Test-and-Treat in Los Angeles: A Mathematical Model of the Effects of Test-and-Treat for the Population of Men Who Have Sex With Men in Los Angeles County

Autor: Zachary Wagner, Neeraj Sood, Raffaele Vardavas, Amber Jaycocks, Emmanuel F Drabo
Rok vydání: 2013
Předmět:
Zdroj: Clinical Infectious Diseases. 56:1789-1796
ISSN: 1537-6591
1058-4838
Popis: (See the Editorial Commentary by Jena on pages 1797–9.) Recent evidence suggests that antiretroviral therapy (ART) reduces the probability of human immunodeficiency virus (HIV) transmission, particularly if initiated at early stages of the disease [1–3]. Evidence also suggests that testing HIV positive causes dramatic reductions in sexual activity levels, which also reduces HIV transmission probability [4, 5]. In light of this evidence, health officials across the United States are taking steps toward scaling up testing programs and recommending immediate ART initiation to individuals testing positive, regardless of CD4 cell count [6]. Some argue a “test-and-treat” policy could lead to elimination of the HIV epidemic [7–9]. Although reasons exist for optimism regarding the role of increased testing and treating in HIV prevention agendas, some concerns remain unaddressed. One important concern is that increased ART use creates more multidrug-resistant strains, which might limit the benefits of test-and-treat [10]. Treatment resistance already poses a major public health problem in the United States [11]. Therefore, determining how to implement test-and-treat policies where HIV prevention is maximized and multidrug resistance (MDR) prevalence is minimized is important. Previous mathematical models that simulate the impact of scaling up test-and-treat policies show mixed results. Some find dramatic benefits [7, 12], whereas others find only modest effects [13–15]. There is also evidence from a natural experiment suggesting that some model results may be exaggerated [16]. The discrepancy in model findings reflects the sensitivity of test-and-treat outcomes to differing underlying assumptions about HIV prevalence, proportion of undiagnosed cases, risky sexual behavior, and other population or location-specific parameters [17, 18]. This highlights the critical need to calibrate mathematical models to mimic real-world HIV prevalence and incidence trends [19]. Additionally, none of these articles explicitly addresses potential effects of test-and-treat policies on the spread of MDR. However, an earlier strand of literature examining expanded ART use addresses this issue and reports mixed findings. Some find that increasing the percentage of people using ART would substantially reduce the HIV epidemic's severity even in the presence of high ART resistance levels [9, 20]. However, the authors note that emergence of highly transmissible resistant strains of HIV can significantly reduce the benefits of expanded use of ART [9]. Baggaley et al found that controlling sub-Saharan African HIV epidemics through treatment is ineffective, as increasing the proportion on treatment increases the emergence and spread of drug resistance [21]. Others find that benefits from expanded ART use are counterbalanced by modest increases in risky sexual behavior [21–23]. Our study contributes to this literature by using a mathematical model to simulate effects of increased testing and early initiation of treatment for men who have sex with men (MSM) in Los Angeles County (LAC). No previous study has focused on test-and-treat in LAC. In the United States, LAC has the largest incidence of HIV, and MSM account for 82% of all people living with HIV/AIDS (PLWHA) [24, 25]. We calibrate our model using HIV surveillance data from LAC for the years 2000 to 2009. Following calibration, we manipulate parameters relating to test-and-treat to simulate alternate test-and-treat policy scenarios. To assess the individual and complementary effects of testing and treating on epidemiologic outcomes, the intensity of both testing and treatment rates are varied. Finally, we also assess how the intensity of each mechanism affects the portion of the population with MDR. The results could help inform policy makers on best approaches for the test-and-treat policy and where to focus future HIV prevention efforts.
Databáze: OpenAIRE
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