Dataset Information

A mathematical model of comprehensive test-and-treat services and HIV incidence among men who have sex with men in the United States.

ABSTRACT:

Background

Early diagnosis and treatment of HIV infection and suppression of viral load are potentially powerful interventions for reducing HIV incidence. A test-and-treat strategy may have long-term effects on the epidemic among urban men who have sex with men (MSM) in the United States and may achieve the 5-year goals of the 2010 National AIDS Strategy that include: 1) lowering to 25% the annual number of new infections, 2) reducing by 30% the HIV transmission rate, 3) increasing to 90% the proportion of persons living with HIV infection who know their HIV status, 4) increasing to 85% the proportion of newly diagnosed patients linked to clinical care, and 5) increasing by 20% the proportion of HIV-infected MSM with an undetectable HIV RNA viral load.

Methods and findings

We constructed a dynamic compartmental model among MSM in an urban population (based on New York City) that projects new HIV infections over time. We compared the cumulative number of HIV infections in 20 years, assuming current annual testing rate and treatment practices, with new infections after improvements in the annual HIV testing rate, notification of test results, linkage to care, initiation of antiretroviral therapy (ART) and viral load suppression. We also assessed whether five of the national HIV prevention goals could be met by the year 2015. Over a 20-year period, improvements in test-and-treat practice decreased the cumulative number of new infections by a predicted 39.3% to 69.1% in the urban population based on New York City. Institution of intermediate improvements in services would be predicted to meet at least four of the five goals of the National HIV/AIDS Strategy by the 2015 target.

Conclusions

Improving the five components of a test-and-treat strategy could substantially reduce HIV incidence among urban MSM, and meet most of the five goals of the National HIV/AIDS Strategy.

SUBMITTER: Sorensen SW

PROVIDER: S-EPMC3277596 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A mathematical model of comprehensive test-and-treat services and HIV incidence among men who have sex with men in the United States.

Sorensen Stephen W SW Sansom Stephanie L SL Brooks John T JT Marks Gary G Begier Elizabeth M EM Buchacz Kate K Dinenno Elizabeth A EA Mermin Jonathan H JH Kilmarx Peter H PH

PloS one 20120210 2

<h4>Background</h4>Early diagnosis and treatment of HIV infection and suppression of viral load are potentially powerful interventions for reducing HIV incidence. A test-and-treat strategy may have long-term effects on the epidemic among urban men who have sex with men (MSM) in the United States and may achieve the 5-year goals of the 2010 National AIDS Strategy that include: 1) lowering to 25% the annual number of new infections, 2) reducing by 30% the HIV transmission rate, 3) increasing to 90 ...[more]

PMID: 22347994

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Project description:HIV set point viral load (SPVL), the viral load established shortly after initial infection, is a proxy for HIV virulence: higher SPVLs lead to higher risk of transmission and faster disease progression. Three models of test-and-treat scenarios, mainly in heterosexual populations, found that increasing treatment coverage selected for more virulent viruses. We modeled virulence evolution in a population of men who have sex with men (MSM) with increasing test-and-treat coverage. We extended a stochastic, dynamic network model (EvoNetHIV). We varied relationship patterns (MSM vs. heterosexual), HIV transmission models (increasing vs. plateauing probability of transmission at very high viral loads), and treatment roll-out (with explicit testing or fixed intervals between infection and treatment). In scenarios most similar to previous models (longer relational durations and the plateauing transmission function), we replicated trends previously found: increasing treatment coverage led to increased virulence (0.12 log10 increase in mean population SPVL between 20% and 100% treatment coverage). In scenarios reflecting MSM behavioral data using the increasing transmission function, increasing treatment coverage selected for viruses with lower virulence (0.16 log10 decrease in mean population SPVL between 20% and 100% treatment coverage). These findings emphasize the impact of sexual network conditions and transmission function details on predicted epidemiological and evolutionary outcomes. Varying these features creates very different evolutionary environments, which in turn lead to opposite effects in mean population SPVL evolution. Our results suggest that, under some realistic conditions, effective test-and-treat strategies may not face the previously reported tradeoff in which increasing coverage leads to evolution of greater virulence. This suggests instead that a virtuous cycle of increasing treatment coverage and diminishing virulence is possible.

