Literature DB >> 11477962

Modelling HIV/AIDS epidemics in sub-Saharan Africa using seroprevalence data from antenatal clinics.

J A Salomon1, C J Murray.   

Abstract

OBJECTIVE: To improve the methodological basis for modelling the HIV/AIDS epidemics in adults in sub-Saharan Africa, with examples from Botswana, Central African Republic, Ethiopia, and Zimbabwe. Understanding the magnitude and trajectory of the HIV/AIDS epidemic is essential for planning and evaluating control strategies.
METHODS: Previous mathematical models were developed to estimate epidemic trends based on sentinel surveillance data from pregnant women. In this project, we have extended these models in order to take full advantage of the available data. We developed a maximum likelihood approach for the estimation of model parameters and used numerical simulation methods to compute uncertainty intervals around the estimates.
FINDINGS: In the four countries analysed, there were an estimated half a million new adult HIV infections in 1999 (range: 260 to 960 thousand), 4.7 million prevalent infections (range: 3.0 to 6.6 million), and 370 thousand adult deaths from AIDS (range: 266 to 492 thousand).
CONCLUSION: While this project addresses some of the limitations of previous modelling efforts, an important research agenda remains, including the need to clarify the relationship between sentinel data from pregnant women and the epidemiology of HIV and AIDS in the general population.

Entities:  

Mesh:

Year:  2001        PMID: 11477962      PMCID: PMC2566469     

Source DB:  PubMed          Journal:  Bull World Health Organ        ISSN: 0042-9686            Impact factor:   9.408


  10 in total

1.  HIV and population dynamics: a general model and maximum-likelihood standards for east Africa.

Authors:  Patrick Heuveline
Journal:  Demography       Date:  2003-05

2.  A Bayesian approach to uncertainty analysis of sexually transmitted infection models.

Authors:  Leigh F Johnson; Leontine Alkema; Rob E Dorrington
Journal:  Sex Transm Infect       Date:  2009-11-01       Impact factor: 3.519

3.  Estimates of age-specific reductions in HIV prevalence in Uganda: Bayesian melding estimation and probabilistic population forecast with an HIV-enabled cohort component projection model.

Authors:  Samuel J Clark; Jason R Thomas; Le Bao
Journal:  Demogr Res       Date:  2012-12-12

4.  Effect of variable transmission rate on the dynamics of HIV in sub-Saharan Africa.

Authors:  Diego F Cuadros; Philip H Crowley; Ben Augustine; Sarah L Stewart; Gisela García-Ramos
Journal:  BMC Infect Dis       Date:  2011-08-11       Impact factor: 3.090

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

Authors:  Daniel R Hogan; Alan M Zaslavsky; James K Hammitt; Joshua A Salomon
Journal:  Sex Transm Infect       Date:  2010-12       Impact factor: 3.519

6.  Fitting HIV Prevalence 1981 Onwards for Three Indian States Using the Goals Model and the Estimation and Projection Package.

Authors:  Tarun Bhatnagar; Tapati Dutta; John Stover; Sheela Godbole; Damodar Sahu; Kangusamy Boopathi; Shilpa Bembalkar; Kh Jitenkumar Singh; Rajat Goyal; Arvind Pandey; Sanjay M Mehendale
Journal:  PLoS One       Date:  2016-10-06       Impact factor: 3.240

7.  Recognizing the hidden: strengthening the HIV surveillance system among key and priority populations in Mozambique.

Authors:  Cynthia Semá Baltazar; Makini Boothe; Denise Chitsondzo Langa; Isabel Sathane; Roberta Horth; Peter Young; Nick Schaad; Henry F Raymond
Journal:  BMC Public Health       Date:  2021-01-07       Impact factor: 3.295

8.  Analysing the impact of migration on HIV/AIDS cases using epidemiological modelling to guide policy makers.

Authors:  Ofosuhene O Apenteng; Prince P Osei; Noor Azina Ismail; Aline Chiabai
Journal:  Infect Dis Model       Date:  2022-01-30

9.  Cross-sectional comparative study of risky sexual behaviours among HIV-infected persons initiated and waiting to start antiretroviral therapy in rural Rakai, Uganda.

Authors:  Lydia Jacenta Nakiganda; Gertrude Nakigozi; Joseph Kagaayi; Fred Nalugoda; David Serwadda; Nelson Sewankambo; Ronald Gray; Anthony Ndyanabo; Richard Muwanika; Benedict Oppong Asamoah
Journal:  BMJ Open       Date:  2017-09-11       Impact factor: 2.692

10.  Challenges in estimating HIV prevalence trends and geographical variation in HIV prevalence using antenatal data: Insights from mathematical modelling.

Authors:  Leigh F Johnson; Mmamapudi Kubjane; Jeffrey W Eaton
Journal:  PLoS One       Date:  2020-11-20       Impact factor: 3.240

  10 in total

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