339 research outputs found

    Evaluating strategies to improve HIV care outcomes in Kenya: a modelling study

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    Background With expanded access to antiretroviral therapy (ART) in sub-Saharan Africa, HIV mortality has decreased, yet life-years are still lost to AIDS. Strengthening of treatment programmes is a priority. We examined the state of an HIV care programme in Kenya and assessed interventions to improve the impact of ART programmes on population health. Methods We created an individual-based mathematical model to describe the HIV epidemic and the experiences of care among adults infected with HIV in Kenya. We calibrated the model to a longitudinal dataset from the Academic Model Providing Access To Healthcare (known as AMPATH) programme describing the routes into care, losses from care, and clinical outcomes. We simulated the cost and effect of interventions at different stages of HIV care, including improvements to diagnosis, linkage to care, retention and adherence of ART, immediate ART eligibility, and a universal test-and-treat strategy. Findings We estimate that, of people dying from AIDS between 2010 and 2030, most will have initiated treatment (61%), but many will never have been diagnosed (25%) or will have been diagnosed but never started ART (14%). Many interventions targeting a single stage of the health-care cascade were likely to be cost-effective, but any individual intervention averted only a small percentage of deaths because the effect is attenuated by other weaknesses in care. However, a combination of five interventions (including improved linkage, point-of-care CD4 testing, voluntary counselling and testing with point-of-care CD4, and outreach to improve retention in pre-ART care and on-ART) would have a much larger impact, averting 1Β·10 million disability-adjusted life-years (DALYs) and 25% of expected new infections and would probably be cost-effective (US571perDALYaverted).Thisstrategywouldimprovehealthmoreefficientlythanauniversaltestβˆ’andβˆ’treatinterventioniftherewerenoaccompanyingimprovementstocare(571 per DALY averted). This strategy would improve health more efficiently than a universal test-and-treat intervention if there were no accompanying improvements to care (1760 per DALY averted). Interpretation When resources are limited, combinations of interventions to improve care should be prioritised over high-cost strategies such as universal test-and-treat strategy, especially if this is not accompanied by improvements to the care cascade. International guidance on ART should reflect alternative routes to programme strengthening and encourage country programmes to evaluate the costs and population-health impact in addition to the clinical benefits of immediate initiation

    Recent HIV prevalence trends among pregnant women and all women in sub-Saharan Africa: implications for HIV estimates

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    OBJECTIVES: National population-wide HIV prevalence and incidence trends in sub-Saharan Africa (SSA) are indirectly estimated using HIV prevalence measured among pregnant women attending antenatal clinics (ANC), among other data. We evaluated whether recent HIV prevalence trends among pregnant women are representative of general population trends. DESIGN: Serial population-based household surveys in 13 SSA countries. METHODS: We calculated HIV prevalence trends among all women aged 15–49 years and currently pregnant women between surveys conducted from 2003 to 2008 (period 1) and 2009 to 2012 (period 2). Log-binomial regression was used to test for a difference in prevalence trend between the two groups. Prevalence among pregnant women was age-standardized to represent the age distribution of all women. RESULTS: Pooling data for all countries, HIV prevalence declined among pregnant women from 6.5 [95% confidence interval (CI) 5.3–7.9%] to 5.3% (95% CI 4.2–6.6%) between periods 1 and 2, whereas it remained unchanged among all women at 8.4% (95% CI 8.0–8.9%) in period 1 and 8.3% (95% CI 7.9–8.8%) in period 2. Prevalence declined by 18% (95% CI βˆ’9–38%) more in pregnant women than nonpregnant women. Estimates were similar in Western, Eastern, and Southern regions of SSA; none were statistically significant (Pβ€Š>β€Š0.05). HIV prevalence decreased significantly among women aged 15–24 years while increasing significantly among women 35–49 years, who represented 29% of women but only 15% of pregnant women. Age-standardization of prevalence in pregnant women did not reconcile the discrepant trends because at older ages prevalence was lower among pregnant women than nonpregnant women. CONCLUSION: As HIV prevalence in SSA has shifted toward older, less-fertile women, HIV prevalence among pregnant women has declined more rapidly than prevalence in women overall. Interpretation of ANC prevalence data to inform national HIV estimates should account for both age-specific fertility patterns and HIV-related sub-fertility

    HIV Treatment as Prevention: Considerations in the Design, Conduct, and Analysis of Cluster Randomized Controlled Trials of Combination HIV Prevention

