Statistical Report No 24: 2014
Trials (2017) 18:152, DOI 10.1186/s13063-017-1881-z
DHS Further Analysis Reports No 102
A systematic review informing a radical transformation of health workforce development
Manual for Training in Cancer Control
Thirty-three years after its discovery, the Human Immunodeficiency Virus (HIV), responsible for the AIDS pandemic, remains a major public health problem despite advanced researches providing better diagnostic and therapeutic tools. The virus targets especially CD4+ T cells, leading to deficiency of ...the immune system and altering therefore defense against infections and cancer cells. Antiretroviral
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Document No. : FDA/SMC/SMD/GL-SMP/2015/05 |
These guidelines are for information, guidance and strict compliance by Marketing Authorization Holders and Local Representatives of regulated products to help in the continuous safety monitoring of products granted marketing authorization in Ghana.
Scientific brief
8 April 2020
Scientific Brief, 30 June 2020
The primary aim of this assessment is to evaluate current approaches to malaria surveillance in Myanmar and to provide a set of practical and feasible recommendations to further strengthen the surveillance system in the short to medium term. The assessment focuses on the surveillance of malaria case...s (as distinct from more general surveillance to support monitoring and evaluation) and, more specifically, on instruments and systems to collect, collate, report and analyse malaria data as a basis for informing malaria control policy and practice.
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This article is part four in a series of explainers on vaccine development and distribution
Available in different languages
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 misclassification 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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DHS Working Papers No. 69
This paper uses data from the three Indian National Family Health Surveys (1992-93, 1998-99, 2005-06) to examine how the relationship between household wealth and child mortality evolved during a time of significant economic change in India. The main predictor is a new... measure of household wealth that captures changes in wealth over time. Outcomes include neonatal mortality, postneonatal mortality, child mortality, and under-five mortality. Multivariate analysis is conducted at the national, urban, rural, and regional levels.
Results indicate that the overall relationship between household wealth and mortality weakened over time, as evidenced by the coefficients for under-five mortality at the national level.
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