Expanded IMPACT Program in Zimbabwe
Lea Toto and APHIAplus Nuru ya Bonde programs in Kenya Yekokeb Berhan Program for Highly Vulnerable Children in Ethiopia
The Lancet Global Health, published online 18 August 2017;
http://dx.doi.org/10.1016/S2214-109X(17)30332-7
Regional Operational Plan 2016 FY17 Strategic Direction Summary
2 May 2016
This assessment seeks to better understand what types of legal migration pathways and other protection services Iraqi refugees and other migrants are aware of and attempt to access at different points during their migration journey. Furthermore, it highlights when, where and why Iraqi refugees and o...ther migrants fail to access protection services.
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Tropical Medicine and Infectious Disease 2017, 2(4), 50
This is a cross-sectional analysis of baseline data in a longitudinal study on asymptomatic, LF antigen-positive and -negative young people in Myanmar. Rapid field screening was used to identify antigen-positive cases and a group of antige...n-negative controls of similar age and gender were invited to continue in the study. ... Results demonstrate that sub-clinical changes associated with infection can be detected in asymptomatic cases. Further exploration of these low-cost devices in clinical and research settings on filariasis-related lymphedema are warranted.
https://doi.org/10.3390/tropicalmed2040050
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This is an update of a seven-year TB and Leprosy national strategic plan (TBL-NSP), which extends from 2013 to 2020. The update focuses on the plan covering from 2017-20 and is based on the 2017 external mid-term programme review key findings and recommendations; the global and national End TB strat...e-gies and targets; stakeholders consultation and recent revision of the national TB guidelines.
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Review
Journal of Virus Eradication 2016 Jul; 2(3): 156–161.
Published online 2016 Jul 1.
PMCID: PMC4967967
PMID: 27482455
DHS Analytical Studies No. 57
Research Article
Journal of Addiction
Volume 2016, Article ID 2476164, 8 pages
http://dx.doi.org/10.1155/2016/2476164
Sudan Medical and Scientific Research Institute, Khartoum, Sudan
Received 26 November 2015; Accepted 27 January 2016
The 2012 NDRMP lays out the Disaster Risk Management (DRM) architecture of the country and provides guidance for DRM intervention at all levels. However, implementation has been slow and resource challenges exist throughout the government.
The PNG government’s policy and institutional framework... for DRM still faces numerous obstacles. The main challenges in moving towards a more proactive and systematic approach to manage risks and build resilience include 1.) the limited coordination between DRM and Climate Change Adaptation agencies; 2.) the slow migration from emphasis on response to risk reduction and management; 3.) the limited institutional capacity for planning and design of risk informed investments; and 4.) the lack of available historic natural hazard data, which hinders the assessment of risks.
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This module carries pre-training entry level assessment as well as hands on exercise manual on Geographic Information Systems, Remote Sensing, Geographic Positioning System (GPS) and some applications of these technologies on Disaster Risk Management (DRM) especially for hazard mapping, monitoring a...nd risk assessment module as well as the damage assessment module. Practical manual developed using open source products like Quantum GIS , RStudio, Google Earth Pro and Google Earth Engine.
This module can also can be used by other training facilitators, non-technical professionals and selflearners as well. However, it is strongly recommended that training participants and self-learners already have some basic knowledge of Computer Basic, Geoinformatics and disaster management.
No publication year indicated.
Original file: 29,5 MB
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The need for a roadmap for risk assessment stemmed from the lack of standardised and systematic effort to national risk assessment effort to date. The road map details the process, activities necessary for each step and the availability and accessibility of technical and financial resources, and coo...rdination mechanisms for the implementation f a national risk assessment.
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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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DHS Methodological Report No. 20
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally used additive methods with a data reduction method—principal component analysis (PCA).
We scored ...the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index.
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