Dataset Information

Achieving NHAS 90/90/80 Objectives by 2020: An Interactive Tool Modeling Local HIV Prevalence Projections.

ABSTRACT:

Background

Tools using local HIV data to help jurisdictions estimate future demand for medical and support services are needed. We present an interactive prevalence projection model using data obtainable from jurisdictional HIV surveillance and publically available data.

Methods

Using viral load data from Georgia's enhanced HIV/AIDS Reporting System, state level death rates for people living with HIV and the general population, and published estimates for HIV transmission rates, we developed a model for projecting future HIV prevalence. Keeping death rates and HIV transmission rates for undiagnosed, in care/viral load >200, in care/viral load<200, and out of care (no viral load for 12 months) constant, we describe results from simulations with varying inputs projecting HIV incidence and prevalence from 2014 to 2024.

Results

In this model, maintaining Georgia's 2014 rates for diagnosis, transitions in care, viral suppression (VS), and mortality by sub-group through 2020, resulted in 85% diagnosed, 59% in care, and 44% VS among diagnosed (85%/58%/44%) with a total of 67 815 PLWH, 33 953 in care, and more than 1000 new cases per year by 2020. Neither doubling the diagnosis rate nor tripling rates of re-engaging out of care PLWH into care alone were adequate to reach 90/90/80 by 2020. We demonstrate a multicomponent scenario that achieved NHAS goals and resulted in 63 989 PLWH, 57 546 in care, and continued annual prevalence increase through 2024.

Conclusions

Jurisdictions can use this HIV prevalence prediction tool, accessible at https://dph.georgia.gov/hiv-prevalence-projections to assess local capacity to meet future HIV care and social services needs. In this model, achieving 90/90/80 by 2020 in Georgia slowed but did not reverse increases in HIV prevalence, and the number of HIV-infected persons needing care and support services more than doubled. Improving the HIV care infrastructure is imperative.

SUBMITTER: Kelly JM

PROVIDER: S-EPMC4961282 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:HIV programmes face challenges achieving high rates of HIV testing and treatment needed to optimise health and to reduce transmission. We used data from the Botswana Combination Prevention Project study survey to assess Botswana's progress toward achieving UNAIDS targets for 2020: 90% of all people living with HIV knowing their status, 90% of these receiving sustained antiretroviral therapy (ART), and 90% of those having virological suppression (90-90-90). METHODS:A population-based sample of individuals was recruited and interviewed in 30 rural and periurban communities from Oct 30, 2013, to Nov 24, 2015, as part of a large, ongoing community-randomised trial designed to assess the effect of a combination prevention package on HIV incidence. A random sample of about 20% of households in each community was selected. Consenting household residents aged 16-64 years who were Botswana citizens or spouses of citizens responded to a questionnaire and had blood drawn for HIV testing in the absence of documentation of positive HIV status. Viral load testing was done in all HIV-infected participants, irrespective of treatment status. We used modified Poisson generalised estimating equations to obtain prevalence ratios, corresponding Huber robust SEs, and 95% Wald CIs to examine associations between individual sociodemographic factors and a binary outcome indicating achievement of the three individual and combined overall 90-90-90 targets. The study is registered at ClinicalTrials.gov, number NCT01965470. FINDINGS:81% of enumerated eligible household members took part in the survey (10% refused and 9% were absent). Among 12?610 participants surveyed, 3596 (29%) were infected with HIV, and 2995 (83·3%, 95% CI 81·4-85·2) of these individuals already knew their HIV status. Among those who knew their HIV status, 2617 (87·4%, 95% CI 85·8-89·0) were receiving ART (95% of those eligible by national guidelines, and 73% of all infected people). Of the 2609 individuals receiving ART with a viral load measurement, 2517 (96·5%, 95% CI 96·0-97·0) had viral load of 400 copies per mL or less. Overall, 70·2% (95% CI 67·5-73·0) of HIV-infected people had virological suppression, close to the UNAIDS target of 73%. INTERPRETATION:UNAIDS 90-90-90 targets are achievable even in resource-constrained settings with high HIV burden. FUNDING:US President's Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention.

Project description:INTRODUCTION:The 90-90-90 targets set by the United Nations aspire to 73% of people living with HIV (PLHIV) being virally suppressed by 2020. Using the HIV Synthesis Model, we aim to mimic the epidemic in Zimbabwe and make projections to assess whether Zimbabwe is on track to meet the 90-90-90 targets and assess whether recently proposed UNAIDS HIV transition metrics are likely to be met. METHODS:We used an approximate Bayesian computation approach to identify model parameter values which result in model outputs consistent with observed data, evaluated using a calibration score. These parameter values were then used to make projections to 2020 to compare with the 90-90-90 targets and other key indicators. We also calculated HIV transition metrics proposed by UNAIDS (percentage reduction in new HIV infections and AIDS-related mortality from 2010 to 2020, absolute rate of new infections and AIDS-related mortality, incidence-mortality ratio and incidence-prevalence ratios). RESULTS:After calibration, there was general agreement between modelled and observed data. The median predicted outcomes in 2020 were: proportion of PLHIV (aged 15 to 65) diagnosed 0.91 (90% uncertainty range 0.87, 0.94) (0.84 men, 0.95 women); of those diagnosed, proportion on treatment 0.92 (0.90, 0.93); of those receiving treatment, proportion with viral suppression 0.86 (0.81, 0.91). This results in 72% of PLHIV having viral suppression in 2020. We estimated a percentage reduction of 36.5% (13.7% increase to 67.4% reduction) in new infections from 2010 to 2020, and of 30.4% (9.7% increase to 56.6% reduction) in AIDS-related mortality (UNAIDS target 75%). The modelled absolute rates of HIV incidence and AIDS-related mortality in 2020 were 5.48 (2.26, 9.24) and 1.93 (1.31, 2.71) per 1000 person-years respectively. The modelled incidence-mortality ratio and incidence-prevalence ratios in 2020 were 1.05 (0.46, 1.66) and 0.009 (0.004, 0.013) respectively. CONCLUSIONS:Our model was able to produce outputs that are simultaneously consistent with an array of observed data and predicted that while the 90-90-90 targets are within reach in Zimbabwe, increased efforts are required in diagnosing men in particular. Calculation of the HIV transition metrics suggest increased efforts are needed to bring the HIV epidemic under control.