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    The rigorous evaluation of the impact of combination HIV prevention packages at the population level will be critical for the future of HIV prevention. In this review, we discuss important considerations for the design and interpretation of cluster randomized controlled trials (C-RCTs) of combination prevention interventions. We focus on three large C-RCTs that will start soon and are designed to test the hypothesis that combination prevention packages, including expanded access to antiretroviral therapy, can substantially reduce HIV incidence. Using a general framework to integrate mathematical modelling analysis into the design, conduct, and analysis of C-RCTs will complement traditional statistical analyses and strengthen the evaluation of the interventions. Importantly, even with combination interventions, it may be challenging to substantially reduce HIV incidence over the 2- to 3-y duration of a C-RCT, unless interventions are scaled up rapidly and key populations are reached. Thus, we propose the innovative use of mathematical modelling to conduct interim analyses, when interim HIV incidence data are not available, to allow the ongoing trials to be modified or adapted to reduce the likelihood of inconclusive outcomes. The preplanned, interactive use of mathematical models during C-RCTs will also provide a valuable opportunity to validate and refine model projections

    The estimation and projection package age-sex model and the r-hybrid model: new tools for estimating HIV incidence trends in sub-Saharan Africa.

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    OBJECTIVES: Improve models for estimating HIV epidemic trends in sub-Saharan Africa (SSA). DESIGN: Mathematical epidemic model fit to national HIV survey and ANC sentinel surveillance (ANC-SS) data. METHODS: We modified EPP to incorporate age and sex stratification (EPP-ASM) to more accurately capture the shifting demographics of maturing HIV epidemics. Secondly, we developed a new functional form for the HIV transmission rate, termed 'r-hybrid', which combines a four-parameter logistic function for the initial epidemic growth, peak, and decline followed by a first-order random walk for recent trends after epidemic stabilization. We fitted the r-hybrid model along with previously developed r-spline and r-trend models to HIV prevalence data from household surveys and ANC-SS in 177 regions in 34 SSA countries. We used leave-one-out cross validation with household survey HIV prevalence to compare model predictions. RESULTS: The r-hybrid and r-spline models typically provided similar HIV prevalence trends, but sometimes qualitatively different assessments of recent incidence trends because of different structural assumptions about the HIV transmission rate. The r-hybrid model had the lowest average continuous ranked probability score, indicating the best model predictions. Coverage of 95% posterior predictive intervals was 91.5% for the r-hybrid model, versus 87.2 and 85.5% for r-spline and r-trend, respectively. CONCLUSION: The EPP-ASM and r-hybrid models improve consistency of EPP and Spectrum, improve the epidemiological assumptions underpinning recent HIV incidence estimates, and improve estimates and short-term projections of HIV prevalence trends. Countries that use general population survey and ANC-SS data to estimate HIV epidemic trends should consider using these tools

    How Much Do We Know about Drug Resistance Due to PrEP Use? Analysis of Experts' Opinion and Its Influence on the Projected Public Health Impact

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    BACKGROUND: Randomized controlled trials reported that pre-exposure prophylaxis (PrEP) with tenofovir and emtricitabine rarely selects for drug resistance. However, drug resistance due to PrEP is not completely understood. In daily practice, PrEP will not be used under the well-controlled conditions available in the trials, suggesting that widespread use of PrEP can result in increased drug resistance. METHODS: We surveyed expert virologists with questions about biological assumptions regarding drug resistance due to PrEP use. The influence of these assumptions on the prevalence of drug resistance and the fraction of HIV transmitted resistance was studied with a mathematical model. For comparability, 50% PrEP-coverage of and 90% per-act efficacy of PrEP in preventing HIV acquisition are assumed in all simulations. RESULTS: Virologists disagreed on the following: the time until resistance emergence (range: 20–180 days) in infected PrEP users with breakthrough HIV infections; the efficacy of PrEP against drug-resistant HIV (25%-90%); and the likelihood of resistance acquisition upon transmission (10%-75%). These differences translate into projections of 0.6%- 1% and 3.5%β€”6% infected individuals with detectable resistance 10 years after introducing PrEP, assuming 100% and 50% adherence, respectively. The rate of resistance emergence following breakthrough HIV infection and the rate of resistance reversion after PrEP use is discontinued, were the factors identified as most influential on the expected resistance associated with PrEP. Importantly, 17–23% infected individuals could virologically fail treatment as a result of past PrEP use or transmitted resistance to PrEP with moderate adherence. CONCLUSIONS: There is no broad consensus on quantification of key biological processes that underpin the emergence of PrEP-associated drug resistance. Despite this, the contribution of PrEP use to the prevalence of the detectable drug resistance is expected to be small. However, individuals who become infected despite the use of PrEP should be closely monitored due to higher risk of virological failure when initiating antiretroviral treatment in the future

