Intestinal Helminthes Infections and Re-Infections with Special Emphasis on Schistosomiasis Mansoni in Waja, North Ethiopia

To determine the status of infection and re-infection caused by Schistosoma mansoni in a small town of Waja, northern Ethiopia, stool samples were collected from primary school children in two rounds (in mid June and mid September 2004) and were examined using the Kato thick smear method. In addition, water bodies that might serve as biotopes for the intermediate host snails were located and searched using scoops. During the first survey, the prevalence of S. mansoni among the 224 children (119 male and 105 females) sampled was 27.1%. S. mansoni prevalence increased from 27.1% to 36.4% (P< 0.05), during the 2nd survey, three months following the treatment of the positive cases. Similarly, an increase in the prevalence of T. trichiura was observed (from 16 to 30.7%), whereas that of Ascaris lumbricoides decreased during the second survey (from 50 to 42.8%) (

Evaluation of regional climate models performance in simulating rainfall climatology of Jemma sub-basin, Upper Blue Nile Basin, Ethiopia

This study examines the performance of 10 Regional Climate Model (RCM) outputs which are dynamically downscaled from the fifth phase of Coupled Model Inter-comparison Project (CMIP5) GCMs using different RCMs parameterization approaches. The RCMs are evaluated based on their ability to reproduce the magnitude and pattern of monthly and annual rainfall, characteristics of rainfall events and variability related to Sea Surface Temperature (SST) for the period 1981–2005. The outputs of all RCMs showed wet bias, particularly in the higher elevation areas of the sub-basin. Wet bias of annual rainfall ranges from 9.60% in CCLM4 (HadGEM2-ES) model to 110.9% in RCA4 (EC-EARTH) model. JJAS (June-September) rainfall is also characterized by wet bias ranges from 0.76% in REMO (MPI-ESM-LR) model to 100.7% in RCA4 (HadGEM2-ES) model. GCMs that were dynamically downscaled through REMO (Max Planck Institute) and CCLM4 (Climate Limited-Area Modeling) performed better in capturing the rainfall climatology and distribution of rainfall events. However, GCMs dynamically downscaled using RCA4 (SMHI Rossby Center Regional Atmospheric Model) were characterized by overestimation and there are more extreme rainfall events in the cumulative distribution. Most of the RCMs’ rainfall over the sub-basin showed a teleconnection with Sea Surface Temperature (SST) of CMIP5 GCMs in the Pacific and Indian Oceans, but weak. The ensemble mean of all 10 RCMs simulations was superior in capturing the seasonal pattern of the rainfall and had better correlation with observed annual (Correl = 0.6) and JJAS season rainfall (Correl = 0.5) than any single model (S-RCM). We recommend using GCMs downscaled using REMO and CCLM4 RCMs and stations based statistical bias correction to manage elevation based biases of RCMs in the Upper Blue Nile Basin, specifically in the Jemma sub-basin

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen’s slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies

Statistical bias correction of regional climate model simulations for climate change projection in the Jemma sub-basin, upper Blue Nile Basin of Ethiopia

This study evaluates bias correction methods and develops future climate scenarios using the output of a better bias correctiontechnique at the Jemma sub-basin. The performance of different bias correction techniques was evaluated using several statisticalmetrics. The bias correction methods performance under climate condition different from the current climate was also evaluatedusing the differential split sample testing (DSST) and reveals that the distribution mapping technique is valid under climatecondition different from the current climate. All bias correction methods were effective in adjusting mean monthly and annualRCM simulations of rainfall and temperature to the observed rainfall and temperature values. However, distribution mappingmethod was better in capturing the 90th percentile of observed rainfall and temperature and wet day probability of observedrainfall than other methods. As a result, we use the future (2021–2100) simulation of RCMs which are bias corrected usingdistribution mapping technique. The output of bias-adjusted RCMs unfolds a decline of rainfall, a persistent increase of temperature and an increase of extremes of rainfall and temperature in the future climate under emission scenarios of RepresentativeConcentration Pathways 4.5, 8.5 and 2.6 (RCP4.5, RCP8.5 and RCP2.6). Thus, climate adaptation strategies that can provideoptimal benefits under different climate scenarios should be developed to reduce the impact of future climate change

Spatiotemporal variability of soil moisture over Ethiopia and its teleconnections with remote and local drivers

Soil moisture is one of the essential climate variables with a potential impact on local climate variability. Despite the importance of soil moisture, studies on soil moisture characteristics in Ethiopia are less documented. In this study, the spatiotemporal variability of Ethiopian soil moisture (SM) has been characterized, and its local and remote influential driving factors are investigated. An empirical orthogonal function (EOF) and KMeans clustering algorithm have been employed to classify the large domain into homogeneous zones. Complex maximum covariance analysis (CMCA) is applied to evaluate the covariability between SM and selected local and remote variables such as rainfall (RF), evapotranspiration (ET), and sea surface temperature (SST). Inter-comparison among SM datasets highlight that the FLDAS dataset better depicts the country’s SM spatial and temporal distribution (i.e., a correlation coefficient r=0.95 , rmsd=0.04m3m−3 with observations). Results also indicate that regions located in northeastern Ethiopia are drier irrespective of the season (JJAS, MAM, and OND) considered. In contrast, the western part of the country consistently depicted a wetter condition in all seasons. During summer (JJAS), the soil moisture variability is characterized by a strong east–west spatial contrast. The highest and lowest soil moisture values were observed across the country’s central western and eastern parts, respectively. Furthermore, analyses indicate that interannual variability of SM is dictated substantially by RF, though the impact on some regions is weaker. It is also found that ET likely drives the SM in the eastern part of Ethiopia due to a higher atmospheric moisture demand that ultimately invokes changes in surface humidity and rainfall. A composite analysis based on the extreme five wettest and driest SM years revealed a similar spatial distribution of wet SM with positive anomalies of RF across the country and ET over the southern regions. Remote SSTs are also found to have a significant influence on SM distribution. In particular, equatorial central Pacific and western Indian oceans SST anomalies are predominant factors for spatiotemporal SM variations over the country. Major global oceanic indices: Oceanic Nino Index (ONI), Indian Ocean Dipole (IOD), Pacific warm pool (PACWARMPOOL), and Pacific Decadal Oscillations (PDO) are found to be closely associated with the SM anomalies in various parts of the country. The associationship between these remote SST anomalies and local soil moisture is via large-scale atmospheric circulations that are linked to regional factors such as precipitation and temperature anomalies.publishedVersio

