Modelling HIV epidemics in the antiretroviral era: the UNAIDS Estimation and Projection package 2009

The AIDS Epidemic Model 2023 for Estimating HIV Trends and Transmission Dynamics in Asian Epidemic Settings

BACKGROUND

Thirteen Asian countries use the AIDS Epidemic Model (AEM) as their HIV model of choice. This article describes AEM, its inputs, and its application to national modeling.

SETTING

AEM is an incidence tool used by Spectrum for the Joint United Nations Programme on HIV/AIDS global estimates process.

METHODS

AEM simulates transmission of HIV among key populations (KPs) using measured trends in risk behaviors. The inputs, structure and calculations, interface, and outputs of AEM are described. The AEM process includes (1) collating and synthesizing data on KP risk behaviors, epidemiology, and size to produce model input trends; (2) calibrating the model to observed HIV prevalence; (3) extracting outputs by KP to describe epidemic dynamics and assist in improving responses; and (4) importing AEM incidence into Spectrum for global estimates. Recent changes to better align AEM mortality with Spectrum and add preexposure prophylaxis are described.

RESULTS

The application of AEM in Thailand is presented, describing the outputs and uses in-country. AEM replicated observed epidemiological trends when given observed behavioral inputs. The strengths and limitations of AEM are presented and used to inform thoughts on future directions for global models.

CONCLUSIONS

AEM captures regional HIV epidemiology well and continues to evolve to meet country and global process needs. The addition of time-varying mortality and progression parameters has improved the alignment of the key population compartmental model of AEM with the age-sex-structured national model of Spectrum. Many of the features of AEM, including tracking the sources of infections over time, should be incorporated in future global efforts to build more generalizable models to guide policy and programs.

Queiroz B. An indirect method to monitor the fraction of people ever infected with COVID-19: An application to the United States

The number of COVID-19 infections is key for accurately monitoring the pandemics. However, due to differential testing policies, asymptomatic individuals and limited large-scale testing availability, it is challenging to detect all cases. Seroprevalence studies aim to address this gap by retrospectively assessing the number of infections, but they can be expensive and time-intensive, limiting their use to specific population subgroups. In this paper, we propose a complementary approach that combines estimated (1) infection fatality rates (IFR) using a Bayesian melding SEIR model with (2) reported case-fatality rates (CFR) in order to indirectly estimate the fraction of people ever infected (from the total population) and detected (from the ever infected). We apply the technique to the U.S. due to their remarkable regional diversity and because they count with almost a quarter of all global confirmed cases and deaths. We obtain that the IFR varies from 1.25% (0.39-2.16%, 90% CI) in Florida, the most aged population, to 0.69% in Utah (0.21-1.30%, 90% CI), the youngest population. By September 8, 2020, we estimate that at least five states have already a fraction of people ever infected between 10% and 20% (New Jersey, New York, Massachussets, Connecticut, and District of Columbia). The state with the highest estimated fraction of people ever infected is New Jersey with 17.3% (10.0, 55.8, 90% CI). Moreover, our results indicate that with a probability of 90 percent the fraction of detected people among the ever infected since the beginning of the epidemic has been less than 50% in 15 out of the 20 states analyzed in this paper. Our approach can be a valuable tool that complements seroprevalence studies and indicates how efficient have testing policies been since the beginning of the outbreak.

HIV/AIDS Among Female Sex Workers in China: Epidemiology and Recent Prevention Strategies

PURPOSE OF REVIEW

This review aims to describe the epidemiology of HIV among female sex workers (FSWs) in China over the past decade, to summarize current gaps in knowledge regarding risk factors, and to identify new directions for HIV prevention strategies.

RECENT FINDINGS

We summarized national and regional levels of HIV prevalence among FSWs based on reported rates in the literature from 2008 to 2018. Studies identified cases of HIV infection among FSWs in all but one province during this time period, and demonstrated a sporadic pattern in most provinces, with a low overall national HIV prevalence below 1%. However, in Yunnan and Guanxi Zhuang Autonomous Regions, the median-reported prevalence rates were close to or slightly above 1%. National prevention programs have widely promoted male condoms as a primary and practical measure for HIV prevention, but studies evaluating condom use practices among FSWs demonstrated wide variability. A rise in illicit use of synthetic drugs and changing sexual practices in the setting of sex work (e.g., anal sex) may represent newer risk factors for HIV transmission among FSWs; however, more data are needed to better characterize these trends. Limited studies have examined the feasibility and efficacy of innovative prevention tools (e.g., female condoms) or strategies (e.g., pre-exposure prophylaxis, PrEP) to prevent HIV among FSWs. We call for a more comprehensive understanding of current trends in HIV risk among FSWs, as well as more research focuses on innovative strategies to reduce the spread of HIV in this vulnerable population.

The effect of "universal test and treat" program on HIV treatment outcomes and patient survival among a cohort of adults taking antiretroviral treatment (ART) in low income settings of Gurage zone, South Ethiopia

BACKGROUND

Through universal "test and treat approach" (UTT) it is believed that HIV new infection and AIDS related death will be reduced at community level and through time HIV can be eliminated. With this assumption the UTT program was implemented since 2016. However, the effect of this program in terms of individual patient survival and treatment outcome was not assessed in relation to the pre-existing defer treatment approach.

OBJECTIVE

To assess the effects of UTT program on HIV treatment outcomes and patient survival among a cohort of adult HIV infected patients taking antiretroviral treatment in Gurage zone health facilities.

METHODS

Institution based retrospective cohort study was conducted in facilities providing HIV care and treatment. Eight years (2012-2019) HIV/AIDS treatment records were included in the study. Five hundred HIV/AIDS treatment records were randomly selected and reviewed. Data were abstracted using standardized checklist by trained health professionals; then it was cleaned, edited and entered by Epi info version 7 and analyzed by STATA. Cox model was built to estimate survival differences across different study variables.

RESULTS

A total of 500 patients were followed for 1632.6 person-year (PY) of observation. The overall incidence density rate (IDR) of death in the cohort was 3 per-100-PY. It was significantly higher for differed treatment program, which is 3.8 per-100-PY compared to 2.4 per-100-PY in UTT program with a p value of 0.001. The relative risk of death among differed cases was 1.58 times higher than the UTT cases. The cumulative probability of survival at the end of 1st, 2nd, 3rd, and 4th years was 98%, 90.2%, 89.2% and 88% respectively with difference between groups. The log rank test and Kaplan-Meier survival curve indicated patients enrolled in the UTT program survived longer than patients enrolled in the differed treatment program (log rank X2 test = 4.1, p value = 0.04). Age, residence, base line CD4 count, program of enrolment, development of new OIS and treatment failure were predicted mortality from HIV infection.

CONCLUSION

Mortality was significantly reduced after UTT. Therefore, intervention to further reduce deaths has to focus on early initiation of treatment and strengthening UTT programs.

Comparison of HIV prevalence among antenatal clinic attendees estimated from routine testing and unlinked anonymous testing

In 2015, WHO and UNAIDS released new guidance recommending that countries transition from conducting antenatal clinic (ANC) unlinked anonymous testing (ANC-UAT) for tracking HIV prevalence trends among pregnant women to using ANC routine testing (ANC-RT) data, which are more consistent and economic to collect. This transition could pose challenges for distinguishing whether changes in observed prevalence are due to a change in underlying population prevalence or due to a change in the testing approach. We compared the HIV prevalence measured from ANC-UAT and ANCRT in 15 countries that had both data sources in overlapping years. We used linear mixed-e effects model (LMM) to estimate the RT-to-UAT calibration parameter as well as other unobserved quantities. We summarized the results at different levels of aggregation (e.g., country, urban, rural, and province). Based on our analysis, the HIV prevalence measured by ANC-UAT and ANC-RT data are consistent in most countries. Therefore, if large discrepancy is observed between ANC-UAT and ANC-RT at the same location, we recommend that people should be cautious and investigate the reason. For countries that lack information to estimate the calibration parameter, we propose an informative prior distribution of mean 0 and standard deviation 0.2 for the RT-to-UAT calibration parameter.

The Estimation and Projection Package Age-Sex Model and the r-hybrid model: new tools for estimating HIV incidence trends in sub-Saharan Africa

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.

Economic and epidemiologic impact of guidelines for early ART initiation irrespective of CD4 count in Spain

INTRODUCTION

Emerging data suggest that early antiretroviral therapy (ART) could reduce serious AIDS and non-AIDS events and deaths but could also increase costs. In January 2016, the Spanish guidelines were updated to recommend ART at any CD4 count. However, the epidemiologic and economic impacts of early ART initiation in Spain remain unclear.

METHODS

The Johns Hopkins HIV Economic-Epidemiologic Mathematical Model (JHEEM) was utilized to estimate costs, transmissions, and outcomes in Spain over 20 years. We compared implementation of guidelines for early ART initiation to a counterfactual scenario deferring ART until CD4-counts fall below 350 cells/mm3. We additionally studied the impact of early ART initiation in combination with improvements to HIV screening, care linkage and engagement.

