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Seebregts C.J.,eHealth Africa
Yearbook of medical informatics | Year: 2010

The overall objective of this project was to investigate ways to strengthen the OpenMRS community by (i) developing capacity and implementing a network focusing specifically on the needs of OpenMRS implementers, (ii) strengthening community-driven aspects of OpenMRS and providing a dedicated forum for implementation-specific issues, and; (iii) providing regional support for OpenMRS implementations as well as mentorship and training. The methods used included (i) face-to-face networking using meetings and workshops; (ii) online collaboration tools, peer support and mentorship programmes; (iii) capacity and community development programmes, and; (iv) community outreach programmes. The community-driven approach, combined with a few simple interventions, has been a key factor in the growth and success of the OpenMRS Implementers Network. It has contributed to implementations in at least twenty-three different countries using basic online tools; and provided mentorship and peer support through an annual meeting, workshops and an internship program. The OpenMRS Implementers Network has formed collaborations with several other open source networks and is evolving regional OpenMRS Centres of Excellence to provide localized support for OpenMRS development and implementation. These initiatives are increasing the range of functionality and sustainability of open source software in the health domain, resulting in improved adoption and enterprise-readiness. Social organization and capacity development activities are important in growing a successful community-driven open source software model. Source

Eyres P.J.,Netfuse Telecom | Brown L.,Netfuse Telecom | Rohan H.,eHealth Africa
Procedia Engineering | Year: 2015

The effectiveness of both emergency services and response planning functions in humanitarian response and public health crises are significantly enhanced by the availability of location services in mobile networks. Here we describe how eHealth Africa and Netfuse Telecom are working together to use mobile network location services to improve the operational effectiveness of the 117 Ebola response call centre and support decision making and resource allocation at the National Ebola Response Centre, which is coordinating the response to the Ebola epidemic in Sierra Leone. © 2015 The Authors. Published by Elsevier Ltd. Source

Van Zyl H.,eHealth Africa | Dartnall L.,Sexual Violence Research Initiative
Studies in Health Technology and Informatics | Year: 2010

This paper discusses an innovative 3-step eHealth approach to translate research for target audiences' knowledge uptake in developing countries. The first step uses a knowledge transfer model for the identification and packaging of health content as well as the selection of appropriate Information and Communication Technologies (ICT) platforms; followed by consumer health informatics studies to evaluate the efficacy of addressing health consumers' information needs; and the final step recommends forming of strategic partnerships to strengthen and support knowledge transfer and sharing. The 3-step eHealth approach is based on a convergence of ICTs, and application of the practices and principles of informatics and knowledge management. It was refined during the development of AfroAIDSinfo, an AIDS information portal of the SA Medical Research Council (MRC). The approach was evaluated during the forming of a strategic partnership between the AfroAIDSinfo project of the MRC's Web and Media Technologies Platform and the Sexual Violence Research Initiative. The successful outcome of the eHealth approach served to collect evidence for good practice in informatics and knowledge management. © 2010 IMIA and SAHIA. All rights reserved. Source

Murrell B.,Stellenbosch University | Murrell B.,eHealth Africa | Murrell B.,University of Cape Town | Moola S.,Stellenbosch University | And 8 more authors.
Molecular Biology and Evolution | Year: 2013

Model-based analyses of natural selection often categorize sites into a relatively small number of site classes. Forcing each site to belong to one of these classes places unrealistic constraints on the distribution of selection parameters, which can result in misleading inference due to model misspecification. We present an approximate hierarchical Bayesian method using a Markov chain Monte Carlo (MCMC) routine that ensures robustness against model misspecification by averaging over a large number of predefined site classes. This leaves the distribution of selection parameters essentially unconstrained, and also allows sites experiencing positive and purifying selection to be identified orders of magnitude faster than by existing methods. We demonstrate that popular random effects likelihood methods can produce misleading results when sites assigned to the same site class experience different levels of positive or purifying selection-an unavoidable scenario when using a small number of site classes. Our Fast Unconstrained Bayesian AppRoximation (FUBAR) is unaffected by this problem, while achieving higher power than existing unconstrained (fixed effects likelihood) methods. The speed advantage of FUBAR allows us to analyze larger data sets than other methods: We illustrate this on a large influenza hemagglutinin data set (3,142 sequences). FUBAR is available as a batch file within the latest HyPhy distribution (http://www.hyphy.org), as well as on the Datamonkey web server (http://www.datamonkey.org/). © 2013 The Author. Source

Kosakovsky Pond S.L.,University of California at San Diego | Murrell B.,Stellenbosch University | Murrell B.,eHealth Africa | Fourment M.,University of California at San Diego | And 3 more authors.
Molecular Biology and Evolution | Year: 2011

Adaptive evolution frequently occurs in episodic bursts, localized to a few sites in a gene, and to a small number of lineages in a phylogenetic tree. A popular class of "branch-site" evolutionary models provides a statistical framework to search for evidence of such episodic selection. For computational tractability, current branch-site models unrealistically assume that all branches in the tree can be partitioned a priori into two rigid classes - "foreground" branches that are allowed to undergo diversifying selective bursts and "background" branches that are negatively selected or neutral. We demonstrate that this assumption leads to unacceptably high rates of false positives or false negatives when the evolutionary process along background branches strongly deviates from modeling assumptions. To address this problem, we extend Felsenstein's pruning algorithm to allow efficient likelihood computations for models in which variation over branches (and not just sites) is described in the random effects likelihood framework. This enables us to model the process at every branch-site combination as a mixture of three Markov substitution models - our model treats the selective class of every branch at a particular site as an unobserved state that is chosen independently of that at any other branch. When benchmarked on a previously published set of simulated sequences, our method consistently matched or outperformed existing branch-site tests in terms of power and error rates. Using three empirical data sets, previously analyzed for episodic selection, we discuss how modeling assumptions can influence inference in practical situations. The Author 2011. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. Source

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