Precision medicine is an emerging approach for disease treatment and prevention that considers individual variability in genes, environment, and lifestyle for each person. Big data analytics (BDA) using cutting-edge technologies helps to design models that can diagnose, treat and predict diseases. In Ethiopia, healthcare service delivery faces many challenges specifically in relation to prescribing the right medicine to the right patient at the right time. Thus, patients face challenges ranging from staying on treatment plans longer, and then leaving treatment, and finally dying of complications. Therefore, the aim of this paper is to explore the trends, challenges, and opportunities of applying BDA in precision medicine globally and take lessons for Ethiopia through a systematic literature review of 19 peer reviewed articles from five databases. The findings indicated that cancer in general, epilepsy, and systemic diseases altogether are areas currently getting big attention. The challenges are attributed to the nature of health data, failure in collaboration for data sharing, ethical and legal issues, interoperability of systems, poor knowledge skills and culture, and poor infrastructure. Development of modern technologies, experimental technologies and methods, cloud computing, Internet of Things, social networks and Ethiopia’s government initiative to promote private technological firms could be an …

This study explores the research productivity of Addis Ababa University (AAU) faculty. AAU was established in 1950 and is the oldest modern higher educational institution in Ethiopia. Recently AAU took steps to transform itself to become a pre-eminent African research university. One of the characteristics of a research university is the focus on the amount of research conducted by the institution's faculty. Academic institutions measure research productivity primarily based on published work. The purpose of this study was to analyze the research productivity of AAU faculty, and to examine the differential predictive effects of individual and environmental variables on faculty research productivity. This quantitative study used a theoretical framework and instrument, Faculty at Work. Four hundred questionnaires were distributed to Addis AAU faculty in person and 298 questionnaires were returned resulting in a 74.5% response rate. After exclusion of 12 cases with missing information, 286 cases (71.5% response rate) were analyzed. Most of the respondents were men (M = 92.1%, F = 7.9%). The average age of AAU faculty was 44. A hierarchical multiple regression was used to examine the ability of six sets of independent variables (sociodemographic, career, self-knowledge, social knowledge, behavior, and environmental response) to predict research productivity …

This comprehensive atlas provides data, satellite imagery, and analysis of the environmental conditions and issues relevant to each African country, and several surrounding island nations. The atlas also covers trans-border international issues in Africa.