Dire Dawa University

About: Dire Dawa University is a education organization based out in Dire Dawa, Ethiopia. It is known for research contribution in the topics: Population & Health care. The organization has 183 authors who have published 194 publications receiving 2614 citations. The organization is also known as: የድሬዳዋ ዩኒቨርሲቲ & DDU.

Association between weather data and COVID-19 pandemic predicting mortality rate: Machine learning approaches

Abstract: Nowadays, a significant number of infectious diseases such as human coronavirus disease (COVID-19) are threatening the world by spreading at an alarming rate. Some of the literatures pointed out that the pandemic is exhibiting seasonal patterns in its spread, incidence and nature of the distribution. In connection to the spread and distribution of the infection, scientific analysis that answers the questions whether the next summer can save people from COVID-19 is required. Many researchers have been exclusively asked whether high temperature during summer can slow down the spread of the COVID-19 as it has with other seasonal flues. Since there are a lot of questions that are unanswered right now, and many mysteries aspects about the COVID-19 that is still unknown to us, in-depth study and analysis of associated weather features are required. Moreover, understanding the nature of COVID-19 and forecasting the spread of COVID-19 request more investigation of the real effect of weather variables on the transmission of the COVID-19 among people. In this work, various regressor machine learning models are proposed to extract the relationship between different factors and the spreading rate of COVID-19. The machine learning algorithms employed in this work estimate the impact of weather variables such as temperature and humidity on the transmission of COVID-19 by extracting the relationship between the number of confirmed cases and the weather variables on certain regions. To validate the proposed method, we have collected the required datasets related to weather and census features and necessary prepossessing is carried out. From the experimental results, it is shown that the weather variables are more relevant in predicting the mortality rate when compared to the other census variables such as population, age, and urbanization. Thus, from this result, we can conclude that temperature and humidity are important features for predicting COVID-19 mortality rate. Moreover, it is indicated that the higher the value of temperature the lower number of infection cases.

Breeding Sites of Aedes aegypti: Potential Dengue Vectors in Dire Dawa, East Ethiopia

Abstract: Background and Objectives. Entomological survey was carried out from May-June to September-October 2014 to investigate the presence of dengue vectors in discarded tires and artificial water containers in houses and peridomestic areas. Methods. A cross-sectional immature stage survey was done indoors and outdoors in 301 houses. Mosquito larval sampling was conducted using pipette or dipper depending on container types. Larvae were identified morphologically and larval indices were also calculated. Results. A total of 750 containers were inspected, and of these 405 were positive for mosquito larvae. A total of 1,873 larvae were collected and morphologically identified as Aedes aegypti (n = 1580: 84.4%) and Culex (n = 293: 15.6%). The larval indices, house index, container index, and breteau index, varied from 33.3 to 86.2, from 23.2 to 73.9, and from 56.5 to 188.9, respectively. Conclusion. Aedes aegypti is breeding in a wide range of artificial containers. To control these mosquitoes, the integration of different methods should be taken into consideration.

Environmental sustainability and economic development in sub-Saharan Africa: A modified EKC hypothesis

Abstract: Despite numerous studies of the Environmental Kuznets Curve (EKC), the evidence is still inconclusive and little has been done to capture the issue of environmental sustainability and welfare aspects of growth in the EKC relationship. Accordingly, this paper aims to investigate the environment-development linkage under a sustainability-oriented EKC framework in 20 sub-Saharan African (SSA) countries for the period from 1990 to 2015. The Common Correlated Effects version of Pooled Mean Group Estimator (CCE-PMG) in the context of error-correction based panel Autoregressive Distributed Lag (ARDL) model augmented with cross-sectional averages was employed as a preferred estimation technique. The study also used an appropriate U test to check the presence of genuine inverted U-shaped EKC relationship. The results confirm the existence of a modified EKC hypothesis in SSA, but the linkage depends on the extent of endowment of natural resources. Among the growth-related factors, energy consumption and trade openness are found to have a long run detrimental effect on the environment. The study suggests that country's effort for economic development needs to be accompanied by appropriate policy options to ensure environmental sustainability.