Agricultural Research System of Ethiopia: Past History and Future Vision

Agricultural Research in Ethiopia began in Jimma and Ambo in 1952 and was extended to the then College of Agriculture at Alemaya in 1957 and later in 1965 included Debre Zeit. Realizing the importance of agricultural research in economic development the Ethiopian government established the Institute of Agricultural Research (IAR) in 1966 as a semiautonomous organization under the general supervision of the Ministerial Board of Directors. The specific mandates of the Institution of Agricultural Research was to: Formulate national agricultural research policies, Coordinate national agricultural research Undertake research in its centers and sub-centers located in various agro-ecological zones of the country

Rural Poverty, Food Insecurity and Environmental Degradation in Ethiopia: A Case Study from South Central Ethiopia

This paper addresses the challenge of reducing poverty, food insecurity, and natural resource degradation, and abolishing recurrent famines in Ethiopia. With a population of about 65 million, Ethiopia is one of the largest and most populated countries in Africa. Ethiopia can be regarded as a microcosm of Africa due to its vast and diverse agro-ecology and population. Physically, it ranges from 200 meters to over 4000 meters above sea level. It has about 18 agro-ecological, zones and diverse population of some 85 ethnic or linguistic groups. The paper begins by addressing the conceptual relationship among food insecurity, poverty and natural resource degradation based on an extensive review of pertinent literature. The basic challenges of food insecurity-poverty- natural resource degradation discussed include: The challenge of developing and managing human resource and population growth, the challenge of developing and reforming institutions of governance, and the challenge of adopting poverty-focused economic growth policies. The relevance of agricultural and employment based development strategy is emphasized, given the fact that 85 percent of the population is currently engaged in agriculture and related activities. But, for such a strategy to succeed there is a need to adopt productive and sustainable technologies and institutions. One of the key points made is that farmers must find technologies to be profitable in order to adopt them successfully, and that such technologies can also improve sustainability. The paper further emphasizes the need to develop institutions that are incentive compatible, such as land tenure, agricultural research, and credit markets to enable and to complement the successful adoption of appropriate technologies by farmers. The paper finally draws some broad policy implications by pointing out the critical need to adopt institutions and policies that have a positive-sum or win-win outcome. These policies include investment in agricultural research and technology; the development of institutions that provide access to modern inputs and extension services; the removal of marketing and related policy distortions; and the promotion of policies that counter externalities or spillover effects of production or those that minimize environmental costs by reducing natural resource degradation. The need to adopt a land tenure system that provides security by vesting property or legal ownership rights to farmers aimed agricultural development is one of the key policy implications of the study

Spatial distribution and determinant factors of anemia among women age 15-49 years in Burkina Faso; using mixed-effects ordinal logistic regression model

Background: Anemia is a condition in which the number of healthy red blood cells/ hemoglobin (Hgb) level (and consequently their oxygen-carrying capacity) is insufficient to meet the body’s physiologic needs. Assessing the geographic distributions of anemia and determinant factors across the regions in Burkina Faso can inform the national policy in designing prevention and intervention programmes to address anemia. Thus, the current study is aimed to assess the spatial distribution and determinant factors of anemia among women aged 15–49.in Burkina Faso Methods: A secondary data analysis was done based on 2021 Burkina Faso; Demographic and Health Surveys (EDHS). Total weighted samples of 5655 women’s were included. Data processing and analysis were performed using STATA 14; ArcGIS 10.1 and SaTScan 9.6 software. Spatial autocorrelation was checked using Global Moran’s index (Moran’s I). Hotspot analysis was made using Gettis-OrdGi*statistics. Additionally, spatial scan statistics were applied to identify significant primary and secondary cluster of anemia. Mixed effect ordinal logistics were fitted to determine factors associated with the level of anemia. Result: The spatial distribution of anemia in Burkina Faso among women aged 15–49.was found to be clustered (Global Moran’s I = 0.25, p value < 0.0001). In the multivariable mixed-effect ordinal regression analysis; Age 25-29 years [AOR = 1.31 ; 95% CI: 1.06  1.61], rich wealth status [AOR = 1.32 ; 95% CI: 1.08   1.62],   regions Cascades [AOR = 1.62 ; 95% CI: 1.16   2.25],   Hauts-bassins [AOR =  1.40   ; 95% CI: 1.06   1.84],  Plateau central [AOR =  0.72    ; 95% CI: -0.54   0.96 and Sahel[AOR =  0.42   ; 95% CI: 0.28  0.63] , were significant predictors of anemia among women aged 15–49 Conclusions: A significant clustering of anemia among women aged 15–49 were found in Burkina Faso and the significant hotspot areas with high cluster anemia were identified in Boucle du mouhoun , Centre , Hauts-bassins ,Nord, Centre Ouest, Plateau central, and Centre Est regions. Besides, Age, wealth index, regions Cascades , Hauts-bassins, Plateau central, and Sahel were significant predictors of anemia. Therefore, effective public health intervention and nutritional education should be designed for the identified hotspot areas and risk groups in order to decrease the incidence of anemia