Project description:IntroductionMore than 70% of new HIV diagnoses in the United States were among men who have sex with men (MSM) in 2019. Pre-exposure prophylaxis (PrEP) is a transformative innovation for reducing human immunodeficiency virus (HIV) infections. Structural stigma against sexual minorities, including in the form of state-level policies, may affect PrEP implementation. We evaluated whether lower structural stigma reflected by earlier year of state same-sex marriage legalization was associated with increased male PrEP prescriptions and male PrEP-to-need ratio (PnR), a ratio of PrEP prescriptions to new HIV diagnoses.MethodsWe used 2012-2019 AIDSVu data on male PrEP prescriptions and male PnR in each US state and year. We used generalized estimating equations to evaluate the relationship between the timing of implementing state same-sex marriage policies and the outcomes of male PrEP prescriptions per 100,000 people and the male PnR. We adjusted for calendar year, Medicaid expansion and the political party of the governor in each state.ResultsState implementation of same-sex marriage policies in earlier, relative to later, periods was associated with increases in the rate of male PrEP prescriptions and in the male PnR. Specifically, implementing state same-sex marriage policies between 2004 and 2011 and between 2012 and 2013 were each associated with greater rates of male PrEP prescriptions relative to implementing same-sex marriage policies between 2014 and 2015. Implementing state same-sex marriage policies between 2004 and 2011 as well as between 2012 and 2013 were both significantly associated with a greater male PnR relative to implementing same-sex marriage policies between 2014 and 2015. By 2019, the difference in male PrEP prescriptions was 137.9 (97.3-175.5) per 100,000 in states that implemented same-sex marriage in 2004-2011 and 27.2 (23.3-30.5) per 100,000 in states that implemented same-sex marriage from 2012 to 2013, relative to states that implemented same-sex marriage in 2014-2015.ConclusionsEarlier implementation of state same-sex marriage policies was associated with greater rates of male PrEP prescriptions. Reducing state-level structural stigma may improve HIV prevention among MSM in the United States.

Project description:BACKGROUND:The rise of gonococcal antimicrobial resistance highlights the need for strategies that extend the clinically useful life span of antibiotics. Because there is limited evidence to support the current practice of switching empiric first-line antibiotic when resistance exceeds 5% in the population, our objective was to compare the impact of alternative strategies on the effective life spans of antibiotics and the overall burden of gonorrhea. METHODS AND FINDINGS:We developed and calibrated a mathematical model of gonorrhea transmission among men who have sex with men (MSM) in the United States. We calibrated the model to the estimated prevalence of gonorrhea, the rate of gonorrhea cases, and the proportion of cases presenting symptoms among MSM in the US. We used this model to project the effective life span of antibiotics and the number of gonorrhea cases expected under current and alternative surveillance strategies over a 50-year simulation period. We demonstrate that compared to the current practice, a strategy that uses quarterly (as opposed to yearly) surveillance estimates and incorporates both the estimated prevalence of resistance and the trend in the prevalence of resistance to determine treatment guidelines could extend the effective life span of antibiotics by 0.83 years. This is equivalent to successfully treating an additional 80.1 (95% uncertainty interval: [47.7, 111.9]) gonorrhea cases per 100,000 MSM population each year with the first-line antibiotics without worsening the burden of gonorrhea. If the annual number of isolates tested for drug susceptibility is doubled, this strategy could increase the effective life span of antibiotics by 0.94 years, which is equivalent to successfully treating an additional 91.1 (54.3, 127.3) gonorrhea cases per 100,000 MSM population each year without increasing the incidence of gonorrhea. Study limitations include that our conclusions might not be generalizable to other settings because our model describes the transmission of gonorrhea among the US MSM population, and, to better capture uncertainty in the characteristics of current and future antibiotics, we chose to model hypothetical drugs with characteristics similar to the antibiotics commonly used in gonorrhea treatment. CONCLUSIONS:Our results suggest that use of data from surveillance programs could be expanded to prolong the clinical effectiveness of antibiotics without increasing the burden of the disease. This highlights the importance of maintaining effective surveillance systems and the engagement of policy makers to turn surveillance findings into timely and effective decisions.

Dataset Information

A mathematical model of comprehensive test-and-treat services and HIV incidence among men who have sex with men in the United States.

Background

Methods and findings

Conclusions

Publications

A mathematical model of comprehensive test-and-treat services and HIV incidence among men who have sex with men in the United States.

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