RESULTS

Early ART initiation (irrespective of CD4-count) is expected to avert 20,100 [95% Uncertainty Range (UR) 11,100-83,000] new HIV cases over the next two decades compared to delayed ART (28% reduction), at an incremental health system cost of €1.05 billion [€0.66 - €1.63] billion, and an incremental cost-effectiveness ratio (ICER) of €29,700 [€13,700 - €41,200] per QALY gained. Projected ICERs declined further over longer time horizon; e.g., an ICER of €12,691 over 30 years. Furthermore, the impact of early ART initiation was potentiated by improved HIV screening among high-risk individuals, averting an estimated 41,600 [23,200-172,200] HIV infections (a 58% decline) compared to delayed ART.

CONCLUSIONS

Recommendations for ART initiation irrespective of CD4-counts are cost-effective and could avert > 30% of new cases in Spain. Improving HIV diagnosis can amplify this impact.

Estimating recent HIV incidence among young men who have sex with men: Reinvigorating, validating and implementing Osmond's algorithm for behavioral imputation

HIV incidence information is essential for epidemic monitoring and evaluating preventive interventions. However, reliable HIV incidence data is difficult to obtain, especially among marginalized populations, such as young men who have sex with men (YMSM). Here we evaluate the reliability of an alternative HIV incidence assessment method, behavioral imputation, as compared to serologically estimated HIV incidence. Recent HIV incidence among YMSM (aged 18 to 21 and 18 to 24 years) enrolled in a cohort study in Bangkok from 2006 to 2014 was estimated using two mid-point methods for seroconversion: 1) between age of first anal intercourse and first HIV-positive test (without previous HIV-negative test) (behavioral imputation) and 2) between the date of last negative and first positive HIV test (serological estimation). Serologically estimated HIV incidence was taken as the "gold standard" to evaluate between-method agreement. At baseline, 314 YMSM age 18 to 21 years accumulated 674 person-years (PY) of follow-up since first anal intercourse. Considering that 50 men had prevalent HIV infection, the behaviorally imputed HIV incidence was 7.4 per 100 PY. Of the remaining 264 HIV-negative men, 54 seroconverted for HIV infection during the study, accumulating 724 PY of follow-up and a serologically estimated HIV incidence of 7.5 per 100 PY. At baseline, 712 YMSM age 18 to 24 years (including 18 to 21-year-old men analyzed above) accumulated 2143 PY of follow-up since first anal intercourse. Considering that 151 men had prevalent HIV infection, the behaviorally imputed HIV incidence was 7.0 per 100 PY. Of the remaining 561 HIV-negative men, 125 seroconverted for HIV infection during the study, accumulating 1700 PY of follow-up and a serologically estimated HIV incidence of 7.4 per 100 PY. Behavioral imputation and serological estimation are in good agreement when estimating recent HIV incidence in YMSM.

Probabilistic population projections for countries with generalized HIV/AIDS epidemics

In 2015, the United Nations (UN) issued probabilistic population projections for all countries up to 2100, by simulating future levels of total fertility and life expectancy and combining the results using a standard cohort component projection method. For the 40 countries with generalized HIV/AIDS epidemics, the mortality projections used the Spectrum/Estimation and Projection Package (EPP) model, a complex, multistate model designed for short-term projections of policy-relevant quantities for the epidemic. We propose a simpler approach that is more compatible with existing UN projection methods for other countries. Changes in life expectancy are projected probabilistically using a simple time series regression and then converted to age- and sex-specific mortality rates using model life tables designed for countries with HIV/AIDS epidemics. These are then input to the cohort component method, as for other countries. The method performed well in an out-of-sample cross-validation experiment. It gives similar short-run projections to Spectrum/EPP, while being simpler and avoiding multistate modelling.

Test-and-treat approach to HIV/AIDS: a primer for mathematical modeling

The public benefit of test-and-treat has induced a need to justify goodness for the public, and mathematical modeling studies have played a key role in designing and evaluating the test-and-treat strategy for controlling HIV/AIDS. Here we briefly and comprehensively review the essence of contemporary understanding of the test-and-treat policy through mathematical modeling approaches and identify key pitfalls that have been identified to date. While the decrease in HIV incidence is achieved with certain coverages of diagnosis, care and continued treatment, HIV prevalence is not necessarily decreased and sometimes the test-and-treat is accompanied by increased long-term cost of antiretroviral therapy (ART). To confront with the complexity of assessment on this policy, the elimination threshold or the effective reproduction number has been proposed for its use in determining the overall success to anticipate the eventual elimination. Since the publication of original model in 2009, key issues of test-and-treat modeling studies have been identified, including theoretical problems surrounding the sexual partnership network, heterogeneities in the transmission dynamics, and realistic issues of achieving and maintaining high treatment coverage in the most hard-to-reach populations. To explicitly design country-specific control policy, quantitative modeling approaches to each single setting with differing epidemiological context would require multi-disciplinary collaborations among clinicians, public health practitioners, laboratory technologists, epidemiologists and mathematical modelers.

Modular programming for tuberculosis control, the "AuTuMN" platform

BACKGROUND

Tuberculosis (TB) is now the world's leading infectious killer and major programmatic advances will be needed if we are to meet the ambitious new End TB Targets. Although mathematical models are powerful tools for TB control, such models must be flexible enough to capture the complexity and heterogeneity of the global TB epidemic. This includes simulating a disease that affects age groups and other risk groups differently, has varying levels of infectiousness depending upon the organ involved and varying outcomes from treatment depending on the drug resistance pattern of the infecting strain.

RESULTS

We adopted sound basic principles of software engineering to develop a modular software platform for simulation of TB control interventions ("AuTuMN"). These included object-oriented programming, logical linkage between modules and consistency of code syntax and variable naming. The underlying transmission dynamic model incorporates optional stratification by age, risk group, strain and organ involvement, while our approach to simulating time-variant programmatic parameters better captures the historical progression of the epidemic. An economic model is overlaid upon this epidemiological model which facilitates comparison between new and existing technologies. A "Model runner" module allows for predictions of future disease burden trajectories under alternative scenario situations, as well as uncertainty, automatic calibration, cost-effectiveness and optimisation. The model has now been used to guide TB control strategies across a range of settings and countries, with our modular approach enabling repeated application of the tool without the need for extensive modification for each application.

CONCLUSIONS

The modular construction of the platform minimises errors, enhances readability and collaboration between multiple programmers and enables rapid adaptation to answer questions in a broad range of contexts without the need for extensive re-programming. Such features are particularly important in simulating an epidemic as complex and diverse as TB.

Bayesian projection of life expectancy accounting for the HIV/AIDS epidemic

Background

While probabilistic projection methods for projecting life expectancy exist, few account for covariates related to life expectancy. Generalized HIV/AIDS epidemics have a large, immediate negative impact on the life expectancy in a country, but this impact can be mitigated by widespread use of antiretroviral therapy (ART). Thus, projection methods for countries with generalized HIV/AIDS epidemics could be improved by accounting for HIV prevalence, the future course of the epidemic, and ART coverage.

Methods

We extend the current Bayesian probabilistic life expectancy projection methods of Raftery et al. (2013) to account for HIV prevalence and adult ART coverage in countries with generalized HIV/AIDS epidemics.

Results

We evaluate our method using out-of-sample validation. We find that the proposed method performs better than the method that does not account for HIV prevalence or ART coverage for projections of life expectancy in countries with a generalized epidemic, while projections for countries without an epidemic remain essentially unchanged.

Conclusions

In general, our projections show rapid recovery to pre-epidemic life expectancy levels in the presence of widespread ART coverage. After the initial life expectancy recovery, we project a steady rise in life expectancy until the end of the century.

Contribution

We develop a simple Bayesian hierarchical model for long-term projections of life expectancy while accounting for HIV/AIDS prevalence and coverage of ART. The method produces well-calibrated projections for countries with generalized HIV/AIDS epidemics up to 2100 while having limited data demands.

Stroke in HIV-infected individuals with and without HCV coinfection in Spain in the combination antiretroviral therapy era

The incidence of stroke in human immunodeficiency virus (HIV)–infected individuals has been well analyzed in recent epidemiological studies. However, little is known about the specific contribution of hepatitis C virus (HCV) infection to stroke among HIV-infected individuals. The aims of this study were to analyze trends in the incidence rates of stroke in HIV-infected individuals during the combination antiretroviral (cART) era in Spain and to categorize them by the presence or absence of HCV coinfection. We analyzed hospital discharges with a diagnosis of stroke in Spain according to ICD-9-CM during 1997–2013. The study period was divided into four calendar periods (1997–1999, 2000–2003, 2004–2007, and 2008–2013). Patients were classified according to HCV serology. The number of HIV-infected patients was estimated based on data from the National Centre of Epidemiology. We calculated incidence rates (events per 10,000 patient-years) and in-hospital case fatality rates (CFR). The incidence of hemorrhagic stroke (HS) decreased in HIV-monoinfected patients (15.8 [1997–1999] to 6.5 [2008–2013]; P<0.001) and increased in HIV/HCV-coinfected patients (1.3 [1997–1999] to 5.5 [2008–2013]; P<0.001). The incidence of ischemic stroke (IS) decreased in HIV-monoinfected patients (27.4 [1997–1999] to 21.7 [2008–2013]; P = 0.005) and increased in HIV/HCV-coinfected patients (1.8 [1997–1999] to 11.9 [2008–2013]; P<0.001). The CFR was 3.3 times higher for HS than for IS for the whole study period. The CFR of HS in HIV-monoinfected patients decreased significantly (47.4% [1997–1999] to 30.6% [2008–2013]; P = 0.010) but did not change significantly among HIV/HCV-coinfected patients (41.4% [1997–1999] to 44.7% [2008–2013]; P = 0.784). The CFR of IS in the whole HIV-infected population decreased significantly (14.6% [1997–1999] to 10.9% [2008–2013]; P = 0.034), although no significant differences were found when each group was analyzed separately. In conclusion, after the introduction of cART, HS and IS rates decreased in HIV-monoinfected individuals, but increased steadily in HIV/HCV-coinfected individuals.

