The ongoing COVID-19 pandemic has shown that public financial management (PFM) should be an integral part of the response. Effectiveness in financing the health response depends not only on the level of funding but also on the way public funds are allocated and spent, this is determined by the PFM r...ules, and how money flows to health service providers. So far, early assessments have shown that PFM systems ranged from being a fundamental enabler to acting as a roadblock in the COVID-19 health response. While service delivery mechanisms have been extensively documented throughout the pandemic, the underlying PFM mechanisms of the response also merit attention. To highlight the importance of PFM in health emergency contexts, this rapid review analyses various country PFM experiences and identifies early lessons emerging from the financing of the health response to COVID-19. The assessment is done by stages of the budget cycle: budget allocation, budget execution, and budget oversight. Identifying lessons from the varying PFM modalities used to finance the response to COVID-19 is fundamental both for health policy-makers and for finance authorities to prepare for future health emergencies.
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"This is the final report of the six-year collaboration between the WHO Department of Mental Health and Substance Abuse and the Gulbenkian Global Mental Health Platform, an initiative of the Calouste Gulbenkian Foundation aimed at reducing the global burden of mental health through the development a...nd application of evidence and good practices to global mental health."
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A One Health Response. A Briefing Note
Twenty-Fourth Annual Trachoma Control Program Review, Summary Proceedings
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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Collection of country-level good practices
Monitoring implementation of the Dublin Declaration on Partnership to Fight HIV/AIDS in Europe and Central Asia: 2012 progress
Special Report
Of the 50 antibiotics in the pipeline, 32 target WHO priority pathogens but the majority have only limited benefits when compared to existing antibiotics. Two of these are active against the multi-drug resistant Gram-negative bacteria, which are spreading rapidly and require urgent solutions.
Gr...am-negative bacteria, such as Klebsiella pneumoniae and Escherichia coli, can cause severe and often deadly infections that pose a particular threat for people with weak or not yet fully developed immune systems, including newborns, ageing populations, people undergoing surgery and cancer treatment.
The report highlights a worrying gap in activity against the highly resistant NDM-1 (New Delhi metallo-beta-lactamase 1), with only three antibiotics in the pipeline. NDM-1 makes bacteria resistant to a broad range of antibiotics, including those from the carbapenem family, which today are the last line of defence against antibiotic-resistant bacterial infections.
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