DHS Further Analysis Reports No. 109 - This report documents trends in key child nutrition indicators in Rwanda. Data from the Demographic and Health Surveys (DHS) in 2005, 2010, and 2014-15 were analyzed, disaggregated by selected equity-related variables, and tested for trends. Over the survey per...iod, Rwanda had high rates of exclusive breastfeeding, with regional variation. Rates of continued breastfeeding were also high but generally decreased as mother’s education and household wealth increased in all survey years. Complementary feeding practices varied by region, mother’s education, household wealth, urban-rural residence, and sex of the child.
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Health Systems in Transition. Vol. 5 No.3 2015
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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A supplement to The State of the World’s Children Report 2009
La Enfermedad por el Virus de la Chikungunya – EVCH fue descrita por primera vez durante un brote ocurrido en 1952 al sur de Tanzania, su nombre es de origen makonde, grupo étnico que vive en esa región, que significa “aquel que se encorva” o “retorcido”, que describe la apariencia inc...linada de las personas que sufren la enfermedad, por las artralgias intensas que la caracterizan
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Statement
Impact of migration on infectious diseases in Europe | August 2007 | 1-7
The Kenya Essential Medicines List 2019 is an indispensable guide to the medicines recommended for the management of common conditions in Kenya. It is primarily directed at health care providers and medicines supply managers in the public and non-public health sectors. It should be used together wit...h the current versions of updated national clinical guidelines for those conditions for which such guidelines exist
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Community Health Volunteers
Estimating the size of key affected populations (KAP) provides important data for planning and implementing an effective response to the HIV epidemic. In the Philippines, these KAP include males who have sex with males (MSM), female sex workers (FSW), and injecting drug users (IDU). Given the diffic...ulty in reaching these populations, as well as their high mobility, the process consequently entailed a specific methodology to directly estimate the size of KAP.
The national estimate of MSM was 531,500 or 2.2% (1.8%-3.2%) of males aged 15-49. Within this MSM estimate, figures for transgender women (TGW) and male transactional sex workers (MSW) were determined. The national estimate for TGW was 122,800 or about 0.50% (0.40%-0.75%) of males aged 15-49, and 23% of the MSM population. Meanwhile, MSW comprised 0.35% (0.29%-0.53%) of the male population aged 15-49 and 16% of the MSM population, giving a best estimate of 86,600.
The estimate of combined RFSW and FFSW was 66,100 or 0.28% (0.19%-0.40%) of females aged 15-49. Meanwhile, there are approximately 10,000 to 21,700 IDU or 0.04%-0.09% of males aged 15-49.
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