This report investigates the impact of potential misclassification of samples on HIV prevalence estimates for 23 surveys conducted from 2010-2014. In addition to visual inspection of laboratory results, we examined how accounting for potential miscl
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assification of HIV status through Bayesian latent class models affected the prevalence estimates. Two types of Bayesian models were specified: a model that only uses the individual dichotomous test results and a continuous model that uses the quantitative information of the EIA (i.e., the signal-to-cutoff values). Overall, we found that adjusted prevalence estimates matched the surveys’ original results, with overlapping uncertainty intervals. This suggested that misclassification of HIV status should not affect the prevalence estimates in most surveys. However, our analyses suggested that two surveys may be problematic. The prevalence could have been overestimated in the Uganda AIDS Indicator Survey 2011 and the Zambia Demographic and Health Survey 2013-14, although the magnitude of overestimation remains difficult to ascertain. Interpreting results from the Uganda survey is difficult because of the lack of internal quality control and potential violation of the multivariate normality assumption of the continuous Bayesian latent class model. In conclusion, despite the limitations of our latent class models, our analyses suggest that prevalence estimates from most of the surveys reviewed are not affected by sample misclassification.
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www.jogh.org • doi: 10.7189/jogh.02.020405 ~ December 2012 • Vol. 2 No. 2 • 020405
Background: Understanding the natural course of child and adolescent posttraumatic stress disorder (PTSD) has significant implications for the identification of, and intervention for, at-risk youth. We used a meta-analytic approach to examine longitudinal changes in youth PTSD
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prevalence and symptoms over the first 12 months posttrauma.
Journal of Child Psychology and Psychiatry57:8 (2016), pp 884–898
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10th edition
The IDF Diabetes Atlas 10th edition provides detailed information on the estimated and projected prevalence of diabetes, globally, by region, country and territory, for 2021, 2030 and 2045. It draws attention to the growing impact of d
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iabetes across the world and highlights proven and effective actions that governments and policy-makers must urgently take to tackle it.
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Reporting period: January 2014 – December 2014
The human immunodeficiency virus (HIV) epidemic in Myanmar is concentrated among men who have sex with men (MSM), people who inject drugs (PWID) and female sex workers (FSW). HIV prevalence in th
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e adult population aged 15 years and older was estimated at 0.54% in 2014. But data from HIV Sentinel Sero-Surveillance (HSS) indicates higher prevalence in 2014 among key populations: FSW 6.3%, MSM 6.6% and PWID 23.1%. Compared to 2012 data, the prevalence has declined from 7.1% in FSW and 8.9% in MSM, but has increased from 18% in PWID.
Epidemiological modelling suggests that in 2014 there were around 212,000 people living with HIV (PLHIV) in Myanmar, 34% of whom were females. Nearly 11,000 people died of HIV-related illnesses, compared to approximately 15,000 in 2011. An estimated 9,000 new infections occurred in 2014.
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The Lancet Published Online
October 8, 2021 https://doi.org/10.1016/ S0140-6736(21)02143-7
Global and regional estimates of violence against women
he report presents the first global systematic review of scientific data on the prevalence of two forms of violence against women: violence by an intimate partner (intimate partner violence) a
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nd sexual violence by someone other than a partner (non-partner sexual violence). It shows, for the first time, global and regional estimates of the prevalence of these two forms of violence, using data from around the world. Previous reporting on violence against women has not differentiated between partner and non-partner violence. You can download the report in different languages
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DHS Working Papers No. 85
Analysis of microfilaria prevalence data from 430 communities
PLoS ONE 12(7): e0180996. https://doi.org/10.1371/journal.pone.0180996
PLOS ONE 10(12): e0144040. doi:10.1371/journal.pone.0144040