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Publication Years
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Toolboxes
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2
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Further Analysis of the 2000, 2005, and 2011 Demographic and Health Surveys. DHS Further Analysis Reports No. 79
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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
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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 Methodological Report No. 20
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally used additive methods with a data reduction method—principal component analysis (PCA).
We scored ... the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index. more
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally used additive methods with a data reduction method—principal component analysis (PCA).
We scored ... the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index. more
The Essential WASH Actions toolkit expands the connection between WASH and nutrition. This resource offers a comprehensive set of essential WASH actions, references training materials for health workers, nutrition managers and community workers to build capacity, and outlines accompanying behaviors
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needed to support the Essential Nutrition Actions.
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Through public-private partnerships, the government of Rwanda can make more efficient use of public resources by targeting and meeting the needs of specific populations and thus help ensure family planning services and products will be available to all Rwandans in the long term. This report aims to
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inform stakeholders working to strengthen family planning through multisectoral partnerships about Rwanda’s family market.
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The Capacity Project worked to strengthen HRIS in several low-resource countries to assist decision-makers and human resources managers in identifying and responding to critical gaps in HRH. The findings and recommendations in this report cover the Capacity Project’s implementation of HRIS in Swaz
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iland, Rwanda and Uganda.
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This toolkit provides practical guidance to governments, funders, civil society organizations and other implementing partners on conducting a gender analysis and using findings to inform HIV prevention, care and treatment programs with key populations. It outlines considerations and steps for conduc
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ting a gender analysis; explores how to engage with stakeholders, including key population members, in a meaningful partnership; shares lessons learned from a comprehensive gender analysis in Kenya and an abridged gender analysis in Cameroon; and provides tools and resources for conducting a gender analysis with key populations.
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