PLoS Negl Trop Dis 11(2): e0005356 -Published: February 23, 2017 21 pp
Guidelines
June 2017
HIV strategic information for impact
The report offers 20 top recommendations for getting ahead of future outbreaks in Yemen and similarly complex humanitarian settings.
In 2015, Yemen was declared a Level 3 emergency by the UN, kicking into gear the highest level of humanitarian support. A massive cholera outbreak followed, leading t...o 1 million suspected cases in 2 waves from September 2016-July 2018.
“We largely know ‘what to do’ to control cholera, but context-specific practices on ‘how to do it’ in order to surmount challenges to coordination, logistics, insecurity, access and politics remain needed,” the report states.
While the response improved between the 2 waves, there were gaps. For one, Yemen’s history of cholera should have triggered a heavy focus on pre-planning for an epidemic, such as stockpiling supplies and doubling down on community-based surveillance, the report fou
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The objective of this document is to guide the preparation and implementation of national preparedness plans for the safety of substances of human origin during outbreaks of Zika virus infection, both in affected and non-affected areas.
The main objectives of the SOPs are to: (i) establish standards and timelines for response activities; and (ii) guide national governments and GPEI partners in key support functions.
This new version of the SOPs presents overall response requirements for dealing with type 1, 2 and 3 poliovirus fo...llowing monovalent type 2 oral polio vaccine (mOPV2) cessation. Version 2.4 will be valid until release of revised version 3.0 (anticipated May 2018).
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A GUIDE FOR HEALTH WORKERS AND AUTHORITIES IN NIGERIA
Outstanding child and adolescent TB priorities include the need to: find the missing children with active TB and link them to TB care; prevent TB in children who are in contact with infectious TB cases (through implementation of active contact investigation and provision of preventive treatment); an...d advance integration within general child health services, including maternal and child health/ reproductive, maternal, newborn, child and adolescent health, HIV, nutrition and other programmes.
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The classification of digital health interventions (DHIs) categorizes the different ways in which digital and mobile technologies are being used to support health system needs. Historically, the diverse communities working in digital health—including government stakeholders, technologists, clinic...ians, implementers, network operators, researchers, donors— have lacked a mutually understandable language with which to assess and articulate functionality. A shared and standardized vocabulary was recognized as necessary to identify gaps and duplication, evaluate effectiveness, and facilitate alignment across different digital health implementations. Targeted primarily at public health audiences, this Classification framework aims to promote an accessible and bridging language for health program planners to articulate functionalities of digital health implementations.
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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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Molecular methods for antimicrobial resistance (AMR)diagnostics to enhance the Global Antimicrobial Resistance Surveillance System
The objectives of pertussis surveillance are to:hmonitor disease burden and the impact of the pertussis vaccination programme, with a special focus on understanding the morbidity and mortality in children < 5 years of agehgenerate data to inform vaccine schedule and delivery strategy decisions to op...timize the impact of vaccinationhdetect and guide public health response to outbreaks of pertussis
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