October 2018
HIV testing services
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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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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CBM and the Global Campaign for Education 2014
Weekly Epidemiological Record. This report summarizes application of the SAFE strategy against trachoma during 2023. It includes estimates of the global population at risk of trachoma blindness based on district-by-district data submitted to WHO by national programmes. Summarizing the epidemiologica...l situation in this way is inherently complex because, for any district, up to 3 serial estimates of prevalence may be valid at different times during a calendar year.
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Cureus 2024 Jan 16;16(1):e52358. doi: 10.7759/cureus.52358
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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Vector-borne diseases are responsible for 17% of the global burden of communicable diseases and more than 500 000 deaths annually. The ambitious global targets for the control of vector-borne diseases come in the context of the (re-)emergence of diseases, increasing resistances to insecticides and u...ncertainty related to the financing of global vector control efforts. The United Nations 2030 Agenda with its related Sustainable Development Goals (SDGs), the New Urban Agenda adopted at the United Nations Conference on Housing and Sustainable Urban Development (Habitat III)
in Quito in 2016 and WHO’s Global vector control response 2017–2030 (WHO, 2017a) emphasize the value of elevating multisectoral actions and strategies that extend beyond the health sector to the core of integrated vector control.
This policy brief underlines the important role housing conditions have in the transmission of vector-borne diseases and showcases interventions and policies the housing sector can contribute to effective, integrated and intersectoral vector-borne diseases management.
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IN THE AMOUNT OF SDR 21.8 MILLION (US$30 MILLION EQUIVALENT) WITH AN ADDITIONAL GRANT FROM THE GLOBAL FINANCING FACILITY (GFF) IN THE AMOUNT OF US$ 10 MILLION TO THE DEMOCRATIC REPUBLIC OF CONGO FOR A HUMAN DEVELOPMENT SYSTEMS STRENGTHENING PROJECT