The Standard consists of nine key inclusion standards, and seven sets of sector-specific inclusion standards for protection – water, sanitation and hygiene, food security and livelihoods, nutrition, shelter, settlement and household items, health and education. Each standard comes with key actions..., guidance, tools and resources.
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Program Report for Collaborative Agreement: DFD-A-00-08-00309-00 September 30, 2008 -December 31, 2015
Int Health. 2012 December 1; 4(4): 253–259. doi:10.1016/j.inhe.2012.07.001
This report outlines the results of a scientific study of the impacts of weather, climate variability, and climate change on health in Mozambique, with a focus on diarrheal disease and malaria.
This revision covers the main non-communicable diseases in Mozambique as well as the National Strategic Plan's aim to create a positive environment to minimize or eliminate the exposure to risk factors and guarantee access to care.
The 2013 RMIS is a nationally representative, household-based survey that provides data on malaria indicators, which are used to assess the progress of a malaria control program. The primary objective of the 2013 Rwanda Malaria Indicator Survey (2013 RMIS) was to provide up-to date information on th...e prevention of malaria to policymakers, planners, and researchers.
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This report provides an overview of the Key findings of the Rwanda 2014-2015 Demographic and Health Survey (RDHS). The 2014-15 Rwanda Demographic and Health Survey (RDHS) was designed to provide data for monitoring the population and health situation in Rwanda. The 2014-15 RDHS is the fifth Demogra...phic and Health Survey
conducted in Rwanda since 1992. The objective of the survey was to provide reliable estimates of fertility levels, marriage, sexual activity, fertility preferences, family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, early childhood development, malaria, domestic violence, and HIV/AIDS and other sexually transmitted infections (STIs) that can be used by program managers and policymakers to evaluate and improve existing programs.
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(August 28 – October 10, 2017)
A nutrition and mortality assessment using SMART methodology was applied and the survey covered 15 statistical (14 districts plus 1) domains countrywide. The main objective of the survey was to assess the current nutrition status of the population, especially ch...ildren 6-59 months old and women of reproductive age (15-49 years of age). The survey also looked at the major contextual factors contributing to undernutrition such as infant and young child feeding (IYCF) practices; food security indicators; water, sanitation and hygiene indicators; and health situation in Sierra Leone
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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 ...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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