Free roaming dogs and the communities’ knowledge, attitude and practices of rabies incidence/human exposures: Cases of selected settings in Ethiopia and Kenya

AbstractBackground: According to the recommendation made by World Health organization, vaccinating 70% of the dog population helps to control rabies and prevent rabies virus in human population. However, the exponential increase in the population of free roaming dogs is a serious challenge to this strategy in Eastern African countries including Ethiopia and Kenya. Understanding the dynamics of free roaming dog populations is, thus, a step to be taken prior to designing effective rabies prevention and control strategy in these countries.Objectives: The present study was designed to determine the number of free roaming dogs in selected settings in Ethiopia and Kenya, and describe the level of community knowledge, attitude and practice (KAP) on rabies incidence/human exposures. The study also described the socio-cultural value of dog keeping in the areas considered in the study.Methodology: Counting free roaming dogs were a major means of collecting data in both Ethiopia and Kenya. Dog count was made using the markup capture approach. Other than counting, questionnaire was used to obtain data for the study. Three-hundred and ninety-eight copies of questionnaires were administered to the study participants in Ethiopia, while the number of respondents to the questionnaire in Kenya was 351. In addition, a five-year retrospective data on dog/animal bite cases were collected from selected health facilities of the study sites.Results: A total of 2991 and 386 free roaming dogs were counted in Ethiopia and Kenya, respectively. A five-year retrospective data showed cases of 1524 (in Mekelle) and 429 (Assela) individuals who were bitten/infected by rabies-suspected animals. Evidence obtained from the health facilities in Mekelle and Assela showed the bitten/infected individuals took PEP within the specified period.In Kenya, a total of 3441 and 4997 animal bite cases were reported from 2010-2014 in Kisumu and Siaya, respectively. The number of animal bite cases may signify the economic burden incurred (cost of PEP and other related costs), public health impact and social value of the disease. The questionnaire data also indicated the existing dog management practices, awareness of the community about rabies and its zoonotic importance, the first line of action taken at home for individuals bitten by rabies suspected animal, awareness of the community on dog vaccination, importance of free roaming dogs and their management.Conclusion: The significant proportion of free roaming dogs and number of animal bite cases calls for an integrated action between human and veterinary professionals to control the number of free roaming dog population, initiate awareness creation programs in the community and increase the vaccination of owned dogs there by to control and prevent rabies. Ethiop. J. Health Dev. 2018;32(1):27-35

Nanoscopic Current Effects on Photovoltaics

Silicon heterojunction (SHJ) solar cells represent a promising technological approach toward higher photovoltaic efficiencies and lower fabrication cost. While the device physics of SHJ solar cells has been studied extensively in the past, the ways in which nanoscopic electronic processes such as charge-carrier generation, recombination, trapping, and percolation affect SHJ device properties macroscopically are yet to be fully understood. We report the study of atomic-scale current percolation at state-of-the-art a-Si:H/c-Si heterojunction solar cells at room temperature, revealing the profound complexity of electronic SHJ interface processes. Using conduction atomic force microscopy, it is shown that the macroscopic current–voltage characteristics of SHJ solar cells are governed by the average of local nanometer-sized percolation pathways associated with bandtail states of the doped a-Si:H selective contact leading to above bandgap local photovoltages (VOCloc) as high as 1.2 V (eVOCloc > EgapSi). This is not in violation of photovoltaic device physics but a consequence of the nature of nanometer-scale charge percolation pathways that originate from trap-assisted tunneling causing dark leakage current. We show that the broad distribution of nanoscopic local photovoltage is a direct consequence of randomly trapped charges at a-Si:H dangling bond defects, which lead to strong local potential fluctuations and induce random telegraph noise of the dark current

A Framework for Bundling Climate-Smart Agriculture (CSA) and Climate Information Services (CIS) in Ethiopia

Ethiopia is increasingly impacted by climate change and variability because of its greater reliance on climate-sensitive economic sectors such as agriculture. The impacts of climate change and variability are greater on a poor section of the rural community in particular because of their weak adaptive capacities. In recent years, there has been an increasing focus on promoting climate-smart agriculture (CSA) and climate information services (CIS) to improve climate risk management and adaptation of smallholders to climate change in Ethiopia. However, CSA and CIS are rarely provided to farmers in an integrated manner. Therefore, considering the current agricultural technology development and dissemination landscape and the growing digital climate agro-advisory services in the country, a CSA and CIS budling framework is developed for Ethiopia. Bundling of CSA and CIS is expected to empower farmers to make appropriate decisions on a seasonal and intra-seasonal basis, minimize 'technology failure' due to climate variability and enhance adoption of new or existing CSA technologies/practices, reduce yield loss due to climate variability, and farm costs, and increase household income and food security and enhances resilience. Moreover, the bundling framework creates an opportunity for a platform to integrate tools, technologies, and services provided by different institutions and actors. The framework is validated through stakeholder feedback, and it is expected to guide the scaling of bundled services to smallholders