Background: Sabes, a treatment-as-prevention intervention among men who have sex with men and transgender women in Lima, Peru, was developed to identify HIV during early primary infection (<3 months from acquisition) through monthly serologic assays and HIV RNA tests. Newly diagnosed individuals were rapidly linked to care and offered to initiate ART. In this study we sought to study the cost-effectiveness of Sabes compared to the standard of care (SOC) for HIV testing and initiation of treatment.
Methods: We adapted a compartmental model of HIV transmission to evaluate the cost-effectiveness of the Sabes approach compared to the SOC using a government health care perspective, 20-year time horizon, and 3% annual discounting. We estimated the proportion of cases of HIV detected during early primary infection, reduction in HIV incidence and prevalence, incremental cost-effectiveness ratio (ICER), and net monetary benefit. We analyzed costs using data from the Sabes study, the Peruvian Ministry of Health, published literature, and expert consultation.
Findings: The Sabes intervention is projected to identify 9294 early primary HIV infections in Lima, Peru over 20 years. The intervention costs $6,896 per early primary infection diagnosed and by 2038 is expected to decrease the fraction of early infections among prevalent infections by 62%. Sabes is expected to improve health, resulting in greater total discounted QALYs per person than the SOC (16·7 vs 16·4, respectively). Sabes had an ICER of $1431 (22% per capita GDP in Peru) per QALY compared to SOC.
Interpretation: Our analysis suggests that in Lima, Peru the Sabes intervention could be a cost-effective approach to reduce the burden of HIV even under stringent cost-effectiveness criteria. This finding suggests that programs that use frequent HIV testing, rapid linkage to care and initiation of ART should be considered as part of a comprehensive HIV prevention strategy.
Funding: National Institutes of Health.
Keywords: ART; Acute infection; Cost-effectiveness; Early primary infection; HIV prevention; Mathematical model.
© 2022 Published by Elsevier Ltd.