Surveillance and response for high-risk populations: what can malaria elimination programmes learn from the experience of HIV?

To eliminate malaria, malaria programmes need to develop new strategies for surveillance and response appropriate for the changing epidemiology that accompanies transmission decline, in which transmission is increasingly driven by population subgroups whose behaviours place them at increased exposure. Conventional tools of malaria surveillance and response are likely not sufficient in many elimination settings for accessing high-risk population subgroups, such as mobile and migrant populations (MMPs), given their greater likelihood of asymptomatic infections, illegal risk behaviours, limited access to public health facilities, and high mobility including extended periods travelling away from home. More adaptive, targeted strategies are needed to monitor transmission and intervention coverage effectively in these groups. Much can be learned from HIV programmes’ experience with “second generation surveillance”, including how to rapidly adapt surveillance and response strategies to changing transmission patterns, biological and behavioural surveys that utilize targeted sampling methods for specific behavioural subgroups, and methods for population size estimation. This paper reviews the strategies employed effectively for HIV programmes and offers considerations and recommendations for adapting them to the malaria elimination context.

Producing HIV estimates: from global advocacy to country planning and impact measurement

BACKGROUND

The development of global HIV estimates has been critical for understanding, advocating for and funding the HIV response. The process of generating HIV estimates has been cited as the gold standard for public health estimates.

OBJECTIVE

This paper provides important lessons from an international scientific collaboration and provides a useful model for those producing public health estimates in other fields.

DESIGN

Through the compilation and review of published journal articles, United Nations reports, other documents and personal experience we compiled historical information about the estimates and identified potential lessons for other public health estimation efforts.

RESULTS

Through the development of core partnerships with country teams, implementers, demographers, mathematicians, epidemiologists and international organizations, UNAIDS has led a process to develop the capacity of country teams to produce internationally comparable HIV estimates. The guidance provided by these experts has led to refinements in the estimated numbers of people living with HIV, new HIV infections and AIDS-related deaths over the past 20 years. A number of important updates to the methods since 1997 resulted in fluctuations in the estimated levels, trends and impact of HIV. The largest correction occurred between the 2005 and 2007 rounds with the additions of household survey data into the models. In 2001 the UNAIDS models at that time estimated there were 40 million people living with HIV. In 2016, improved models estimate there were 30 million (27.6-32.7 million) people living with HIV in 2001.

CONCLUSIONS

Country ownership of the estimation tools has allowed for additional uses of the results than had the results been produced by researchers or a team in Geneva. Guidance from a reference group and input from country teams have led to critical improvements in the models over time. Those changes have improved countries' and stakeholders' understanding of the HIV epidemic.

Trends in Epidemiology of COPD in HIV-Infected Patients in Spain (1997-2012)

Purpose

The aim of this study was to estimate trends of incidence of hospital admissions and in-hospital mortality (IHM) in HIV-infected patients with COPD in the combination antiretroviral therapy (cART) era in Spain (1997–2012).

Methods

A retrospective study with data from nationwide population-based COPD diagnoses in the Spanish Minimum Basic Data Set (MBDS) was performed. We established groups according to their HIV and HCV infections: 1) HIV-uninfected patients; 2) HIV-infected patients (with or without HCV coinfection).

Results

1,580,207 patients discharge with a COPD diagnosis were included in the study, 8902 of them were HIV-infected patients (5000 HIV-monoinfected patients and 3902 HIV/HCV-coinfected patients). The HIV-infected patients had higher incidence rates of hospital admissions for COPD than the HIV-uninfected patients during the study period. The HIV-monoinfected patients had higher rates of hospitalizations for COPD than the HIV/HCV-coinfected patients in the early-period cART (1997–1999), but these rates decreased in the first group and increased in the second, being even similar in both groups in the late-period cART (2004–2011). On the other hand, the HIV-infected patients with COPD had higher IHM than the HIV-uninfected patients with COPD. The mortality rates were higher in the HIV-monoinfected patients with COPD than in the HIV/HCV-coinfected patients with COPD in the early-period cART; however, in the late-period cART, the mortality rates trends seems higher in the HIV/HCV group. The likelihood of death in HIV/HCV-coinfected patients with COPD was similar to than in HIV-monoinfected patients with COPD.

Conclusions

Incidence of hospital admissions for COPD and IHM have decreased among HIV-monoinfected individuals but have increased steadily among HIV/HCV-coinfected individuals in the cART era.

Human Resources for Treating HIV/AIDS: Are the Preventive Effects of Antiretroviral Treatment a Game Changer?

Shortages of human resources for treating HIV/AIDS (HRHA) are a fundamental barrier to reaching universal antiretroviral treatment (ART) coverage in developing countries. Previous studies suggest that recruiting HRHA to attain universal ART coverage poses an insurmountable challenge as ART significantly increases survival among HIV-infected individuals. While new evidence about ART's prevention benefits suggests fewer infections may mitigate the challenge, new policies such as treatment-as-prevention (TasP) will exacerbate it. We develop a mathematical model to analytically study the net effects of these countervailing factors. Using South Africa as a case study, we find that contrary to previous results, universal ART coverage is achievable even with current HRHA numbers. However, larger health gains are possible through a surge-capacity policy that aggressively recruits HRHA to reach universal ART coverage quickly. Without such a policy, TasP roll-out can increase health losses by crowding out sicker patients from treatment, unless a surge capacity exclusively for TasP is also created.

Estimating HIV incidence among key affected populations in China from serial cross-sectional surveys in 2010-2014

Introduction

HIV incidence is an important measure for monitoring the development of the epidemic, but it is difficult to ascertain. We combined serial HIV prevalence and mortality data to estimate HIV incidence among key affected populations (KAPs) in China.

Methods

Serial cross-sectional surveys were conducted among KAPs from 2010 to 2014. Trends in HIV prevalence were assessed by the Cochran-Armitage test, adjusted by risk group. HIV incidence was estimated from a mathematical model that describes the relationship between changes in HIV incidence with HIV prevalence and mortality.

Results

The crude HIV prevalence for the survey samples remained stable at 1.1 to 1.2% from 2010 to 2014. Among drug users (DUs), HIV prevalence declined from 4.48 to 3.29% (p<0.0001), and among men who have sex with men (MSM), HIV prevalence increased from 5.73 to 7.75% (p<0.0001). Changes in HIV prevalence among female sex workers (FSWs) and male patients of sexually transmitted disease clinics were more modest but remained statistically significant (all p<0.0001). The MSM population had the highest incidence estimates at 0.74% in 2011, 0.59% in 2012, 0.57% in 2013 and 0.53% in 2014. Estimates of the annual incidence for DUs and FSWs were very low and may not be reliable.

Conclusions

Serial cross-sectional prevalence data from representative samples may be another approach to construct approximate estimates of national HIV incidence among key populations. We observed that the MSM population had the highest incidence for HIV among high-risk groups in China, and we suggest that interventions targeting MSM are urgently needed to curb the growing HIV epidemic.

The continuum of HIV care in Catalonia

The objective was to produce a cascade of care for Catalonia to gain a public health perspective on the overall quality of HIV services and allow comparison with other countries. It was constructed using the Integrated Epidemiological Surveillance System of HIV in Catalonia and data from the PISCIS Cohort. Estimates of the number of people living with HIV in Catalonia are modelled using Spectrum Projection Package 2011 (UNAIDS/WHO). Totals for each stage in the cascade are obtained by applying to the preceding stage a proportion estimated from available surveillance and cohort data. Undiagnosed HIV was estimated from the European literature. The proportions retained in care, on ART and virally suppressed were derived from the PISCIS cohort. Programmatic data on ART consumption was used to validate estimates. By the end of 2011 there were about 33,000 people living with HIV in Catalonia, 71% of which had been both diagnosed and linked to care. We estimate that 61% of all HIV infected persons were retained in care, 56% were on ART and 48% were virally suppressed. These figures data are comparable, although slightly lower, than that of France or the UK. The Cascade of HIV Care in Catalonia is similar to other western European countries such as France and the UK. Direct estimates of the undiagnosed HIV population and linkage to care are desirable but the contribution of cohort data to the cascade highlights their continued importance in HIV surveillance and design of evidence-based health strategies.

