 2019 |
Bibliographical note
Publisher Copyright:© 2019 The Authors
Keywords
- Antiretroviral therapy
- HIV incidence
- HIV prevention
- Mathematical model