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To the Editors:HIV remains a major cause of preventable morbidity and mortality in Kenya, with 100,000 new infections and an estimated 62,000 deaths in 2011.1 At the same time, unhealthy alcohol consumption is an important risk factor for HIV acquisition2–7 and progression.8 Kenya has one of the highest rates of unhealthy alcohol use worldwide,9,10 and as many as 13% of new HIV infections in Kenya may be attributable to unhealthy alcohol use.11Randomized controlled trials (RCTs) of cognitive behavioral therapy (CBT)-based interventions addressing unhealthy alcohol consumption in Kenya show promising results, increasing abstinence by 45%,12,13 and decreasing risky sex.14,15 However, alcohol remains conspicuously absent from programming in HIV and substance use.9,16 In low-resource settings, the benefits of scaling up an effective intervention must be balanced against the opportunity costs of using those resources to scale up alternatives intervention with potential benefit [for example, increasing eligibility for the first-line antiretroviral therapy (ART)]. Accordingly, we used a published validated computer simulation of the HIV epidemic in Kenya, incorporating HIV transmission and disease progression, to evaluate the cost-effectiveness of the alcohol intervention reported by Papas et al.12 Given the uncertainty surrounding costs of scale-up, we varied costing assumptions over a wide range ($1 to $50 per person), to identify the threshold at which its incremental cost-effectiveness ratio (ICER) descended below those of alternative resource uses (eg, when an alcohol intervention bought more “health” than alternative resource uses).We developed a computer simulation to inform HIV prevention decisions in East Africa across a wide range of possible interventions, including those directed at unhealthy alcohol use. This simulation is composed of a within-host progression module (eg, hypothetical patients are followed over time, and depending on ART adherence and other factors, may be more or less likely to die of AIDS versus other causes) that provides data to inform a population-level transmission module (eg, hypothetical groups of persons interact with one another, and HIV-infected groups may transmit the infection to non–HIV-infected groups). For example, an alcohol intervention may improve ART adherence, which lowers viral load and extends life expectancy in the progression model. The reduced viral load then decreases the risk of transmitting HIV in the transmission model. Additionally, an alcohol intervention may decrease risky sex. The design of the simulation, as well as its calibration and validation, is described in more detail elsewhere.11,17Based on a systematic review of pathways through which alcohol may impact HIV transmission risk,18 unhealthy alcohol use was modeled as having 3 main effects: (1) increasing the risk of condom nonuse (RR 1.29 for unsafe sex based on 2 sub-Saharan studies),19,20 (2) increasing the risk of ART nonadherence (RR 2.33 of missing doses based on pooled estimate from 4 studies),21–24 and (3) increasing sexually transmitted infection (STI) prevalence. The effect size of unhealthy alcohol use on increasing condom nonuse was assumed to be 1.72, based on 2 sub-Saharan studies.6,25 Other inputs to the simulation (eg, costs and utilities) are described elsewhere.17,26 In base case analyses, an alcohol intervention was assumed to decrease unhealthy alcohol consumption by 45%, based on the RCT of Papas et al,12 which used a CBT-based intervention adapted for Kenya.Outcomes included total life years, total quality-adjusted life years (QALYs), incremental cost per QALY, and incremental cost per infection averted. Costs and effects were discounted at 3% per WHO guidelines27 over a time horizon of 20 years, and costs were assessed from a societal perspective, in 2012 US$.