R Lyerla1, E Gouws, J M García-Calleja, E Zaniewski. 1. Department of Policy, Evidence and Partnerships, Joint United Nations Programme on HIV/AIDS, UNAIDS, Geneva, Switzerland. lyerlar@unaids.org
Abstract
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.
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.
Authors: N Walker; J Stover; K Stanecki; A E Zaniewski; N C Grassly; J M Garcia-Calleja; P D Ghys Journal: Sex Transm Infect Date: 2004-08 Impact factor: 3.519
Authors: Eline L Korenromp; Brian G Williams; Sake J de Vlas; Eleanor Gouws; Charles F Gilks; Peter D Ghys; Bernard L Nahlen Journal: Emerg Infect Dis Date: 2005-09 Impact factor: 6.883
Authors: Ryuichi Komatsu; Eline L Korenromp; Daniel Low-Beer; Catherine Watt; Christopher Dye; Richard W Steketee; Bernard L Nahlen; Rob Lyerla; Jesus M Garcia-Calleja; John Cutler; Bernhard Schwartländer Journal: BMC Infect Dis Date: 2010-04-30 Impact factor: 3.090