A Comparison of South African National HIV Incidence Estimates: A Critical Appraisal of Different Methods

BACKGROUND

The interpretation of HIV prevalence trends is increasingly difficult as antiretroviral treatment programs expand. Reliable HIV incidence estimates are critical to monitoring transmission trends and guiding an effective national response to the epidemic.

METHODS AND FINDINGS

We used a range of methods to estimate HIV incidence in South Africa: (i) an incidence testing algorithm applying the Limiting-Antigen Avidity Assay (LAg-Avidity EIA) in combination with antiretroviral drug and HIV viral load testing; (ii) a modelling technique based on the synthetic cohort principle; and (iii) two dynamic mathematical models, the EPP/Spectrum model package and the Thembisa model. Overall, the different incidence estimation methods were in broad agreement on HIV incidence estimates among persons aged 15-49 years in 2012. The assay-based method produced slightly higher estimates of incidence, 1.72% (95% CI 1.38 - 2.06), compared with the mathematical models, 1.47% (95% CI 1.23 - 1.72) in Thembisa and 1.52% (95% CI 1.43 - 1.62) in EPP/Spectrum, and slightly lower estimates of incidence compared to the synthetic cohort, 1.9% (95% CI 0.8 - 3.1) over the period from 2008 to 2012. Among youth aged 15-24 years, a declining trend in HIV incidence was estimated by all three mathematical estimation methods.

CONCLUSIONS

The multi-method comparison showed similar levels and trends in HIV incidence and validated the estimates provided by the assay-based incidence testing algorithm. Our results confirm that South Africa is the country with the largest number of new HIV infections in the world, with about 1 000 new infections occurring each day among adults aged 15-49 years in 2012.

Trends in nontuberculous mycobacterial disease in hospitalized subjects in Spain (1997-2010) according to HIV infection

OBJECTIVES

The aim of the study was to estimate the incidence of nontuberculous mycobacterial (NTM) disease and the rate of NTM disease-related mortality and to analyse trends in these variables according to HIV infection.

METHODS

We performed a retrospective study for the period 1997-2010 using data from the Minimum Basic Data Set (MBDS) provided by the Spanish Ministry of Health. The exposure variables were: (i) HIV infection (HIV positive versus HIV negative); (ii) calendar period in relation to widespread use of combination antiretroviral therapy (cART) [1997-1999 (early cART period), 2000-2003 (middle cART period) and 2004-2010 (late cART period)]. The outcome variables were (i) new NTM disease diagnosis and (ii) mortality.

RESULTS

A total of 3729 cases of incident NTM disease were collected in MBDS, 1795 in the HIV-negative group and 1934 in the HIV-positive group, among whom 602 deaths occurred, 223 in the HIV-negative group and 379 in the HIV-positive group. The incidence of NTM disease and the rate of NTM disease-related mortality were 1000-fold higher in the HIV-positive group than in the HIV-negative group. Regarding the incidence of NTM disease, in the HIV-negative group the incidence increased from 2.91 to 3.97 events per 1,000,000 patient-years from 1997-1999 to 2004-2010 (P < 0.001), while in the HIV-positive group the incidence decreased from 2.29 to 0.71 events per 1000 patient-years from 1997-1999 to 2004-2010 (P < 0.001). Regarding mortality, in the HIV-negative group mortality increased from 2.63 to 4.26 events per 10,000,000 patient-years from 1997-1999 to 2000-2003 (P = 0.059), and then the rate stabilized at around 3.87 events per 10,000,000 patient-years in 2004-2010 (P = 0.128), while in the HIV-positive group mortality decreased from 4.28 to 1.39 events per 10,000 patient-years from 1997-1999 to 2004-2010 (P < 0.001).

CONCLUSIONS

HIV infection was associated with a higher NTM disease incidence and higher NTM disease-related mortality than in the general population, but these rates decreased in the HIV-positive group from 1997-1999 to 2004-2010, whereas the NTM disease incidence increased in the HIV-negative group.

Use of surveillance data on HIV diagnoses with HIV-related symptoms to estimate the number of people living with undiagnosed HIV in need of antiretroviral therapy

Background

It is important to have methods available to estimate the number of people who have undiagnosed HIV and are in need of antiretroviral therapy (ART).

Methods

The method uses the concept that a predictable level of occurrence of AIDS or other HIV-related clinical symptoms which lead to presentation for care, and hence diagnosis of HIV, arises in undiagnosed people with a given CD4 count. The method requires surveillance data on numbers of new HIV diagnoses with HIV-related symptoms, and the CD4 count at diagnosis. The CD4 count-specific rate at which HIV-related symptoms develop are estimated from cohort data. 95% confidence intervals can be constructed using a simple simulation method.

Results

For example, if there were 13 HIV diagnoses with HIV-related symptoms made in one year with CD4 count at diagnosis between 150–199 cells/mm³, then since the CD4 count-specific rate of HIV-related symptoms is estimated as 0.216 per person-year, the estimated number of person years lived in people with undiagnosed HIV with CD4 count 150–199 cells/mm3 is 13/0.216 = 60 (95% confidence interval: 29–100), which is considered an estimate of the number of people living with undiagnosed HIV in this CD4 count stratum.

Conclusions

The method is straightforward to implement within a short period once a surveillance system of all new HIV diagnoses, collecting data on HIV-related symptoms at diagnosis, is in place and is most suitable for estimating the number of undiagnosed people with CD4 count <200 cells/mm3 due to the low rate of developing HIV-related symptoms at higher CD4 counts. A potential source of bias is under-diagnosis and under-reporting of diagnoses with HIV-related symptoms. Although this method has limitations as with all approaches, it is important for prompting increased efforts to identify undiagnosed people, particularly those with low CD4 count, and for informing levels of unmet need for ART.

Recalibration of the limiting antigen avidity EIA to determine mean duration of recent infection in divergent HIV-1 subtypes

Background

Mean duration of recent infection (MDRI) and misclassification of long-term HIV-1 infections, as proportion false recent (PFR), are critical parameters for laboratory-based assays for estimating HIV-1 incidence. Recent review of the data by us and others indicated that MDRI of LAg-Avidity EIA estimated previously required recalibration. We present here results of recalibration efforts using >250 seroconversion panels and multiple statistical methods to ensure accuracy and consensus.

Methods

A total of 2737 longitudinal specimens collected from 259 seroconverting individuals infected with diverse HIV-1 subtypes were tested with the LAg-Avidity EIA as previously described. Data were analyzed for determination of MDRI at ODn cutoffs of 1.0 to 2.0 using 7 statistical approaches and sub-analyzed by HIV-1 subtypes. In addition, 3740 specimens from individuals with infection >1 year, including 488 from patients with AIDS, were tested for PFR at varying cutoffs.

Results

Using different statistical methods, MDRI values ranged from 88–94 days at cutoff ODn = 1.0 to 177–183 days at ODn = 2.0. The MDRI values were similar by different methods suggesting coherence of different approaches. Testing for misclassification among long-term infections indicated that overall PFRs were 0.6% to 2.5% at increasing cutoffs of 1.0 to 2.0, respectively. Balancing the need for a longer MDRI and smaller PFR (<2.0%) suggests that a cutoff ODn = 1.5, corresponding to an MDRI of 130 days should be used for cross-sectional application. The MDRI varied among subtypes from 109 days (subtype A&D) to 152 days (subtype C).

Conclusions

Based on the new data and revised analysis, we recommend an ODn cutoff = 1.5 to classify recent and long-term infections, corresponding to an MDRI of 130 days (118–142). Determination of revised parameters for estimation of HIV-1 incidence should facilitate application of the LAg-Avidity EIA for worldwide use.

Estimating HIV incidence from case-report data: method and an application in Colombia

Objective:

Quantifying HIV incidence is essential for tracking epidemics but doing this in concentrated epidemic can be a particular challenge because of limited consistent high-quality data about the size, behaviour and prevalence of HIV among key populations. Here, we examine a method for estimating HIV incidence from routinely collected case-reporting data.

Methods:

A flexible model of HIV infection, diagnosis and survival is constructed and fit to time-series data on the number of reported cases in a Bayesian framework. The time trend in the hazard of infection is specified by a penalized B-spline. We examine the performance of the model by applying it to synthetic data and determining whether the method is capable of recovering the input incidence trend. We then apply the method to real data from Colombia and compare our estimates of incidence with those that have been derived using alternative methods.

Results:

The method can feasibly be applied and it successfully recovered a range of incidence trajectories in synthetic data experiments. However, estimates for incidence in the recent past are highly uncertain. When applied to data from Colombia, a credible trajectory of incidence is generated which indicates a much lower historic level of HIV incidence than has previously been estimated using other methods.

Conclusion:

It is feasible, though not satisfactory, to estimate incidence using case-report data in settings with good data availability. Future work should examine the impact on missing or biased data, the utility of alternative formulations of flexible functions specifying incidence trends, and the benefit of also including data on deaths and programme indicators such as the numbers receiving antiretroviral therapy.

