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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.

Evidence-based planning has been the cornerstone of India's response to HIV/AIDS. Here we describe the process, method and tools used for generating the 2015 HIV estimates and provide a summary of the main results. Spectrum software supported by the UNAIDS was used to produce HIV estimates for India as a whole and its States/Union Territories. This tool takes into consideration the size and HIV prevalence of defined population groups and programme data to estimate HIV prevalence, incidence and mortality over time as well as treatment needs. India's national adult prevalence of HIV was 0.26 per cent in 2015. Of the 2.1 million people living with HIV/AIDS, the largest numbers were in Andhra Pradesh, Maharashtra and Karnataka. New HIV infections were an estimated 86,000 in 2015, reflecting a decline by around 32 per cent from 2007. The declining trend in incidence was mirrored in most States, though an increasing trend was detected in Assam, Chandigarh, Chhattisgarh, Gujarat, Sikkim, Tripura and Uttar Pradesh. AIDS-related deaths were estimated to be 67,600 in 2015, reflecting a 54 per cent decline from 2007. There were variations in the rate and trend of decline across India for this indicator also. While key indicators measured through Spectrum modelling confirm success of the National AIDS Control Programme, there is no room for complacency as rising incidence trends in some geographical areas and population pockets remain the cause of concern. Progress achieved so far in responding to HIV/AIDS needs to be sustained to end the HIV epidemic.

This paper describes the Estimation and Projection Package (EPP) for estimating and projecting HIV prevalence levels in countries with generalised epidemics. The paper gives an overall summary of the software and interface. It describes the process of defining and modelling a national epidemic in terms of locally relevant sub-epidemics and the four epidemiological parameters used to fit a curve to produce the prevalence trends in the epidemic. It also provides an example of using the EPP in a country with a generalised epidemic. The paper discusses the strengths and weaknesses of the software and its envisaged future developments.

ObjectiveUNAIDS and country analysts use a simple infectious disease model, embedded in the Estimation and Projection Package (EPP), to generate annual updates on the global HIV/AIDS epidemic. Our objective was to develop modifications to the current model that improve fit to recently observed prevalence trends across countries.MethodsOur proposed alternative to the current EPP approach simplifies the model structure and explicitly models changes in average infection risk over time, operationalised using penalised B-splines in a Bayesian framework. We also present an alternative approach to initiating the epidemic that improves standardisation and efficiency, and add an informative prior distribution for changes in infection risk beyond the last data point that enhances the plausibility of short-term extrapolations.ResultsThe spline-based model produces better fits than the current model to observed prevalence trends in settings that have recently experienced levelling or rising prevalence following a steep decline, such as Uganda and urban Rwanda. The model also predicts a deceleration of the decline in prevalence for countries with recent experience of steady declines, such as Kenya and Zimbabwe. Estimates and projections from our alternative model are comparable to those from the current model where the latter performs well.ConclusionsA more flexible epidemiological model that accommodates changing infection risk over time can provide better estimates and short-term projections of HIV/AIDS incidence, prevalence and mortality than the current EPP model. The alternative model specification can be incorporated easily into existing analytical tools that are used to produce updates on the global HIV/AIDS epidemic.

Background: In the Joint United Nations Programme on HIV/AIDS (UNAIDS) approach to HIV and AIDS estimates, estimates of adult prevalence produced by the Estimation and Projection Package (EPP) or the Workbook are transferred to Spectrum to estimate the consequences of the HIV/AIDS epidemic, including the number of people living with HIV by age and sex, new infections, AIDS deaths, AIDS orphans, treatment needs, and the impact of treatment on survival. Methods: The UNAIDS Reference Group on Estimates, Models and Projections recommends updates to the methodology and assumptions based on the latest research findings and international policy and programme guidelines. The latest update to Spectrum has been used in the 2005 round of global estimates. Results: Several new features have been added to Spectrum in the past two years. New patterns of the age distribution of prevalence over time are based on the latest survey data. A more detailed treatment of mother to child transmission of HIV is now based on information about current breastfeeding practices, treatment options offered to prevent mother to child transmission (PMTCT), infant feeding options, and the percentage or number of pregnant women accessing PMTCT services. A new section on child survival includes the effects of cotrimoxazole and ART on child survival. Projections can now be calibrated with national survey data. A new set of outputs is provided for all adults over the age of 15 in addition to the traditional 15–49 age group. New outputs are now available to show plausibility bounds and regional estimates for key indicators. Conclusions: The latest update to the Spectrum program is intended to incorporate the latest research findings and provide new outputs needed by national and international planners.