Incidence of mortality and its predictors among septic shock patients admitted to the intensive care unit of comprehensive specialized hospitals in the northwest of Amhara, Ethiopia

IntroductionSeptic shock is a global health issue causing high mortality rates in intensive care units, with limited evidence in Africa, including Ethiopia, regarding its incidence and predictors. The aim of this study was assess the incidence and predictors of mortality among patients with septic shock admitted to the ICU of Comprehensive Specialized Hospitals of the Northwest Amhara region.MethodsA study involving 386 ICU patients with septic shock from 2019 to 2023 was conducted using a random sampling method and structured data extraction tool. Data was analyzed using EpiData and STATA, with variables selected for multivariate analysis.ResultThe overall incidence rate of septic shock was 10.4 per 100-person day of observation with a median survival time of 7, days and the proportion of deaths during the study period was 58.29%. In multivariate Cox proportional regression analysis, age 40–59 years (HR: 1.77, p = 0.005), age > 60 years (HR: 3.52, p < 0.001), delay ICU admission (HR: 1.93, p = 0.001), low MAP (HR: 2.56, p < 0.001), comorbidity (HR: 2.74, p < 0.001), complication (HR: 1.87, p = 0.012), ALF (HR: 1.84, p = 0.037), no pathogen identification (HR: 1.69, p = 0.035) were found significant predictors of mortality for patients with septic shock in the ICU.ConclusionThe incidence of mortality in patients with septic shock admitted to the ICU was high and the main predictors were age> 60 years, low MAP, comorbidity, and delay ICU admission >6 h, Hence, Early recognition and appropriate treatment recommended by the International Sepsis Survival Campaign guideline should be implemented

Genetic and non-genetic parameter estimates for growth traits and Kleiber ratios in Dorper × indigenous sheep

Genetic improvement programme will only be successful when accompanied by a good understanding of the influence of different environmental factors, knowledge of the genetic parameters and the genetic relationships between the traits of interest. This study aimed to evaluate the influence of non-genetic fac- tors on growth traits and Kleiber ratios and to estimate genetic parameters for early growth traits in Dorper indigenous crossbred sheep. The effects of fixed factors were analysed by the general linear model procedure of statistical analysis system, while the genetic parameters were estimated using a WOMBAT computer program fitted animal model. The overall least-square mean for birth weight (BRW), weaning weight (3MW), six-month weight, nine-month weight, and yearling weight were 3.03 ± 0.02, 14.5 ± 0.18, 20.4 ± 0.26, 24.8 ± 0.31, and 28.3 ± 0.40 kg, respectively. The overall least- square mean for Kleiber ratio from birth to weaning (KR1), weaning to six months, six to nine months and nine months to yearling age were 16.8 ± 0.10, 6.41 ± 0.17, 4.55 ± 0.21 and 3.38 ± 0.20 g/kg of meta- bolic weight, respectively. The inclusion of maternal genetic effect had a significant influence on BRW, and it explains 20% of the phenotypic variation. The total heritability estimates for BRW, 3MW, birth to weaning average daily weight gain and KR1 were 0.10, 0.14, 0.16 and 0.12, respectively. The pheno- typic correlation varied from 0.11 ± 0.05 to 0.98 ± 0.02, whereas the direct genetic correlation ranged from 0.32 ± 0.40 to 0.98 ± 0.17. The mean inbreeding coefficient was 0.105% with an annual rate of 0.02%. The heritability estimates for growth traits and Kleiber ratio suggest that slow genetic progress would be expected from the selection. However, the integration of selection with crossbreeding pro- gramme can enhance genetic gain. Therefore, selection should be conducted based on breeding values estimated from multiple information sources to increase the selection response