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

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 -9-38%) more in pregnant women than nonpregnant women. Estimates were similar in Western, Eastern, and Southern regions of SSA; none were statistically significant (P>0.05). 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.

Updates to the spectrum model to estimate key HIV indicators for adults and children

Background:

The Spectrum program is used to estimate key HIV indicators for national programmes. The purpose of the study is to describe the key updates made to Spectrum in the last 2 years to produce the version used in the 2013 global estimates of HIV/AIDS.

Methods:

The United Nations Programme on HIV/AIDS (UNAIDS) Reference Group on Estimates, Models and Projections regularly reviews new data and information needs and recommends updates to the methodology and assumptions used in Spectrum. The latest data from surveys, census and special studies are used to estimate key parameter values for countries and regions.

Results:

Country-specific life tables prepared by the United National Population Division (UNPD) have been incorporated into Spectrum's demographic projections replacing the model life tables used previously. This update includes revised estimates of non-AIDS life expectancy. Incidence among all adults 15–49 years generated from curve fitting to surveillance and survey data is now split by age using incidence rate ratios derived from Analysing Longitudinal Population-based HIV/AIDS data on Africa Network data for generalized epidemics. Methods for estimating the number of AIDS orphans have been updated to include the changing effects of PMTCT and antiretroviral therapy programmes. Procedures for estimating the number of adults eligible for treatment have been updated to reflect the 2013 WHO guidelines. Program data on AIDS mortality has been used to estimate prevalence trends in Argentina, Brazil and Mexico for the 2013 estimates.

Conclusion:

Spectrum was updated for the 2013 round of HIV estimates in order to support national programmes with improved methods and data to estimating national indicators.

A user-friendly, open-source tool to project impact and cost of diagnostic tests for tuberculosis

Most models of infectious diseases, including tuberculosis (TB), do not provide results customized to local conditions. We created a dynamic transmission model to project TB incidence, TB mortality, multidrug-resistant (MDR) TB prevalence, and incremental costs over 5 years after scale-up of nine alternative diagnostic strategies. A corresponding web-based interface allows users to specify local costs and epidemiology. In settings with little capacity for up-front investment, same-day microscopy had the greatest impact on TB incidence and became cost-saving within 5 years if delivered at $10/test. With greater initial investment, population-level scale-up of Xpert MTB/RIF or microcolony-based culture often averted 10 times more TB cases than narrowly-targeted strategies, at minimal incremental long-term cost. Xpert for smear-positive TB had reasonable impact on MDR-TB incidence, but at substantial price and little impact on overall TB incidence and mortality. This user-friendly modeling framework improves decision-makers' ability to evaluate the local impact of TB diagnostic strategies.

DOI:http://dx.doi.org/10.7554/eLife.02565.001

Tuberculosis is an infectious bacterial disease caused predominantly by the microorganism Mycobacterium tuberculosis. Although the number of deaths from tuberculosis has been falling in recent years, the disease still kills more than 1 million people every year, mainly in developing countries. Tuberculosis can be treated with antibiotics, but the emergence of bacteria that are resistant to existing drugs is threatening efforts to eradicate the disease.

Preventing the spread of tuberculosis is heavily dependent on accurate diagnosis of individuals with the disease. This is challenging because the initial symptoms are often mild, usually just a cough, which means that someone can spread the disease to many others over a period of several months before the symptoms become worse—fever, night sweats, and weight loss—and they realize that they are sick. Multiple diagnostic strategies are available, from the relatively low-tech—examining sputum samples under a microscope to detect tuberculosis bacteria—to more sophisticated tests that can detect bacterial DNA and determine whether the bacteria are drug-resistant in less than 2 hr.

Choosing which diagnostic strategy to adopt can be challenging because the optimal solution in a region will depend on the specific local conditions. To overcome this problem, Dowdy et al. have developed a computer program that enables decision-makers to input four key parameters that describe the tuberculosis situation in their region, and to obtain 5-year projections of the rate of new infections, mortality, and total costs likely to result from adopting any of nine different diagnostic strategies.

The four parameters are the number of new cases of tuberculosis each year (incidence), the proportion of new cases that are multi-drug resistant, the proportion of the adult population that has HIV, and the local costs of various diagnostic techniques and treatments. Since the entire computer program is written in a freely available open-source programming language (Python), any user can tweak these parameters to provide a more precise fit to their own region. Alternatively, the standard version of the program can be run directly from a website without any need to interact with computer code.

This model is the first to enable local decision-makers to evaluate the impact of different diagnostic strategies for tuberculosis under the conditions specific to their region. The model predicts, for example, that in areas where there is little money available for up-front investment, same-day microscopy analysis of sputum samples and starting patients on treatment is the most cost-effective strategy for reducing the rate of new infections. Given the wide variation in conditions within even small geographical areas, this more flexible approach should lead to the more efficient use of resources and may, ultimately, help to reduce the spread of tuberculosis.

DOI:http://dx.doi.org/10.7554/eLife.02565.002

Modeling age-specific mortality for countries with generalized HIV epidemics

BACKGROUND

In a given population the age pattern of mortality is an important determinant of total number of deaths, age structure, and through effects on age structure, the number of births and thereby growth. Good mortality models exist for most populations except those experiencing generalized HIV epidemics and some developing country populations. The large number of deaths concentrated at very young and adult ages in HIV-affected populations produce a unique 'humped' age pattern of mortality that is not reproduced by any existing mortality models. Both burden of disease reporting and population projection methods require age-specific mortality rates to estimate numbers of deaths and produce plausible age structures. For countries with generalized HIV epidemics these estimates should take into account the future trajectory of HIV prevalence and its effects on age-specific mortality. In this paper we present a parsimonious model of age-specific mortality for countries with generalized HIV/AIDS epidemics.

METHODS AND FINDINGS

The model represents a vector of age-specific mortality rates as the weighted sum of three independent age-varying components. We derive the age-varying components from a Singular Value Decomposition of the matrix of age-specific mortality rate schedules. The weights are modeled as a function of HIV prevalence and one of three possible sets of inputs: life expectancy at birth, a measure of child mortality, or child mortality with a measure of adult mortality. We calibrate the model with 320 five-year life tables for each sex from the World Population Prospects 2010 revision that come from the 40 countries of the world that have and are experiencing a generalized HIV epidemic. Cross validation shows that the model is able to outperform several existing model life table systems.

CONCLUSIONS

We present a flexible, parsimonious model of age-specific mortality for countries with generalized HIV epidemics. Combined with the outputs of existing epidemiological and demographic models, this model makes it possible to project future age-specific mortality profiles and number of deaths for countries with generalized HIV epidemics.

High HIV incidence in the postpartum period sustains vertical transmission in settings with generalized epidemics: a cohort study in Southern Mozambique

INTRODUCTION

Acute infection with HIV in the postpartum period results in a high risk of vertical transmission through breastfeeding. A study was done to determine the HIV incidence rate and associated risk factors among postpartum women in Southern Mozambique, where HIV prevalence among pregnant women is 21%.

METHODS

A prospective cohort study was conducted in six rural health facilities in Gaza and Maputo provinces from March 2008 to July 2011. A total of 1221 women who were HIV-negative on testing at delivery or within two months postpartum were recruited and followed until 18 months postpartum. HIV testing, collection of dried blood spot samples and administration of a structured questionnaire to women were performed every three months. Infant testing by DNA-PCR was done as soon as possible after identification of a new infection in women. HIV incidence was estimated, and potential risk factors at baseline were compared using Poisson regression.

RESULTS

Data from 957 women were analyzed with follow-up after the enrolment visit, with a median follow-up of 18.2 months. The HIV incidence in postpartum women is estimated at 3.20/100 women-years (95% CI: 2.30-4.46), with the highest rate among 18- to 19-year-olds (4.92 per 100 women-years; 95% CI: 2.65-9.15). Of the new infections, 14 (34%) were identified during the first six months postpartum, 11 (27%) between 6 and 12 months and 16 (39%) between 12 and 18 months postpartum. Risk factors for incident HIV infection include young age, low number of children, higher education level of the woman's partner and having had sex with someone other than one's partner. The vertical transmission was 21% (95% CI: 5-36) among newly infected women.

CONCLUSIONS

Incidence of HIV is high among breastfeeding women in Southern Mozambique, contributing to increasing numbers of HIV-infected infants. Comprehensive primary prevention strategies targeting women of reproductive age, particularly pregnant and postpartum women and their partners, will be crucial for the elimination of paediatric AIDS in Africa.

