Les résultats provisoires du recensement de la population réalisé en 2008 et en particulier celui des personnes handicapées montrent l'étendue des besoins et la nécessité de poursuivre nos actions pour améliorer les conditions de vie de ces personnes au Burundi.
The major areas of focus for the plan will be:
- Social mobilization and community empowerment (health promotion & education for disease prevention);
- Promotion of access to safe water, good sanitation and hygiene;
- Surveillance and laboratory confirmation of outbreaks;
- Prom...pt case management and infection control;
- Complementary use of oral cholera vaccine (OCV) for cholera endemic communities; and
- Coordination and stewardship between and for all actors.
- Monitoring, supervision, evaluation and operation research to ensure continued improvement in service delivery.
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This Technical Brief focuses on appraising and prioritising options for climate resilience with a view to informing water, sanitation and hygiene (WASH) programme and project design.
This Technical Brief:
- provides a simple scorecard/checklist approach to use as a starting point for appr...aising and prioritising options, and as an awareness-raising activity - covers all aspects of WASH
- has a predominantly rural focus, to align with the rest of the Strategic Framework and Technical Briefs
- focuses on current and near future options over the next 15–20 years, which fits in with WASH programming timescales and development
- includes WASH examples to show how the approach can be applied.
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The main objective of the 2014-15 RDHS was to obtain current information on demographic and health indicators, including family planning; maternal mortality; infant and child mortality; nutrition status of mothers and children; prenatal care, delivery, and postnatal care; childhood diseases; and ped...iatric immunization. In addition, the survey was designed to measure indicators such as domestic violence, the prevalence of anemia and malaria among women and children, and the prevalence of HIV infection in Rwanda. For the first time, this 2014-15 RDHS also includes indicators to monitor HIV testing among children age 0-14 as well as domestic violence for males age 15-59.
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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 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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This report complements the previous poverty analysis studies by presenting a series of poverty maps of Rwanda at cell and sector levels, based on data from EICV4 and the 2012 Population and Housing Census. A poverty map is simply a map that shows the incidence of poverty in different areas of the c...ountry. It allows the viewer to appreciate, at a glance, the geographic dimensions of poverty. Apart from their intrinsic interest, poverty maps may be used to help guide the allocation of resources across local agencies or governmental units, in an effort to better target efforts to reach the poor by pinpointing the small areas of most need.
In 2015, the National Institute of Statistics of Rwanda (NISR) published the Rwanda Poverty Profile Report which provided a detailed portrait of the extent and nature of poverty in the country, while in 2016 a Poverty Trends Analysis Report which complements the Profile study by looking at the trends in poverty between 2010/11 and 2013/14 was also published. Both reports were based on information collected by an integrated household living conditions survey (EICV4) undertaken between October 2013 and September 2014.
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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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Report on the nutrition and health situation of Nigeria
Data collection – 13th July to 13th September 2015
A call for national and regional containment, recovery and prevention
MMWR Morbidity and Mortality Weekly Report December 19, 2014 / 63(50);1205-1206
Weekly epidemiological record/Relevé épidémiologique hebdomadaire , 1ST SEPTEMBER 2017, 92th YEAR / no.35 (2017) 501-520