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Sex Transm Infect 86:ii84-ii92 doi:10.1136/sti.2010.045104
  • Supplement

Flexible epidemiological model for estimates and short-term projections in generalised HIV/AIDS epidemics

Open Access
  1. Joshua A Salomon1,4
  1. 1Harvard School of Public Health, Center for Health Decision Science, Boston, Massachusetts, USA
  2. 2Harvard University, Centre for Risk Analysis, Boston, Massachusetts, USA and Toulouse School of Economics (LERNA-INRA), Toulouse, France
  3. 3Harvard University, Center for Risk Analysis, Boston, Massachusetts, USA
  4. 4Harvard School of Public Health, Department of Global Health and Population, Boston, Massachusetts, USA
  1. Correspondence to Daniel R Hogan, Harvard School of Public Health, Center for Health Decision Science, 718 Huntington Ave 2nd Floor, Boston, MA 02115, USA; dhogan{at}fas.harvard.edu
  1. Contributors DRH led the design of the study, development of the model, data acquisition, analysis and interpretation, and wrote the first draft of the manuscript. AMZ and JKH provided methodological input on model development and data analysis and contributed to revision of the manuscript. JAS conceived the study and contributed to design, model development, analysis, interpretation and writing of the manuscript.

  • Accepted 8 September 2010

Abstract

Objective UNAIDS 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.

Methods Our 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.

Results The 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.

Conclusions A 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.

Footnotes

  • Funding This study was supported in part by funding from the UNAIDS Reference Group on Estimates, Modelling and Projections, and by a T32 training grant from the National Institute of Allergy and Infectious Diseases (AI 007433).

  • Competing interests None.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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