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Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation
BACKGROUND: HIV surveillance of generalised epidemics in Africa primarily relies on prevalence at antenatal clinics, but estimates of incidence in the general population would be more useful. Repeated cross-sectional measures of HIV prevalence are now becoming available for general populations in ma...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2288620/ https://www.ncbi.nlm.nih.gov/pubmed/18590346 http://dx.doi.org/10.1371/journal.pmed.0050080 |
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author | Hallett, Timothy B Zaba, Basia Todd, Jim Lopman, Ben Mwita, Wambura Biraro, Sam Gregson, Simon Boerma, J. Ties |
author_facet | Hallett, Timothy B Zaba, Basia Todd, Jim Lopman, Ben Mwita, Wambura Biraro, Sam Gregson, Simon Boerma, J. Ties |
author_sort | Hallett, Timothy B |
collection | PubMed |
description | BACKGROUND: HIV surveillance of generalised epidemics in Africa primarily relies on prevalence at antenatal clinics, but estimates of incidence in the general population would be more useful. Repeated cross-sectional measures of HIV prevalence are now becoming available for general populations in many countries, and we aim to develop and validate methods that use these data to estimate HIV incidence. METHODS AND FINDINGS: Two methods were developed that decompose observed changes in prevalence between two serosurveys into the contributions of new infections and mortality. Method 1 uses cohort mortality rates, and method 2 uses information on survival after infection. The performance of these two methods was assessed using simulated data from a mathematical model and actual data from three community-based cohort studies in Africa. Comparison with simulated data indicated that these methods can accurately estimates incidence rates and changes in incidence in a variety of epidemic conditions. Method 1 is simple to implement but relies on locally appropriate mortality data, whilst method 2 can make use of the same survival distribution in a wide range of scenarios. The estimates from both methods are within the 95% confidence intervals of almost all actual measurements of HIV incidence in adults and young people, and the patterns of incidence over age are correctly captured. CONCLUSIONS: It is possible to estimate incidence from cross-sectional prevalence data with sufficient accuracy to monitor the HIV epidemic. Although these methods will theoretically work in any context, we have able to test them only in southern and eastern Africa, where HIV epidemics are mature and generalised. The choice of method will depend on the local availability of HIV mortality data. |
format | Text |
id | pubmed-2288620 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-22886202008-04-26 Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation Hallett, Timothy B Zaba, Basia Todd, Jim Lopman, Ben Mwita, Wambura Biraro, Sam Gregson, Simon Boerma, J. Ties PLoS Med Research Article BACKGROUND: HIV surveillance of generalised epidemics in Africa primarily relies on prevalence at antenatal clinics, but estimates of incidence in the general population would be more useful. Repeated cross-sectional measures of HIV prevalence are now becoming available for general populations in many countries, and we aim to develop and validate methods that use these data to estimate HIV incidence. METHODS AND FINDINGS: Two methods were developed that decompose observed changes in prevalence between two serosurveys into the contributions of new infections and mortality. Method 1 uses cohort mortality rates, and method 2 uses information on survival after infection. The performance of these two methods was assessed using simulated data from a mathematical model and actual data from three community-based cohort studies in Africa. Comparison with simulated data indicated that these methods can accurately estimates incidence rates and changes in incidence in a variety of epidemic conditions. Method 1 is simple to implement but relies on locally appropriate mortality data, whilst method 2 can make use of the same survival distribution in a wide range of scenarios. The estimates from both methods are within the 95% confidence intervals of almost all actual measurements of HIV incidence in adults and young people, and the patterns of incidence over age are correctly captured. CONCLUSIONS: It is possible to estimate incidence from cross-sectional prevalence data with sufficient accuracy to monitor the HIV epidemic. Although these methods will theoretically work in any context, we have able to test them only in southern and eastern Africa, where HIV epidemics are mature and generalised. The choice of method will depend on the local availability of HIV mortality data. Public Library of Science 2008-04 2008-04-08 /pmc/articles/PMC2288620/ /pubmed/18590346 http://dx.doi.org/10.1371/journal.pmed.0050080 Text en Copyright: © 2008 Hallett et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hallett, Timothy B Zaba, Basia Todd, Jim Lopman, Ben Mwita, Wambura Biraro, Sam Gregson, Simon Boerma, J. Ties Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation |
title | Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation |
title_full | Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation |
title_fullStr | Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation |
title_full_unstemmed | Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation |
title_short | Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation |
title_sort | estimating incidence from prevalence in generalised hiv epidemics: methods and validation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2288620/ https://www.ncbi.nlm.nih.gov/pubmed/18590346 http://dx.doi.org/10.1371/journal.pmed.0050080 |
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