Evaluation of the false recent classification rates of multiassay algorithms in estimating HIV type 1 subtype C incidence

Laboratory cross-sectional assays are useful for the estimation of HIV incidence, but are known to misclassify individuals with long-standing infection as recently infected. The false recent rate (FRR) varies widely across geographic areas; therefore, accurate estimates of HIV incidence require a locally defined FRR. We determined FRR for Botswana, where HIV-1 subtype C infection is predominant, using the BED capture enzyme immunoassay (BED), a Bio-Rad Avidity Index (BAI) assay (a modification of the Bio-Rad HIV1/2+O EIA), and two multiassay algorithms (MAA) that included clinical data. To estimate FRR, stored blood samples from 512 antiretroviral (ARV)-naive HIV-1 subtype C-infected individuals from a prospective cohort in Botswana were tested at 18-24 months postenrollment. The following FRR mean (95% CI) values were obtained: BED 6.05% (4.15-8.48), BAI 5.57% (3.70-8.0), BED-BAI 2.25% (1.13-4.0), and a combination of BED-BAI with CD4 (>200) and viral load (>400) threshold 1.43% (0.58-2.93). The interassay agreement between BED and BAI was 92.8% (95% CI, 90.1-94.5) for recent/long-term classification. Misclassification was associated with viral suppression for BED [adjusted OR (aOR) 10.31; p=0.008], BAI [aOR 9.72; p=0.019], and MAA1 [aOR 16.6; p=0.006]. Employing MAA can reduce FRR to <2%. A local FRR can improve cross-sectional HIV incidence estimates.

Spline-based modelling of trends in the force of HIV infection, with application to the UNAIDS Estimation and Projection Package

Objective

We previously developed a flexible specification of the UNAIDS Estimation and Projection Package (EPP) that relied on splines to generate time-varying values for the force of infection parameter. Here, we test the feasibility of this approach for concentrated HIV/AIDS epidemics with very sparse data and compare two methods for making short-term future projections with the spline-based model.

Methods

Penalised B-splines are used to model the average infection risk over time within the EPP 2011 modelling framework, which includes antiretroviral treatment effects and CD4 cell count progression, and is fit to sentinel surveillance prevalence data with a Bayesian algorithm. We compare two approaches for future projections: (1) an informative prior related to equilibrium prevalence and (2) a random walk formulation.

Results

The spline-based model produced plausible fits across a range of epidemics, which included 87 subpopulations from 14 countries with concentrated epidemics and 75 subpopulations from 33 countries with generalised epidemics. The equilibrium prior and random walk approaches to future projections yielded similar prevalence estimates, and both performed well in tests of out-of-sample predictive validity for prevalence. In contrast, in some cases the two approaches varied substantially in estimates of incidence, with the random walk formulation avoiding extreme changes in incidence.

Conclusions

A spline-based approach to allowing the force of infection parameter to vary over time within EPP 2011 is robust across a diverse array of epidemics, including concentrated ones with limited surveillance data. Future work on the EPP model should consider the impact that different modelling approaches have on estimates of HIV incidence.

Identifying and quantifying misclassified and under-reported AIDS deaths in Brazil: a retrospective analysis from 1985 to 2009

BACKGROUND

A retrospective analysis of deaths registered in the Brazilian Mortality System was conducted to quantify the under-reporting of HIV/AIDS deaths and those misclassified to AIDS-related conditions in the 15-49 years old population in Brazil.

METHODS

Death rates for AIDS-related diseases were calculated by age and sex for 1985-2009. Changes in the age-sex-specific death rates over time were used to identify conditions likely to be misclassified AIDS deaths and to quantify the corresponding number of misclassified deaths. Deaths due to ill-defined causes were redistributed across all other natural causes of death. The resulting total number of AIDS deaths was further adjusted for incompleteness of the mortality reporting system.

RESULTS

Out of the 28 potential causes of death investigated, five increased in the same distinct age pattern as AIDS: pneumonia, Kaposi's sarcoma, other immunodeficiencies, other septicaemia and toxoplasmosis. 18 490 deaths due to these five causes were recoded to HIV/AIDS from 1985 to 2009. 38 145 deaths due to ill-defined causes were redistributed to AIDS and 15 485 were added to the number of AIDS deaths to correct for completeness of the mortality system in Brazil. Altogether, 72 120 deaths were recoded to AIDS between 1985 and 2009 and added to the reported 194 445 AIDS related deaths in the country, representing 27% misclassification of AIDS deaths in Brazil.

CONCLUSIONS

This study demonstrated that AIDS mortality is underestimated by the official mortality information system in Brazil. Efforts need to be made to reduce misclassification of causes of death in the future and identify ways in which the confidentiality of information regarding cause of death can be maintained.

Focusing the HIV response through estimating the major modes of HIV transmission: a multi-country analysis

Objective

An increasing number of countries have been estimating the distribution of new adult HIV infections by modes of transmission (MOT) to help prioritise prevention efforts. We compare results from studies conducted between 2008 and 2012 and discuss their use for planning and responding to the HIV epidemic.

Methods

The UNAIDS recommended MOT model helps countries to estimate the proportion of new HIV infections that occur through key transmission modes including sex work, injecting drug use (IDU), men having sex with men (MSM), multiple sexual partnerships, stable relationships and medical interventions. The model typically forms part of a country-led process that includes a comprehensive review of epidemiological data. Recent revisions to the model are described.

Results

Modelling results from 25 countries show large variation between and within regions. In sub-Saharan Africa, new infections occur largely in the general heterosexual population because of multiple partnerships or in stable discordant relationships, while sex work contributes significantly to new infections in West Africa. IDU and sex work are the main contributors to new infections in the Middle East and North Africa, with MSM the main contributor in Latin America. Patterns vary substantially between countries in Eastern Europe and Asia in terms of the relative contribution of sex work, MSM, IDU and spousal transmission.

Conclusions

The MOT modelling results, comprehensive review and critical assessment of data in a country can contribute to a more strategically focused HIV response. To strengthen this type of research, improved epidemiological and behavioural data by risk population are needed.

National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models

Objectives

Population-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors.

Methods

For 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals.

Results

Selection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5.

Conclusions

Our analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence.

Trends in HIV prevalence among young people in generalised epidemics: implications for monitoring the HIV epidemic

Background

Countries measure trends in HIV incidence to assess the impact of HIV prevention and treatment programmes. Most countries have approximated trends in HIV incidence through modelled estimates or through trends in HIV prevalence among young people (aged 15–24 years) assuming they have recently become sexually active and have thus only been recently exposed to HIV.

Methods

Trends in HIV incidence are described and results are compared using three proxy measures of incidence: HIV prevalence among young women attending antenatal clinics (ANCs) in 22 countries; HIV prevalence among young male and female nationally representative household survey respondents in 14 countries; and modelled estimates of adult (ages 15–49 years) HIV incidence in 26 countries. The significance of changes in prevalence among ANC attendees and young survey respondents is tested.

Results

Among 26 countries, 25 had evidence of some decline in HIV incidence and 15 showed statistically significant declines in either ANC data or survey data. Only in Mozambique did the direction of the trend in young ANC attendees differ from modelled adult incidence, and in Mali and Zambia trends among young men differed from trends in adult incidence. The magnitude of change differed by method.

Conclusions

Trends in HIV prevalence among young people show encouraging declines. Changes in fertility patterns, HIV-infected children surviving to adulthood, and participation bias could affect future proxy measures of incidence trends.

Analysis of duration of risk behaviour for key populations: a literature review

Background

The objective of this paper is to review literature in order to calculate regional estimates of the average duration of time individuals maintain a specific high-risk behaviour.

Methods

The review targeted the key populations of female sex workers (FSW), male clients of female sex workers (MCFSW), people who inject drugs (injecting drug users (IDU)) and high-risk men who have sex with men (MSM). To be included in the review the study had to provide information on (1) the time a person spent at risk until death or cessation of the risk behaviour, (2) the percentage of the sample who initiated the risk behaviour in less than a year or (3) the mean or median duration of the behaviour from a representative sample.

Results

49 papers were found for the FSW population describing the period of time FSW stay in sex work to be between 2.9 years (Asia) and 12 years (Latin America). Eight papers were found for MCFSW showing the duration of the risk behaviour in this category varying from 4.6 years in Africa to 32 years in Asia. 86 papers were reviewed for the population of IDU showing that the average time a person injects illegal drugs varies from 5.6 years (Africa) to 21 years (South America). No information was found for duration of high-risk behaviour among MSM; instead, the definitions found in the literature for high- and low-risk behaviour among MSM were described.

Conclusions

There is high variability of estimates of duration of high-risk behaviours at regional level. More research is needed to inform models and prevention programmes on the average duration of time individuals maintain a specific high-risk behaviour.

Updates to the Spectrum/Estimation and Projection Package (EPP) model to estimate HIV trends for adults and children

BACKGROUND

The Spectrum and Estimation and Projection Package (EPP) programs are used to estimate key HIV indicators based on HIV surveillance and surveys, programme statistics and epidemic patterns. These indicators include the number of people living with HIV, new infections, AIDS deaths, AIDS orphans, the number of adults and children needing treatment, the need for preventing mother to child transmission (PMTCT) and the impact of antiretroviral treatment on survival.

METHODS

The Joint United Nations Programme on HIV and AIDS (UNAIDS) Reference Group on Estimates, Models and Projections regularly reviews new data and information needs and recommends updates to the methodology and assumptions used in Spectrum. The latest updates described here were used in the 2011 round of global estimates.

