Fuente: PLoS Medicine
1 Imperial College London, London, United Kingdom, 2 London School of Hygiene and Tropical Medicine, London, United Kingdom, 3 National Institute for Medical Research, Mwanza, Tanzania, 4 Medical Research Council/Uganda Virus Research Institute, Uganda Research Unit on AIDS, Entebbe, Uganda, 5 Biomedical Research and Training Institute, Harare, Zimbabwe, 6 World Health Organization, Geneva, Switzerland
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.
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.
Funding: TBH, SG, BL, and WM thank the Wellcome Trust; BZ was supported by a grant from Global Fund to Fight AIDS, Tuberculosis and Malaria; JT and SB were supported by UK MRC. The funders had no role in the study design, analysis, and preparation of the manuscript or the decision to publish.
Academic Editor: Peter Ghys, Joint United Nations Programme on HIV/AIDS, Switzerland
Citation: Hallett TB, Zaba B, Todd J, Lopman B, Mwita W, et al. (2008) Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation. PLoS Med 5(4): e80 doi:10.1371/journal.pmed.0050080
Received: May 21, 2007; Accepted: February 15, 2008; Published: April 8, 2008
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.
Abbreviations: ART, antiretroviral therapy; DHS, Demographic and Health Surveys; PYAR, person-years at risk
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