The Joint United Nations Programme on HIV/AIDS (UNAIDS) has developed the Estimation and Projection Package (EPP) for making national estimates and short-term projections of HIV prevalence based on observed prevalence trends at antenatal clinics. Assessing the uncertainty about its estimates and projections is important for informed policy decision making, and we propose the use of Bayesian melding for this purpose. Prevalence data and other information about the EPP model's input parameters are used to derive a probabilistic HIV prevalence projection, namely a probability distribution over a set of future prevalence trajectories. We relate antenatal clinic prevalence to population prevalence and account for variability between clinics using a random effects model. Predictive intervals for clinic prevalence are derived for checking the model. We discuss predictions given by the EPP model and the results of the Bayesian melding procedure for Uganda, where prevalence peaked at around 28% in 1990; the 95% prediction interval for 2010 ranges from 2% to 7%.

Objective: Review of recent data and practice to derive guidance on questions relating to the measurement and analysis of trends in HIV prevalence and incidence. Results: HIV prevalence among pregnant women attending antenatal clinics (ANCs) remains the principal data source to inform trends in the epidemic. Other data sources are: less available, representative of a small section of the population (sex workers, occupational groups), subject to additional bias (for example, voluntary counselling and testing service statistics), or are not yet available for multiple years (national surveys). Validity of HIV prevalence results may change over time due to improvements in HIV tests per se and implementation of laboratory quality assurance systems. The newer laboratory tests for recent infections require further validation and development of methodology to derive estimates of HIV incidence. Conclusions: Issues to consider during statistical analyses of trends among ANC attendees are: inclusion of consistent sites only, use of confidence intervals, stratification by site when performing a statistical test for trend, the need for at least three observations in a surveillance system with data collection every one to two years, and sound judgement. Trends in HIV prevalence among pregnant 15–24 year olds attending ANCs can be used to approximate trends in incidence. Indepth small area research studies are useful to inform the interpretation of surveillance data and provide directly measured trends in prevalence and incidence. Modelling can assess changes over time in prevalence, incidence, and mortality at the same time. Modelling tools need to be further developed to allow incorporation of estimates of HIV incidence and mortality, as these data are likely to become available in the future. To increase their explanatory power, models should also be extended to incorporate programmatic inputs.

Background: UNAIDS has developed the Estimation and Projection Package (EPP) as a tool for national programmes to use for making national estimates and short term projections of HIV prevalence. EPP provides direct input to Spectrum, which produces incidence, deaths, and AIDS impacts. Methods: The latest version, EPP 2005, includes substantial methodological improvements over the previous version. These include: (1) parallel, but unique, interfaces for generalised and concentrated epidemics; (2) use of maximum likelihood fitting procedures; (3) a new procedure, known as level fits, adjusting for expansion of national surveillance systems into lower prevalence sites; (4) provisions for handling turnover in at-risk populations, including the reassignment of HIV positive former members to lower risk populations; and (5) user-defined calibration to HIV prevalence levels from general population or other epidemiological surveys. Results: Following regional training in mid 2005, this new version has been applied by many national programmes to make their end of 2005 estimates of HIV infections. UNAIDS has combined these national estimates to form the 2005 global HIV and AIDS estimates. Conclusion: EPP 2005 is a substantial improvement over previous versions, forming a solid base for the next round of modifications. Proposed modifications for that next version are presented for the reader’s information.

This paper describes the software package Spectrum, which is a modular program that is used to examine the consequences of current trends and future program interventions in reproductive health. It is used to determine the consequences of the HIV/AIDS epidemic, including the number of people living with HIV/AIDS by age and sex, the number of AIDS deaths, and the number of orphans as a result of AIDS, as well as other demographic indicators of interest, such as life expectancy and <5 mortality. The core of Spectrum is a demographic projection model called DemProj, which projects the population by age and sex. Other modules interact with the demographic projection. The HIV/AIDS projections are added to the demographic projections using a module called AIDS Impact Model. This module uses the projection of adult HIV prevalence over time, which is prepared using the Estimation and Projection Package model or the projection workbook. It also requires assumptions about the epidemiology of HIV, including the ratio of female:male prevalence, the distribution of infection by age, the distribution of the time from infection until AIDS death, and the effect of HIV on fertility.

Objective: This paper describes improvements and updates to an established approach to making epidemiological estimates of HIV prevalence in countries with low level and concentrated epidemics. Methods: The structure of the software used to make estimates is briefly described, with particular attention to changes and improvements. Discussion: The approach focuses on identifying populations which, through their behaviour, are at high risk of infection with HIV or who are exposed through the risk behaviour of their sexual partners. Estimates of size and HIV prevalence of these populations allow the total number of HIV infected people in a country or region to be estimated. Major changes in the software focus on the move away from short term projections and towards developing an epidemiological curve that more accurately represents the change in prevalence of HIV over time. The software continues to provide an output file for use in the Spectrum software so as to estimate the demographic impact of HIV infection at country level.