RESULTS

Spectrum and EPP have now been combined into one software package to enhance ease of use and ensure consistent data and assumptions for the curve fitting and indicator estimations. Major enhancements to the methods include a new adult model that tracks the HIV+ population by CD4 count; new patterns describing child survival by time of infection (perinatally, <6 months, 7-12 months and 12+ months after birth); a more detailed estimate of mother-to-child transmission that includes differential transmission rates by CD4 count of the mother, the effects of incident infections and new prophylaxis options; and new procedures to estimate uncertainty ranges around regional estimates.

CONCLUSIONS

The revised model and software facilitate the preparation of new HIV estimates and use new data to address emerging needs for better information on need for treatment among adults and children.

Population health impact and cost-effectiveness of tuberculosis diagnosis with Xpert MTB/RIF: a dynamic simulation and economic evaluation

BACKGROUND

The Xpert MTB/RIF test enables rapid detection of tuberculosis (TB) and rifampicin resistance. The World Health Organization recommends Xpert for initial diagnosis in individuals suspected of having multidrug-resistant TB (MDR-TB) or HIV-associated TB, and many countries are moving quickly toward adopting Xpert. As roll-out proceeds, it is essential to understand the potential health impact and cost-effectiveness of diagnostic strategies based on Xpert.

METHODS AND FINDINGS

We evaluated potential health and economic consequences of implementing Xpert in five southern African countries--Botswana, Lesotho, Namibia, South Africa, and Swaziland--where drug resistance and TB-HIV coinfection are prevalent. Using a calibrated, dynamic mathematical model, we compared the status quo diagnostic algorithm, emphasizing sputum smear, against an algorithm incorporating Xpert for initial diagnosis. Results were projected over 10- and 20-y time periods starting from 2012. Compared to status quo, implementation of Xpert would avert 132,000 (95% CI: 55,000-284,000) TB cases and 182,000 (97,000-302,000) TB deaths in southern Africa over the 10 y following introduction, and would reduce prevalence by 28% (14%-40%) by 2022, with more modest reductions in incidence. Health system costs are projected to increase substantially with Xpert, by US$460 million (294-699 million) over 10 y. Antiretroviral therapy for HIV represents a substantial fraction of these additional costs, because of improved survival in TB/HIV-infected populations through better TB case-finding and treatment. Costs for treating MDR-TB are also expected to rise significantly with Xpert scale-up. Relative to status quo, Xpert has an estimated cost-effectiveness of US$959 (633-1,485) per disability-adjusted life-year averted over 10 y. Across countries, cost-effectiveness ratios ranged from US$792 (482-1,785) in Swaziland to US$1,257 (767-2,276) in Botswana. Assessing outcomes over a 10-y period focuses on the near-term consequences of Xpert adoption, but the cost-effectiveness results are conservative, with cost-effectiveness ratios assessed over a 20-y time horizon approximately 20% lower than the 10-y values.

CONCLUSIONS

Introduction of Xpert could substantially change TB morbidity and mortality through improved case-finding and treatment, with more limited impact on long-term transmission dynamics. Despite extant uncertainty about TB natural history and intervention impact in southern Africa, adoption of Xpert evidently offers reasonable value for its cost, based on conventional benchmarks for cost-effectiveness. However, the additional financial burden would be substantial, including significant increases in costs for treating HIV and MDR-TB. Given the fundamental influence of HIV on TB dynamics and intervention costs, care should be taken when interpreting the results of this analysis outside of settings with high HIV prevalence.

A new infectious disease model for estimating and projecting HIV/AIDS epidemics

Objectives

As the global HIV pandemic enters its fourth decade, countries have collected longer time series of surveillance data, and the AIDS-specific mortality has been substantially reduced by the increasing availability of antiretroviral treatment. A refined model with a greater flexibility to fit longer time series of surveillance data is desired.

Methods

In this article, we present a new epidemiological model that allows the HIV infection rate, r(t), to change over years. The annual change of infection rate is modelled by a linear combination of three key factors: the past prevalence, the past infection rate and a stabilisation condition. We focus on fitting the antenatal clinic (ANC) data and household surveys which are the most commonly available data source for generalised epidemics defined by the overall prevalence being above 1%. A hierarchical model is used to account for the repeated measurement within a clinic. A Bayesian approach is used for the parameter estimation.

Results

We evaluate the performance of the newly proposed model on the ANC data collected from urban and rural areas of 31 countries with generalised epidemics in sub-Sahara Africa. The three factors in the proposed model all have significant contributions to the reconstruction of r(t) trends. It improves the prevalence fit over the classic Estimation and Projection Package model and provides more realistic projections when the classic model encounters problems.

Conclusions

The proposed model better captures the main pattern of the HIV/AIDS dynamic. It also retains the simplicity of the classic model with a few interpretable parameters that are easy to interpret and estimate.

Modelling national HIV/AIDS epidemics: revised approach in the UNAIDS Estimation and Projection Package 2011

Objective

United Nations Programme on HIV/AIDS reports regularly on estimated levels and trends in HIV/AIDS epidemics, which are evaluated using an epidemiological model within the Estimation and Projection Package (EPP). The relatively simple four-parameter model of HIV incidence used in EPP through the previous round of estimates has encountered challenges when attempting to fit certain data series on prevalence over time, particularly in settings with long running epidemics where prevalence has increased recently. To address this, the most recent version of the modelling package (EPP 2011) includes a more flexible epidemiological model that allows HIV infection risk to vary over time. This paper describes the technical details of this flexible approach to modelling HIV transmission dynamics within EPP 2011.

Methodology

For the flexible modelling approach, the force of infection parameter, r, is allowed to vary over time through a random walk formulation, and an informative prior distribution is used to improve short-term projections beyond the last year of data. Model parameters are estimated using a Bayesian estimation approach in which models are fit to HIV seroprevalence data from surveillance sites.

Results

This flexible model can yield better estimates of HIV prevalence over time in situations where the classic EPP model has difficulties, such as in Uganda, where prevalence is no longer falling. Based on formal out-of-sample projection tests, the flexible modelling approach also improves predictions and CIs for extrapolations beyond the last observed data point.

Conclusions

We recommend use of a flexible modelling approach where data are sufficient (eg, where at least 5 years of observations are available), and particularly where an epidemic is beyond its peak.

The use of epidemiological data to inform the PEPFAR response

The history of the HIV epidemic and the response to the epidemic is fundamentally a history of an emergency response to a global crisis. Trends and projections from initially available data were instrumental in establishing the President's Emergency Plan for AIDS Relief (PEPFAR) and in determining the direction of the program. Additionally, PEPFAR was built on data and the potential impact of interventions, and required the constant monitoring of the epidemic to report on the progress of the program. The response to the HIV epidemic saw the development of international guidelines and recommendations for data collection and epidemiological modeling. Although it is true that the urgency of the response often meant that data from data-poor countries suffered from incompleteness and bias, fortunately, as the response matured, the quality of the data and the infrastructure supporting data collection also matured. PEPFAR investments in surveillance and surveys were and remain critical for responding to the epidemic. The future of the response is reflected in growing country capacities to collect valid and reliable data, and using those data for decision making.

"Maybe his blood is still strong": a qualitative study among HIV-sero-discordant couples on ART in rural Uganda

Background

HIV-negative members of sero-discordant couples are at high risk for HIV acquisition but few behavioral prevention interventions have been implemented in sub-Saharan Africa and discordance is not well understood by couples themselves.

Methods

In this nested sub-study, we interviewed 40 HIV sero-discordant couples before and after a 6-month behavioral intervention that was comprised of four group discussions on specific HIV prevention and care topics. The content of the sessions included: 1) understanding HIV serodiscordance and reducing risk, 2) couple communication, 3) reproductive health and HIV serodiscordance, 4) coping with HIV serodiscordance and ongoing support. Couple members were interviewed individually. Data were analyzed thematically using ‘Framework Analysis’ which incorporated dyadic factors to address couple issues.

Results

Analysis revealed pre-identified concepts and emergent themes that were relevant to the final conceptual model. Four major categories of factors affecting couple relations, beliefs and current risk behaviors emerged: intervention factors, structural/contextual factors, physical health factors, and past risk behavior. The topics within the intervention most relevant were communication and reproductive health. The contextual factors highlighted by couples were gender norms around sexual decision-making and multiple partnerships. Individual beliefs regarding HIV serodiscordance persisted over all time points for some couples. Interestingly, some couple members had divergent views about their HIV status; some believing the HIV-negative member was negative while others described multiple beliefs around the negative member’s blood surely being positive for HIV. Couple communication emerged as an important theme mediating beliefs and behavior.

Conclusions

In addition to biomedical and behavioral interventions, HIV-serodiscordant couple interventions must embrace the contextual complexity and cultural understanding of HIV infection and discordance as well as the dynamic nature of couple communication to influence risk behavior.

