Person: Hogan, Daniel R
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Hogan
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Daniel R
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Hogan, Daniel R
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Publication National HIV prevalence estimates for sub-Saharan Africa: Controlling selection bias with Heckman-type selection models(BMJ Publishing Group, 2012) Hogan, Daniel R; Salomon, Joshua; Canning, David; Hammitt, James; Zaslavsky, Alan; Bärnighausen, TillObjectives: Population-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors. Methods: For 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals. Results: Selection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5. Conclusions: Our analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence.Publication Modelling national HIV/AIDS epidemics: revised approach in the UNAIDS Estimation and Projection Package 2011(BMJ Publishing Group, 2012) Bao, Le; Salomon, Joshua; Brown, Timothy B; Raftery, Adrian E; Hogan, Daniel RObjective: United Nations Programme on HIV/AIDS reports regularly on estimated levels and trends in HIV/AIDS epidemics, which are evaluated using an epidemiological model within the Estimation and Projection Package (EPP). The relatively simple four-parameter model of HIV incidence used in EPP through the previous round of estimates has encountered challenges when attempting to fit certain data series on prevalence over time, particularly in settings with long running epidemics where prevalence has increased recently. To address this, the most recent version of the modelling package (EPP 2011) includes a more flexible epidemiological model that allows HIV infection risk to vary over time. This paper describes the technical details of this flexible approach to modelling HIV transmission dynamics within EPP 2011. Methodology For the flexible modelling approach, the force of infection parameter, r, is allowed to vary over time through a random walk formulation, and an informative prior distribution is used to improve short-term projections beyond the last year of data. Model parameters are estimated using a Bayesian estimation approach in which models are fit to HIV seroprevalence data from surveillance sites. Results: This flexible model can yield better estimates of HIV prevalence over time in situations where the classic EPP model has difficulties, such as in Uganda, where prevalence is no longer falling. Based on formal out-of-sample projection tests, the flexible modelling approach also improves predictions and CIs for extrapolations beyond the last observed data point. Conclusions: We recommend use of a flexible modelling approach where data are sufficient (eg, where at least 5 years of observations are available), and particularly where an epidemic is beyond its peak.Publication Spline-based modelling of trends in the force of HIV infection, with application to the UNAIDS Estimation and Projection Package(BMJ Publishing Group, 2012) Hogan, Daniel R; Salomon, JoshuaObjective: 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.Publication Intervention strategies to reduce the burden of non-communicable diseases in Mexico: cost effectiveness analysis(BMJ Publishing Group Ltd., 2012) Salomon, Joshua; Carvalho, Natalie Ida; Gutiérrez-Delgado, Cristina; Orozco, Ricardo; Mancuso, Anna; Hogan, Daniel R; Lee, Diana; Murakami, Yuki; Sridharan, Lakshmi; Medina-Mora, María Elena; González-Pier, EduardoObjective: To inform decision making regarding intervention strategies against non-communicable diseases in Mexico, in the context of health reform. Design Cost effectiveness analysis based on epidemiological modelling. Interventions 101 intervention strategies relating to nine major clusters of non-communicable disease: depression, heavy alcohol use, tobacco use, cataracts, breast cancer, cervical cancer, chronic obstructive pulmonary disease, cardiovascular disease, and diabetes. Data sources Mexican data sources were used for most key input parameters, including administrative registries; disease burden and population estimates; household surveys; and drug price databases. These sources were supplemented as needed with estimates for Mexico from the WHO-CHOICE unit cost database or with estimates extrapolated from the published literature. Main outcome measures Population health outcomes, measured in disability adjusted life years (DALYs); costs in 2005 international dollars ($Int); and costs per DALY. Results: Across 101 intervention strategies examined in this study, average yearly costs at the population level would range from around ≤$Int1m (such as for cataract surgeries) to >$Int1bn for certain strategies for primary prevention in cardiovascular disease. Wide variation also appeared in total population health benefits, from <1000 DALYs averted a year (for some components of cancer treatments or aspirin for acute ischaemic stroke) to >300 000 averted DALYs (for aggressive combinations of interventions to deal with alcohol use or cardiovascular risks). Interventions in this study spanned a wide range of average cost effectiveness ratios, differing by more than three orders of magnitude between the lowest and highest ratios. Overall, community and public health interventions such as non-personal interventions for alcohol use, tobacco use, and cardiovascular risks tended to have lower cost effectiveness ratios than many clinical interventions (of varying complexity). Even within the community and public health interventions, however, there was a 200-fold difference between the most and least cost effective strategies examined. Likewise, several clinical interventions appeared among the strategies with the lowest average cost effectiveness ratios—for example, cataract surgeries. Conclusions: Wide variations in costs and effects exist within and across intervention categories. For every major disease area examined, at least some strategies provided excellent value for money, including both population based and personal interventions.