The primary objectives of the 2017 TMIS are to measure the level of ownership and use of mosquito nets; assess coverage of intermittent preventive treatment for pregnant women; identify treatment practices, including the use of specific antimalarial medications to treat malaria among c...hildren age 6-59 months; measure the prevalence of malaria and anemia among children age 6-59 months; and assess knowledge, attitudes, and practices among adults with malaria.
This table provides estimates of key indicators for the country as a whole and for each of the 31 geographic regions in Tanzania. A comprehensive analysis of the 2017 TMIS data will be presented in a final report.
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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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The National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect data for monitoring progress on health programs and policies in Rwanda. This publication ill...ustrates the profile of Kigali City
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he National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect data for monitoring progress on health programs and policies in Rwanda. This publication illu...strates the profile of Northern Province.
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The Demographic Dividend study on Rwanda assessed the socio-economic and human development potential of our country in the short, medium and long-term period using a comprehensive approach. It generated relevant policy and programme information to guide a well-informed polciy required to propel Rwan...da towards achieving its aspirations of being high middle income country by 2035 and high income country by 2050.
The primary objectives of this study were to assess Rwanda’s prospects for harnessing the demographic dividend and demonstrate priority policy and programme options that the country should adopt in order to optimise its chances of earning a maximum demographic dividend in the context of its youthful population and medium, long-term socio-economic development aspirations.
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This report presents the findings of the Estimating the Size of Populations through a Household Survey (ESPHS) study that took place in 2011. The study utilized a single household survey to estimate the size of several key populations, including sex workers, men who have sex with men (MSM), injectin...g drug users (IDU), and clients of sex workers. These populations include several groups outlined in the National Strategic Plan for HIV and AIDS as most at risk for HIV infection, specifically sex workers and MSM.
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La deuxième Enquête sur la prestation des services de soins de santé du Rwanda (EPSR-II), réalisée en 2007, est une enquête représentative au niveau national au cours de laquelle un échantillon de 538 établissements de santé ont été enquêtés. L’enquête a couvert les ôpitaux, les ce...ntres de santé, les dispensaires et les postes de santé et a inclus tous les établissements publics, qu’ils appartiennent au secteur gouvernemental ou Agréé, et la plupart des établissements privées. L’EPSR-II a collecté des informations sur les capacités des
établissements à fournir des services de qualité ainsi que sur l’existence de systèmes effectifs garantissant des services de qualité, par le biais d’interviews effectuées auprès des prestataires de santé et des patients ainsi que par le biais d’observations de consultations de patients ; ces informations concernent essentiellement l’infrastructure d’ensemble de l’établissement ainsi que les services de santé maternelle, infantile, de santé de la reproduction, de tuberculose, du paludisme, des infections sexuellement transmissibles (IST) et du VIH/sida. L’objectif de cette étude est, d’une part, d’évaluer les forces et faiblesses de l’infrastructure et des systèmes de support de ces services et, d’autre part, d’évaluer le niveau d’adhésion des prestataires aux standards de prestation des services.
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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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Vous trouverez dans les pages suivantes de la documentation promotionnelle, y compris les documents d’informations, les affiches, les messages postés sur les réseaux sociaux et les autres ressources sur la vaccination, qui vous permettront de densifier les activités en cours et de faciliter les... communications au cours de la semaine. N’hésitez pas à personnaliser et adapter la documentation aux besoins spécifiques de votre pays.
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DHS Further Analysis Reports No. 111
This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health facility delive...ry, and timely postnatal care (PNC).
This study uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12 regions. We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use. We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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DHS Further Analysis Reports No. 88 - This further analysis examines levels, trends, and determinants of neonatal mortality in Rwanda, using data from the 2000, 2005, and 2010 Rwanda Demographic and Health Surveys (RDHS).
‘Do not underestimate the capacity of the community; they are smarter and more capable than you think’
Towards attaining the highest standard Health.
Further analysis of the 1996, 2001, and 2006 Demographic and Health Surveys Data
Advancing Health, Learning and Equity through WASH in Schools