Understanding the modes of transmission model of new HIV infection and its use in prevention planning

The modes of transmission model has been widely used to help decision-makers target measures for preventing human immunodeficiency virus (HIV) infection. The model estimates the number of new HIV infections that will be acquired over the ensuing year by individuals in identified risk groups in a given population using data on the size of the groups, the aggregate risk behaviour in each group, the current prevalence of HIV infection among the sexual or injecting drug partners of individuals in each group, and the probability of HIV transmission associated with different risk behaviours. The strength of the model is its simplicity, which enables data from a variety of sources to be synthesized, resulting in better characterization of HIV epidemics in some settings. However, concerns have been raised about the assumptions underlying the model structure, about limitations in the data available for deriving input parameters and about interpretation and communication of the model results. The aim of this review was to improve the use of the model by reassessing its paradigm, structure and data requirements. We identified key questions to be asked when conducting an analysis and when interpreting the model results and make recommendations for strengthening the model's application in the future.

Bayesian probabilistic population projections for all countries

Projections of countries' future populations, broken down by age and sex, are widely used for planning and research. They are mostly done deterministically, but there is a widespread need for probabilistic projections. We propose a bayesian method for probabilistic population projections for all countries. The total fertility rate and female and male life expectancies at birth are projected probabilistically using bayesian hierarchical models estimated via Markov chain Monte Carlo using United Nations population data for all countries. These are then converted to age-specific rates and combined with a cohort component projection model. This yields probabilistic projections of any population quantity of interest. The method is illustrated for five countries of different demographic stages, continents and sizes. The method is validated by an out of sample experiment in which data from 1950-1990 are used for estimation, and applied to predict 1990-2010. The method appears reasonably accurate and well calibrated for this period. The results suggest that the current United Nations high and low variants greatly underestimate uncertainty about the number of oldest old from about 2050 and that they underestimate uncertainty for high fertility countries and overstate uncertainty for countries that have completed the demographic transition and whose fertility has started to recover towards replacement level, mostly in Europe. The results also indicate that the potential support ratio (persons aged 20-64 per person aged 65+) will almost certainly decline dramatically in most countries over the coming decades.

Voluntary medical male circumcision: modeling the impact and cost of expanding male circumcision for HIV prevention in eastern and southern Africa

BACKGROUND

There is strong evidence showing that voluntary medical male circumcision (VMMC) reduces HIV incidence in men. To inform the VMMC policies and goals of 13 priority countries in eastern and southern Africa, we estimate the impact and cost of scaling up adult VMMC using updated, country-specific data.

METHODS AND FINDINGS

We use the Decision Makers' Program Planning Tool (DMPPT) to model the impact and cost of scaling up adult VMMC in Botswana, Lesotho, Malawi, Mozambique, Namibia, Rwanda, South Africa, Swaziland, Tanzania, Uganda, Zambia, Zimbabwe, and Nyanza Province in Kenya. We use epidemiologic and demographic data from recent household surveys for each country. The cost of VMMC ranges from US$65.85 to US$95.15 per VMMC performed, based on a cost assessment of VMMC services aligned with the World Health Organization's considerations of models for optimizing volume and efficiencies. Results from the DMPPT models suggest that scaling up adult VMMC to reach 80% coverage in the 13 countries by 2015 would entail performing 20.34 million circumcisions between 2011 and 2015 and an additional 8.42 million between 2016 and 2025 (to maintain the 80% coverage). Such a scale-up would result in averting 3.36 million new HIV infections through 2025. In addition, while the model shows that this scale-up would cost a total of US$2 billion between 2011 and 2025, it would result in net savings (due to averted treatment and care costs) amounting to US$16.51 billion.

CONCLUSIONS

This study suggests that rapid scale-up of VMMC in eastern and southern Africa is warranted based on the likely impact on the region's HIV epidemics and net savings. Scaling up of safe VMMC in eastern and southern Africa will lead to a substantial reduction in HIV infections in the countries and lower health system costs through averted HIV care costs.

Male circumcision for HIV prevention: current evidence and implementation in sub-Saharan Africa

Heterosexual exposure accounts for most HIV transmission in sub-Saharan Africa, and this mode, as a proportion of new infections, is escalating globally. The scientific evidence accumulated over more than 20 years shows that among the strategies advocated during this period for HIV prevention, male circumcision is one of, if not, the most efficacious epidemiologically, as well as cost-wise. Despite this, and recommendation of the procedure by global policy makers, national implementation has been slow. Additionally, some are not convinced of the protective effect of male circumcision and there are also reports, unsupported by evidence, that non-sex-related drivers play a major role in HIV transmission in sub-Saharan Africa. Here, we provide a critical evaluation of the state of the current evidence for male circumcision in reducing HIV infection in light of established transmission drivers, provide an update on programmes now in place in this region, and explain why policies based on established scientific evidence should be prioritized. We conclude that the evidence supports the need to accelerate the implementation of medical male circumcision programmes for HIV prevention in generalized heterosexual epidemics, as well as in countering the growing heterosexual transmission in countries where HIV prevalence is presently low.

Impact of albumin on drug delivery--new applications on the horizon

Over the past decades, albumin has emerged as a versatile carrier for therapeutic and diagnostic agents, primarily for diagnosing and treating diabetes, cancer, rheumatoid arthritis and infectious diseases. Market approved products include fatty acid derivatives of human insulin or the glucagon-like-1 peptide (Levemir(®) and Victoza(®)) for treating diabetes, the taxol albumin nanoparticle Abraxane(®) for treating metastatic breast cancer which is also under clinical investigation in further tumor indications, and (99m)Tc-aggregated albumin (Nanocoll(®) and Albures(®)) for diagnosing cancer and rheumatoid arthritis as well as for lymphoscintigraphy. In addition, an increasing number of albumin-based or albumin-binding drugs are in clinical trials such as antibody fusion proteins (MM-111) for treating HER2/neu positive breast cancer (phase I), a camelid albumin-binding nanobody anti-HSA-anti-TNF-α (ATN-103) in phase II studies for treating rheumatoid arthritis, an antidiabetic Exendin-4 analog bound to recombinant human albumin (phase I/II), a fluorescein-labeled albumin conjugate (AFL)-human serum albumin for visualizing the malignant borders of brain tumors for improved surgical resection, and finally an albumin-binding prodrug of doxorubicin (INNO-206) entering phase II studies against sarcoma and gastric cancer. In the preclinical setting, novel approaches include attaching peptides with high-affinity for albumin to antibody fragments, the exploitation of albumin-binding gadolinium contrast agents for magnetic resonance imaging, and physical or covalent attachment of antiviral, antibacterial, and anticancer drugs to albumin that are permanently or transiently attached to human serum albumin (HSA) or act as albumin-binding prodrugs. This review gives an overview of the expanding field of preclinical and clinical drug applications and developments that use albumin as a protein carrier to improve the pharmacokinetic profile of the drug or to target the drug to the pathogenic site addressing diseases with unmet medical needs.

HIV in hiding: methods and data requirements for the estimation of the number of people living with undiagnosed HIV

Many people who are HIV positive are unaware of their infection status. Estimation of the number of people with undiagnosed HIV within a country or region is vital for understanding future need for treatment and for motivating testing programs. We review the available estimation approaches which are in current use. They can be broadly classified into those based on prevalence surveys and those based on reported HIV and AIDS cases. Estimation based on prevalence data requires data from regular prevalence surveys in different population groups together with estimates of the size of these groups. The recommended minimal case reporting data needed to estimate the number of patients with undiagnosed HIV are HIV diagnoses, including CD4 count at diagnosis and whether there has been an AIDS diagnosis in the 3 months before or after HIV diagnosis, and data on deaths in people with HIV. We would encourage all countries to implement several methods that will help develop our understanding of strengths and weaknesses of the various methods.

Using estimation and projection package and Spectrum for Jamaica's national HIV estimates and targets

Background

Adequate coverage of target populations ensures that desired outcomes, such as increased survival of people living with HIV, are achieved. However, estimates of coverage and impact of HIV programmes using available data are limited by the complex natural history of HIV, underreporting of cases and inadequate information systems.

Methods

Jamaica's national HIV estimates were generated using the 2009 version of the UNAIDS estimation and projection package (EPP) and Spectrum. National data used included sentinel surveillance data on antenatal clinic attendees (1986–2005 and 2007), distribution of antiretroviral regimes for prevention of mother-to-child transmission, distribution of antiretroviral therapy (ART) among adults and ART distribution in subpopulations (eg, men who have sex with men (MSM) and sex workers). Surveys of MSM (2007), sex worker (2001, 2005, 2008), STI clinic attendees (1990–2002) and inmates (2006) also provided inputs.

Results

In 2009, Jamaica's HIV prevalence was estimated at 1.7% (range 1.1–2.5) and 31 000 (range 20 000–43 000) adults (>15 years) were living with HIV. The number of adults in need of treatment was 15 000 (range 11 000–19 000) and approximately 2100 new infections occurred in 2009. The EPP/Spectrum estimates were generally consistent with locally available data. However, the number of persons with advanced HIV targeted by the national treatment programme was significantly lower than Spectrum's estimated target population.

Conclusion

EPP/Spectrum can provide important data for national HIV programme planning. Improved monitoring and evaluation systems will provide quality data and result in more robust estimates.