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Progress and challenges in modelling country-level HIV/AIDS epidemics: the UNAIDS Estimation and Projection Package 2007
  1. T Brown1,
  2. J A Salomon2,
  3. L Alkema3,
  4. A E Raftery3,
  5. E Gouws4
  1. 1
    Population and Health Studies, East-West Center, Honolulu, HI, USA
  2. 2
    Harvard University Initiative for Global Health, Cambridge, Maryland, USA
  3. 3
    Center for Statistics and the Social Sciences, University of Washington, Seattle, Washington, USA
  4. 4
    UNAIDS, Geneva, Switzerland
  1. Tim Brown, East-West Center, 1601 East-West Road, Honolulu, HI 96848, USA; tim{at}hawaii.edu

Abstract

The UNAIDS Estimation and Projection Package (EPP) was developed to aid in country-level estimation and short-term projection of HIV/AIDS epidemics. This paper describes advances reflected in the most recent update of this tool (EPP 2007), and identifies key issues that remain to be addressed in future versions. The major change to EPP 2007 is the addition of uncertainty estimation for generalised epidemics using the technique of Bayesian melding, but many additional changes have been made to improve the user interface and efficiency of the package. This paper describes the interface for uncertainty analysis, changes to the user interface for calibration procedures and other user interface changes to improve EPP’s utility in different settings. While formal uncertainty assessment remains an unresolved challenge in low-level and concentrated epidemics, the Bayesian melding approach has been applied to provide analysts in these settings with a visual depiction of the range of models that may be consistent with their data. In fitting the model to countries with longer-running epidemics in sub-Saharan Africa, a number of limitations have been identified in the current model with respect to accommodating behaviour change and accurately replicating certain observed epidemic patterns. This paper discusses these issues along with their implications for future changes to EPP and to the underlying UNAIDS Reference Group model.

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Footnotes

  • Funding: The authors acknowledge the support of UNAIDS for the ongoing development of EPP. National Institute of Child Health and Development grant no R01 HD054511 supported the development of the uncertainty estimation methodologies in EPP.

  • Competing interests: None.

  • Contributors: TB drafted the original version of the paper and incorporated feedback from the other authors. AR and LA developed the Bayesian melding methodologies used in uncertainty estimation and TB implemented these in EPP, developed the uncertainty interface and adapted the algorithms for greater speed. JS documented the limitations of the current Reference Group model and explored possible alternatives to address them. EG assisted in developing the calibration procedures and prepared estimates of the calibration parameters for urban and rural generalised epidemics that are incorporated into EPP 2007. All five are active members of the UNAIDS Reference Group on HIV Estimates, Modelling and Projections that advises UNAIDS on the techniques to be used in EPP.

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