PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002462 November 28, 2017
PLOS ONE | https://doi.org/10.1371/journal.pone.0185526 September 28, 2017
Global Health and Tropical Medicine, GHTM, Instituto de Higiene e Medicina Tropical, IHMT, Universidade Nova de Lisboa, UNL, Lisboa, Portugal
Clinical Medicine
JCI Insight. 2017;2(7):e91963.
Demographic Health Survey Working Paper 2017 No. 130
PLOS ONE | DOI:10.1371/journal.pone.0172392 February 16, 2017
Health Policy Plan (2017) 32 (5): 603-612; 10 pp. 318 kB
African Journal of Laboratory Medicine | Vol 7, No 2 | a796 | 06 December 2018
Original Research
African Journal of Primary Health Care & Family Medicine
ISSN: (Online) 2071-2936, (Print) 2071-2928
Open Access
PLOS ONE | https://doi.org/10.1371/journal.pone.0186835 October 30, 2017
Nationally, Senegal met the MDG target for water supply access. It did this by engaging the public and private sectors to effectively invest and report on investments. It focused on larger population centers, less on remote regions of the country. Its achievements set the stage for more equitable an...d widespread service provision as the country now works to achieve the SDGs, requiring sustainable management of universal access. This case study documents the progression of the sector between 1990 and 2015, and analyzes the impact of local systems created in Senegal to respond to the water and sanitation challenge.
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USAID/Afghanistan’s $443 million investment in the Afghan Sustainable Water Supply and Sanitation (SWSS) activity is one of the Agency’s largest single investments in sustainable rural water supply delivery. The project installed about 2,123 wells with hand pumps across Afghanistan from 2009–2...012. This report presents findings from a retrospective evaluation of a random selection of wells with hand pumps installed under the SWSS project.
This evaluation’s key purpose is to identify factors that support and hinder sustainable water service delivery in different contexts.
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Pan African Medical Journal 2017;27:215. doi: 10.11604/pamj.2017.27.215.12994
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 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.
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PLoS ONE 12(7): e0180996. https://doi.org/10.1371/journal.pone.0180996
Environmental pollution, protection, quality and sustainability