Do Children and Adolescents with Anorexia Nervosa Display an Inefficient Cognitive Processing Style?

Objective: This study aimed to examine neuropsychological processing in children and adolescents with Anorexia Nervosa (AN). The relationship of clinical and demographic variables to neuropsychological functioning within the AN group was also explored.  Method: The performance of 41 children and adolescents with a diagnosis of AN were compared to 43 healthy control (HC) participants on a number of neuropsychological measures.  Results: There were no differences in IQ between AN and HC groups. However, children and adolescents with AN displayed significantly more perseverative errors on the Wisconsin Card Sorting Test, and lower Style and Central Coherence scores on the Rey Osterrieth Complex Figure Test relative to HCs.  Conclusion: Inefficient cognitive processing in the AN group was independent of clinical and demographic variables, suggesting it might represent an underlying trait for AN. The implications of these findings are discussed

Estimating HIV Incidence among Adults in Kenya and Uganda: A Systematic Comparison of Multiple Methods

CITATION: Kim, A. A. et al. 2011. Estimating HIV incidence among adults in Kenya and Uganda : a systematic comparison of multiple methods. PLos ONE, 6(3): e17535, doi:10.1371/journal.pone.0017535.The original publication is available at http://journals.plos.org/plosoneBackground: Several approaches have been used for measuring HIV incidence in large areas, yet each presents specific challenges in incidence estimation. Methodology/Principal Findings: We present a comparison of incidence estimates for Kenya and Uganda using multiple methods: 1) Epidemic Projections Package (EPP) and Spectrum models fitted to HIV prevalence from antenatal clinics (ANC) and national population-based surveys (NPS) in Kenya (2003, 2007) and Uganda (2004/2005); 2) a survey-derived model to infer age-specific incidence between two sequential NPS; 3) an assay-derived measurement in NPS using the BED IgG capture enzyme immunoassay, adjusted for misclassification using a locally derived false-recent rate (FRR) for the assay; (4) community cohorts in Uganda; (5) prevalence trends in young ANC attendees. EPP/Spectrum-derived and survey-derived modeled estimates were similar: 0.67 [uncertainty range: 0.60, 0.74] and 0.6 [confidence interval: (CI) 0.4, 0.9], respectively, for Uganda (2005) and 0.72 [uncertainty range: 0.70, 0.74] and 0.7 [CI 0.3, 1.1], respectively, for Kenya (2007). Using a local FRR, assay-derived incidence estimates were 0.3 [CI 0.0, 0.9] for Uganda (2004/2005) and 0.6 [CI 0, 1.3] for Kenya (2007). Incidence trends were similar for all methods for both Uganda and Kenya. Conclusions/Significance: Triangulation of methods is recommended to determine best-supported estimates of incidence to guide programs. Assay-derived incidence estimates are sensitive to the level of the assay's FRR, and uncertainty around high FRRs can significantly impact the validity of the estimate. Systematic evaluations of new and existing incidence assays are needed to the study the level, distribution, and determinants of the FRR to guide whether incidence assays can produce reliable estimates of national HIV incidence.http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0017535Publisher's versio

Multivariate data analysis. In M. Terre Blanche, K. Durrheim & D. Painter (Eds.),

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Assessment of epidemic projections using recent HIV survey data in South Africa: a validation analysis of ten mathematical models of HIV epidemiology in the antiretroviral therapy era

Background Mathematical models are widely used to simulate the effects of interventions to control HIV and to project future epidemiological trends and resource needs. We aimed to validate past model projections against data from a large household survey done in South Africa in 2012. Methods We compared ten model projections of HIV prevalence, HIV incidence, and antiretroviral therapy (ART) coverage for South Africa with estimates from national household survey data from 2012. Model projections for 2012 were made before the publication of the 2012 household survey. We compared adult (age 15-49 years) HIV prevalence in 2012, the change in prevalence between 2008 and 2012, and prevalence, incidence, and ART coverage by sex and by age groups between model projections and the 2012 household survey. Findings All models projected lower prevalence estimates for 2012 than the survey estimate (18.8%), with eight models' central projections being below the survey 95% CI (17.5-20.3). Eight models projected that HIV prevalence would remain unchanged (n=5) or decline (n=3) between 2008 and 2012, whereas prevalence estimates from the household surveys increased from 16.9% in 2008 to 18.8% in 2012 (difference 1.9, 95% CI -0.1 to 3.9). Model projections accurately predicted the 1.6 percentage point prevalence decline (95% CI -0.3 to 3.5) in young adults aged 15-24 years, and the 2.2 percentage point (0.5 to 3.9) increase in those aged 50 years and older. Models accurately represented the number of adults on ART in 2012; six of ten models were within the survey 95% CI of 1.54-2.12 million. However, the differential ART coverage between women and men was not fully captured; all model projections of the sex ratio of women to men on ART were lower than the survey estimate of 2.22 (95% CI 1.73-2.71). Interpretation Projections for overall declines in HIV epidemics during the ART era might have been optimistic. Future treatment and HIV prevention needs might be greater than previously forecasted. Additional data about service provision for HIV care could help inform more accurate projections

The cost and impact of scaling up pre-exposure prophylaxis for HIV prevention: a systematic review of cost-effectiveness modelling studies.