Global, regional, and national burden of tuberculosis, 1990–2016: results from the Global Burden of Diseases, Injuries, and Risk Factors 2016 Study

Background Although a preventable and treatable disease, tuberculosis causes more than a million deaths each year. As countries work towards achieving the Sustainable Development Goal (SDG) target to end the tuberculosis epidemic by 2030, robust assessments of the levels and trends of the burden of tuberculosis are crucial to inform policy and programme decision making. We assessed the levels and trends in the fatal and non-fatal burden of tuberculosis by drug resistance and HIV status for 195 countries and territories from 1990 to 2016. Methods We analysed 15 943 site-years of vital registration data, 1710 site-years of verbal autopsy data, 764 site-years of sample-based vital registration data, and 361 site-years of mortality surveillance data to estimate mortality due to tuberculosis using the Cause of Death Ensemble model. We analysed all available data sources, including annual case notifications, prevalence surveys, population-based tuberculin surveys, and estimated tuberculosis cause-specific mortality to generate internally consistent estimates of incidence, prevalence, and mortality using DisMod-MR 2.1, a Bayesian meta-regression tool. We assessed how the burden of tuberculosis differed from the burden predicted by the Socio-demographic Index (SDI), a composite indicator of income per capita, average years of schooling, and total fertility rate. Findings Globally in 2016, among HIV-negative individuals, the number of incident cases of tuberculosis was 9·02 million (95% uncertainty interval [UI] 8·05–10·16) and the number of tuberculosis deaths was 1·21 million (1·16–1·27). Among HIV-positive individuals, the number of incident cases was 1·40 million (1·01–1·89) and the number of tuberculosis deaths was 0·24 million (0·16–0·31). Globally, among HIV-negative individuals the age-standardised incidence of tuberculosis decreased annually at a slower rate (–1·3% [–1·5 to −1·2]) than mortality did (–4·5% [–5·0 to −4·1]) from 2006 to 2016. Among HIV-positive individuals during the same period, the rate of change in annualised age-standardised incidence was −4·0% (–4·5 to −3·7) and mortality was −8·9% (–9·5 to −8·4). Several regions had higher rates of age-standardised incidence and mortality than expected on the basis of their SDI levels in 2016. For drug-susceptible tuberculosis, the highest observed-to-expected ratios were in southern sub-Saharan Africa (13·7 for incidence and 14·9 for mortality), and the lowest ratios were in high-income North America (0·4 for incidence) and Oceania (0·3 for mortality). For multidrug-resistant tuberculosis, eastern Europe had the highest observed-to-expected ratios (67·3 for incidence and 73·0 for mortality), and high-income North America had the lowest ratios (0·4 for incidence and 0·5 for mortality). Interpretation If current trends in tuberculosis incidence continue, few countries are likely to meet the SDG target to end the tuberculosis epidemic by 2030. Progress needs to be accelerated by improving the quality of and access to tuberculosis diagnosis and care, by developing new tools, scaling up interventions to prevent risk factors for tuberculosis, and integrating control programmes for tuberculosis and HIV

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator