Spline-based modelling of trends in the force of HIV infection, with application to the UNAIDS Estimation and Projection Package
- Department of Global Health and Population, Harvard School of Public Health, Boston, Massachusetts, USA
- Correspondence to Dr Daniel R Hogan, Harvard School of Public Health, Department of Global Health and Population, 665 Huntington Ave, Building 1, room 1104, Boston, MA 02115, USA; dhogan{at}hsph.harvard.edu
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UNAIDS Report 2012 Guest Editors
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Karen Stanecki
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Peter D Ghys
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Geoff P Garnett
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Catherine Mercer
- Accepted 16 September 2012
Abstract
Objective We previously developed a flexible specification of the UNAIDS Estimation and Projection Package (EPP) that relied on splines to generate time-varying values for the force of infection parameter. Here, we test the feasibility of this approach for concentrated HIV/AIDS epidemics with very sparse data and compare two methods for making short-term future projections with the spline-based model.
Methods Penalised B-splines are used to model the average infection risk over time within the EPP 2011 modelling framework, which includes antiretroviral treatment effects and CD4 cell count progression, and is fit to sentinel surveillance prevalence data with a Bayesian algorithm. We compare two approaches for future projections: (1) an informative prior related to equilibrium prevalence and (2) a random walk formulation.
Results The spline-based model produced plausible fits across a range of epidemics, which included 87 subpopulations from 14 countries with concentrated epidemics and 75 subpopulations from 33 countries with generalised epidemics. The equilibrium prior and random walk approaches to future projections yielded similar prevalence estimates, and both performed well in tests of out-of-sample predictive validity for prevalence. In contrast, in some cases the two approaches varied substantially in estimates of incidence, with the random walk formulation avoiding extreme changes in incidence.
Conclusions A spline-based approach to allowing the force of infection parameter to vary over time within EPP 2011 is robust across a diverse array of epidemics, including concentrated ones with limited surveillance data. Future work on the EPP model should consider the impact that different modelling approaches have on estimates of HIV incidence.
Footnotes
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Contributors DRH designed the study, acquired the data, programmed the model, conducted analyses and wrote the first draft of the manuscript. JAS contributed to development of the model, interpretation of results and revision of the manuscript.
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Funding This work was supported in part by the Joint United Nations Programme on HIV/AIDS.
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Competing interests None.
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Provenance and peer review Commissioned; externally peer reviewed.
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Data sharing statement Readers interested in HIV surveillance data should contact UNAIDS.
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Open Access This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/
This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/3.0/ and http://creativecommons.org/licenses/by-nc/3.0/legalcode








