Since the description of the first case of COVID-19 in Wuhan, Hubei province in China, in December 2019, much knowledge has been accumulated about the dynamics of evolution of the SARS-CoV-2 virus, contagion, disease progression, prevention and treatment.
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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A One Health Response. A Briefing Note
This briefing paper provides an overview of pre-exposure prophylaxis (PrEP) for people planning, commissioning or providing HIV prevention activities in the UK. It does this by reviewing thirty key questions about PrEP and how it might be implemented in the UK.
The Myanmar National Framework seeks to achieve people-centered, inclusive, and sustainable socioeconomic development in the face of disasters triggered by natural hazards and climate change. The framework articulates a common understanding, proposes a coherent approach, and identifies potential opp...ortunities for strengthening the resilience of communities in Myanmar.
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Lancet Glob Health 2022; 10: e491–500
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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