THE REPUBLIC OF BOTSWANA | MINISTRY OF HEALTH | DEPARTMENT OF PUBLIC HEALTH | NATIONAL MALARIA CONTROL PROGRAMME
Timely detection of novel coronavirus (2019-nCoV) infection cases is crucial to interrupt the spread of this virus. We assessed the required expertise and capacity for molecular detection of 2019-nCoV in specialised laboratories in 30 European Union/European Economic Area (EU/EEA) countries. Thirty-...eight laboratories in 24 EU/EEA countries had diagnostic tests available by 29 January 2020. A coverage of all EU/EEA countries was expected by mid-February. Availability of primers/probes, positive controls and personnel were main implementation barriers.
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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
Rashtriya Bal Swasthya Karykram (RBSK). Operational Guidelines
Lancet Glob Health 2022; 10: e491–500
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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