    Estimating HIV Incidence among Adults in Kenya and Uganda: A Systematic Comparison of Multiple Methods

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    CITATION: Kim, A. A. et al. 2011. Estimating HIV incidence among adults in Kenya and Uganda : a systematic comparison of multiple methods. PLos ONE, 6(3): e17535, doi:10.1371/journal.pone.0017535.The original publication is available at http://journals.plos.org/plosoneBackground: Several approaches have been used for measuring HIV incidence in large areas, yet each presents specific challenges in incidence estimation. Methodology/Principal Findings: We present a comparison of incidence estimates for Kenya and Uganda using multiple methods: 1) Epidemic Projections Package (EPP) and Spectrum models fitted to HIV prevalence from antenatal clinics (ANC) and national population-based surveys (NPS) in Kenya (2003, 2007) and Uganda (2004/2005); 2) a survey-derived model to infer age-specific incidence between two sequential NPS; 3) an assay-derived measurement in NPS using the BED IgG capture enzyme immunoassay, adjusted for misclassification using a locally derived false-recent rate (FRR) for the assay; (4) community cohorts in Uganda; (5) prevalence trends in young ANC attendees. EPP/Spectrum-derived and survey-derived modeled estimates were similar: 0.67 [uncertainty range: 0.60, 0.74] and 0.6 [confidence interval: (CI) 0.4, 0.9], respectively, for Uganda (2005) and 0.72 [uncertainty range: 0.70, 0.74] and 0.7 [CI 0.3, 1.1], respectively, for Kenya (2007). Using a local FRR, assay-derived incidence estimates were 0.3 [CI 0.0, 0.9] for Uganda (2004/2005) and 0.6 [CI 0, 1.3] for Kenya (2007). Incidence trends were similar for all methods for both Uganda and Kenya. Conclusions/Significance: Triangulation of methods is recommended to determine best-supported estimates of incidence to guide programs. Assay-derived incidence estimates are sensitive to the level of the assay's FRR, and uncertainty around high FRRs can significantly impact the validity of the estimate. Systematic evaluations of new and existing incidence assays are needed to the study the level, distribution, and determinants of the FRR to guide whether incidence assays can produce reliable estimates of national HIV incidence.http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0017535Publisher's versio

    Disease-specific survival for limited-stage small-cell lung cancer affected by statistical method of assessment

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    BACKGROUND: In general, prognosis and impact of prognostic/predictive factors are assessed with Kaplan-Meier plots and/or the Cox proportional hazard model. There might be substantive differences from the results using these models for the same patients, if different statistical methods were used, for example, Boag log-normal (cure-rate model), or log-normal survival analysis. METHODS: Cohort of 244 limited-stage small-cell lung cancer patients, were accrued between 1981 and 1998, and followed to the end of 2005. The endpoint was death with or from lung cancer, for disease-specific survival (DSS). DSS at 1-, 3- and 5-years, with 95% confidence limits, are reported for all patients using the Boag, Kaplan-Meier, Cox, and log-normal survival analysis methods. Factors with significant effects on DSS were identified with step-wise forward multivariate Cox and log-normal survival analyses. Then, DSS was ascertained for patients with specific characteristics defined by these factors. RESULTS: The median follow-up of those alive was 9.5 years. The lack of events after 1966 days precluded comparison after 5 years. DSS assessed by the four methods in the full cohort differed by 0–2% at 1 year, 0–12% at 3 years, and 0–1% at 5 years. Log-normal survival analysis indicated DSS of 38% at 3 years, 10–12% higher than with other methods; univariate 95% confidence limits were non-overlapping. Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC) obstruction significantly impacted DSS. DSS assessed by the Cox and log-normal survival analysis methods for four clinical risk groups differed by 1–6% at 1 year, 15–26% at 3 years, and 0–12% at 5 years; multivariate 95% confidence limits were overlapping in all instances. CONCLUSION: Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC) obstruction all significantly impacted DSS. Apparent DSS for patients was influenced by the statistical methods of assessment. This would be clinically relevant in the development or improvement of clinical management strategies
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