Estimating the Size of the HIV/AIDS Epidemic: Complementary Use of the Empirical Bayesian Back-Calculation and the Mover-Stayer Model for Gathering the Largest Amount of Information

Cristina Pasqualucci, Lucilla Ravà, Carla Rossi, Giuseppe Schinaia

Research output: Contribution to journalArticlepeer-review

Abstract

The HIV/AIDS epidemic has reached the end of its second decade, and estimations of its size and dynamics are very important, particularly for developing and planning prevention and therapeutic interventions. Since the HIV infection is characterized by a long asymptomatic period and latency time, observational studies are not suitable to study the epidemic. Dynamic models and the Back-Calculation (BC) methods are two general methodologies which provide estimates and projections of HIV/AIDS incidence and prevalence, while focusing attention on different aspects of the epidemic. For example, the Mover-Stayer (MS) Model, a dynamic compartmental model developed to study the epidemic's spread among a general population, is a useful tool to perform scenario analysis, while the Empirical Bayesian Back-Calculation (EBBC) method allows investigation of the dynamics of the epidemic by risk category. Both methods, with timely updating to reflect changes in the natural history of the HIV/ AIDS epidemic, were recently applied within the EU Concerted Action on Multinational AIDS Scenario Analysis and the Italian Consensus Conference. An overview of some dynamic models and BC methods, and an application of the MS Model and EBBC method to the Italian HIV/AIDS epidemic, are presented here.

Original languageEnglish
Pages (from-to)213-227
Number of pages15
JournalSimulation
Volume71
Issue number4
Publication statusPublished - 1998

Keywords

  • AIDS
  • Back-Calculation method
  • Dynamic models
  • Empirical Bayesian Back-Calculation
  • Epidemic
  • HIV
  • Italy
  • Mover-Stayer model

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Software
  • Safety, Risk, Reliability and Quality

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