BACKGROUND: Cost-effectiveness studies inform resource allocation, strategy, and policy development. However, due to their complexity, dependence on assumptions made, and inherent uncertainty, synthesising, and generalising the results can be difficult. We assess cost-effectiveness models evaluating expected health gains and costs of HIV pre-exposure prophylaxis (PrEP) interventions. METHODS AND FINDINGS: We conducted a systematic review comparing epidemiological and economic assumptions of cost-effectiveness studies using various modelling approaches. The following databases were searched (until January 2013): PubMed/Medline, ISI Web of Knowledge, Centre for Reviews and Dissemination databases, EconLIT, and region-specific databases. We included modelling studies reporting both cost and expected impact of a PrEP roll-out. We explored five issues: prioritisation strategies, adherence, behaviour change, toxicity, and resistance. Of 961 studies retrieved, 13 were included. Studies modelled populations (heterosexual couples, men who have sex with men, people who inject drugs) in generalised and concentrated epidemics from Southern Africa (including South Africa), Ukraine, USA, and Peru. PrEP was found to have the potential to be a cost-effective addition to HIV prevention programmes in specific settings. The extent of the impact of PrEP depended upon assumptions made concerning cost, epidemic context, programme coverage, prioritisation strategies, and individual-level adherence. Delivery of PrEP to key populations at highest risk of HIV exposure appears the most cost-effective strategy. Limitations of this review include the partial geographical coverage, our inability to perform a meta-analysis, and the paucity of information available exploring trade-offs between early treatment and PrEP. CONCLUSIONS: Our review identifies the main considerations to address in assessing cost-effectiveness analyses of a PrEP intervention--cost, epidemic context, individual adherence level, PrEP programme coverage, and prioritisation strategy. Cost-effectiveness studies indicating where resources can be applied for greatest impact are essential to guide resource allocation decisions; however, the results of such analyses must be considered within the context of the underlying assumptions made. Please see later in the article for the Editors' Summary

Perspectives on the use of modelling and economic analysis to guide HIV programmes in sub-Saharan Africa

HIV modelling and economic analyses have had a prominent role in guiding programmatic responses to HIV in sub-Saharan Africa. However, there has been little reflection on how the HIV modelling field might develop in future. HIV modelling should more routinely align with national government and ministry of health priorities, recognising their legitimate mandates and stewardship responsibilities, for HIV and other wider health programmes. Importance should also be placed on ensuring collaboration between modellers, and that joint approaches to addressing modelling questions, becomes the norm rather than the exception. Such an environment can accelerate translation of modelling analyses into policy formulation because areas where models agree can be prioritised for action, whereas areas over which uncertainty prevails can be slated for additional study, data collection, and analysis. HIV modelling should increasingly be integrated with the modelling of health needs beyond HIV, particularly in allocative efficiency analyses, where focusing on one disease over another might lead to worse health overall. Such integration might also enhance partnership with national governments whose mandates extend beyond HIV. Finally, we see a need for there to be substantial and equitable investment in capacity strengthening within African countries, so that African researchers will increasingly be leading modelling exercises. Building a critical mass of expertise, strengthened through external collaboration and knowledge exchange, should be the ultimate goal

Perspectives on the use of modelling and economic analysis to guide HIV programmes in sub-Saharan Africa

HIV modelling and economic analyses have had a prominent role in guiding programmatic responses to HIV in sub-Saharan Africa. However, there has been little reflection on how the HIV modelling field might develop in future. HIV modelling should more routinely align with national government and ministry of health priorities, recognising their legitimate mandates and stewardship responsibilities, for HIV and other wider health programmes. Importance should also be placed on ensuring collaboration between modellers, and that joint approaches to addressing modelling questions, becomes the norm rather than the exception. Such an environment can accelerate translation of modelling analyses into policy formulation because areas where models agree can be prioritised for action, whereas areas over which uncertainty prevails can be slated for additional study, data collection, and analysis. HIV modelling should increasingly be integrated with the modelling of health needs beyond HIV, particularly in allocative efficiency analyses, where focusing on one disease over another might lead to worse health overall. Such integration might also enhance partnership with national governments whose mandates extend beyond HIV. Finally, we see a need for there to be substantial and equitable investment in capacity strengthening within African countries, so that African researchers will increasingly be leading modelling exercises. Building a critical mass of expertise, strengthened through external collaboration and knowledge exchange, should be the ultimate goal