The Rwandan Ministry of Health recognizes the threat that Non-Communicable Diseases (NCDs) pose to health and development in Rwanda and in 2009 articulates strategies to respond to them in the Health Sector Strategic Plan 2012 - 2018 (HSSP3). Among other things, the plan calls for a national prevale...nce survey on NCD risk factors. This report responds to that call and summarizes the findings of the first NCD risk factor survey in Rwanda conducted from November 2012 to March 2013.
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This document aims to provide concrete, pragmatic guidance for how TB modelling and related technical assistance is undertaken to support country decision-making. The target audience for this document are the participants and stakeholders in country-level TB modelling efforts, including the individu...als who build and apply models; policy-makers, technical experts and other members of the TB community; international funding and technical partners; and individuals and organizations engaged in supporting TB policy-making.
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Children in refugee situations face many potential dangers, such as violence, abuse, exploitation, discrimination, separation from their families, trafficking and military recruitment. The impact of these experiences can be devastating and long-lasting. Children have different needs from adults and ...these needs can only be identified and met if they are approached in a way that is specific to children.
The impact of the COVID-19 global pandemic has exacerbated the dangers faced by children in refugee situations and laid bare the need for their protection and for ensuring that all their human rights are upheld all the time.
The goal of this publication is to share examples of approaches by members of the Initiative that have proven effective for children.
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This report looks at how the current implications of COVID-19 is exacerbating key challenges for people who menstruate around the world and provides recommendations on how to include menstrual hygiene management (MHM) within a COVID-19 response.
Health Systems in Transition. Vol. 5 No.3 2015
Twenty-Fourth Annual Trachoma Control Program Review, Summary Proceedings
Ade et al. BMC Health Services Research (2016) 16:5
Background: In the “Centre National Hospitalier de Pneumo-Phtisiologie” of Cotonou, Benin, little is known about
the characteristics of patients who have not attended their scheduled appointment, the results of tracing and the
possible b...enefits on improving treatment outcomes. This study aimed to determine the contribution of tracing
activities for those who missed scheduled appointments towards a successful treatment outcome.
Methods: A retrospective cohort study was carried out among all smear-positive pulmonary tuberculosis patients
treated between January and September 2013. Data on demographic and diagnostic characteristics and treatment
outcomes were accessed from tuberculosis registers and treatment cards. Information on those who missed their
scheduled appointments was collected from the tracing tuberculosis register. A univariate analysis was performed
to explore factors associated with missing a scheduled appointment
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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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