Literature DB >> 14523279

Methods and procedures for estimating HIV/AIDS and its impact: the UNAIDS/WHO estimates for the end of 2001.

Neff Walker1, Karen A Stanecki, Tim Brown, John Stover, Stefano Lazzari, Jesus Maria Garcia-Calleja, Bernhard Schwartländer, Peter D Ghys.   

Abstract

BACKGROUND: The Joint United Nations Programme on HIV and AIDS (UNAIDS) and the World Health Organization (WHO) have produced country-specific estimates of HIV/AIDS biannually since 1997. These estimates are a primary source of information about the extent and spread of the HIV/AIDS epidemic and its impact. The importance of having comparable country-specific estimates of HIV/AIDS is growing as estimates are used to determine how international resources to fight HIV/AIDS will be allocated to countries.
OBJECTIVES: This paper describes the procedures and process used to make the 2001 round of UNAIDS/WHO estimates of HIV/AIDS. The paper focuses on the different approaches used to make estimates of prevalence in countries with generalized and low-level and concentrated epidemics as well as on new curve-fitting software that was developed to produce epidemic curves for each country. In addition, it presents the assumptions used (e.g. survival from infection to death, the rate of mother-to-child transmission) that are required to derive estimates of incidence and mortality in adults, as well as prevalence, incidence and mortality in children.
CONCLUSION: The paper describes the general process by which the estimation and modelling procedures have been refined and improved over time. The paper also discusses the limitations and weaknesses of the procedures and the data used to make the estimates, and suggests areas where further improvements need to be made.

Entities:  

Mesh:

Year:  2003        PMID: 14523279     DOI: 10.1097/00002030-200310170-00010

Source DB:  PubMed          Journal:  AIDS        ISSN: 0269-9370            Impact factor:   4.177


  24 in total

1.  Monitoring global health: bottom up approach is more likely to be successful.

Authors:  Ties Boerma; Carla Abou-Zahr
Journal:  BMJ       Date:  2005-01-22

Review 2.  Improving projections at the country level: the UNAIDS Estimation and Projection Package 2005.

Authors:  T Brown; N C Grassly; G Garnett; K Stanecki
Journal:  Sex Transm Infect       Date:  2006-06       Impact factor: 3.519

3.  Estimating the number of people at risk for and living with HIV in China in 2005: methods and results.

Authors:  F Lu; N Wang; Z Wu; X Sun; J Rehnstrom; K Poundstone; W Yu; E Pisani
Journal:  Sex Transm Infect       Date:  2006-06       Impact factor: 3.519

4.  National population based HIV prevalence surveys in sub-Saharan Africa: results and implications for HIV and AIDS estimates.

Authors:  J M García-Calleja; E Gouws; P D Ghys
Journal:  Sex Transm Infect       Date:  2006-06       Impact factor: 3.519

5.  Human immunodeficiency virus (HIV) infection patterns and risk behaviours in different population groups and provinces in Viet Nam.

Authors:  Nguyen Anh Tuan; Knut Fylkesnes; Bui Duc Thang; Nguyen Tran Hien; Nguyen Thanh Long; Nguyen Van Kinh; Pham Hong Thang; Pham Duc Manh; Nigel O'Farrell
Journal:  Bull World Health Organ       Date:  2007-01       Impact factor: 9.408

6.  Do HIV prevalence trends in antenatal clinic surveillance represent trends in the general population in the antiretroviral therapy era? The case of Manicaland, East Zimbabwe.

Authors:  Simon Gregson; Kanika Dharmayat; Monique Pereboom; Albert Takaruza; Owen Mugurungi; Nadine Schur; Constance A Nyamukapa
Journal:  AIDS       Date:  2015-09-10       Impact factor: 4.177

7.  Including pre-AIDS mortality in back-calculation model to estimate HIV prevalence in France, 2000.

Authors:  Sylvie Deuffic-Burban; Dominique Costagliola
Journal:  Eur J Epidemiol       Date:  2006-05-23       Impact factor: 8.082

8.  Refusal bias in HIV prevalence estimates from nationally representative seroprevalence surveys.

Authors:  Georges Reniers; Jeffrey Eaton
Journal:  AIDS       Date:  2009-03-13       Impact factor: 4.177

9.  Adjusting HIV prevalence for survey non-response using mortality rates: an application of the method using surveillance data from Rural South Africa.

Authors:  Makandwe Nyirenda; Basia Zaba; Till Bärnighausen; Victoria Hosegood; Marie-Louise Newell
Journal:  PLoS One       Date:  2010-08-25       Impact factor: 3.240

10.  Female sex work interventions and changes in HIV and syphilis infection risks from 2003 to 2008 in India: a repeated cross-sectional study.

Authors:  Paul Arora; Nico J D Nagelkerke; Rahim Moineddin; Madhulekha Bhattacharya; Prabhat Jha
Journal:  BMJ Open       Date:  2013-06-20       Impact factor: 2.692

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