Determinants of farm mechanization in central and southeast oromia region, Ethiopia.

The study has been conducted to assess the farm mechanization level and tried to identify the determinants. The research utilizes primary data, collected through personal interview of 397 farm households located in the four districts of central and southeast Oromia region of Ethiopia. Multi-stage, purposive and random sampling procedures were used to select the respondents using probability proportional to size from each district. Mechanization Index (MI) based on the matrix use of animate and mechanical energy inputs that incorporate cost factors was used to estimate farm mechanization level, while Tobit model was employed to analyze factors that determine the farm mechanization level. Household's sex, educational background, experience in farming, family labor availability and social capital, location of household, access to all-weather roads and distance to farm mechanization service providers centers, participation in market and off-farm activities, landholding, land fragmentation and size of livestock owned (TLU) are statistically significant in determining level of farm mechanization. Land consolidation, availing infrastructural facilities and facilitating adult education and short-term trainings are important recommendations to enhance farm mechanization level in the study area.

The role of universal health coverage and global health security nexus and interplay on SARS-CoV-2 infection and case-fatality rates in Africa : a structural equation modeling approach.

BACKGROUND: The Coronavirus Disease (COVID-19) caused by SARS-CoV-2 infections remains a significant health challenge worldwide. There is paucity of evidence on the influence of the universal health coverage (UHC) and global health security (GHS) nexus on SARS-CoV-2 infection risk and outcomes. This study aimed to investigate the effects of UHC and GHS nexus and interplay on SARS-CoV-2 infection rate and case-fatality rates (CFR) in Africa. METHODS: The study employed descriptive methods to analyze the data drawn from multiple sources as well used structural equation modeling (SEM) with maximum likelihood estimation to model and assess the relationships between independent and dependent variables by performing path analysis. RESULTS: In Africa, 100% and 18% of the effects of GHS on SARS-CoV-2 infection and RT-PCR CFR, respectively were direct. Increased SARS-CoV-2 CFR was associated with median age of the national population (ß = -0.1244, [95% CI: -0.24, -0.01], P = 0.031 ); COVID-19 infection rate (ß = -0.370, [95% CI: -0.66, -0.08], P = 0.012 ); and prevalence of obesity among adults aged 18 + years (ß = 0.128, [95% CI: 0.06,0.20], P = 0.0001) were statistically significant. SARS-CoV-2 infection rates were strongly linked to median age of the national population (ß = 0.118, [95% CI: 0.02,0.22 ], P = 0.024); population density per square kilometer, (ß = -0.003, [95% CI: -0.0058, -0.00059], P = 0.016 ) and UHC for service coverage index (ß = 0.089, [95% CI: 0.04,0.14, P = 0.001 ) in which their relationship was statistically significant. CONCLUSIONS: The study shade a light that UHC for service coverage, and median age of the national population, population density have significant effect on COVID-19 infection rate while COVID-19 infection rate, median age of the national population and prevalence of obesity among adults aged 18 + years were associated with COVID-19 case-fatality rate. Both, UHC and GHS do not emerge to protect against COVID-19-related case fatality rate.

Impact of good governance, economic growth and universal health coverage on COVID-19 infection and case fatality rates in Africa.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has disrupted lives across all countries and communities. It significantly reduced the global economic output and dealt health systems across the world a serious blow. There is growing evidence showing the progression of the COVID-19 pandemic and the impact it has on health systems, which should help to draw lessons for further consolidating and realizing universal health coverage (UHC) in all countries, complemented by more substantial government commitment and good governance, and continued full implementation of crucial policies and plans to avert COVID-19 and similar pandemic threats in the future. Therefore, the objective of the study was to assess the impact of good governance, economic growth and UHC on the COVID-19 infection rate and case fatality rate (CFR) among African countries. METHODS: We employed an analytical ecological study design to assess the association between COVID-19 CFR and infection rate as dependent variables, and governance, economic development and UHC as independent variables. We extracted data from publicly available databases (i.e., Worldometer, Worldwide Governance Indicators, Our World in Data and WHO Global Health Observatory Repository). We employed a multivariable linear regression model to examine the association between the dependent variables and the set of explanatory variables. STATA version 14 software was used for data analysis. RESULTS: All 54 African countries were covered by this study. The median observed COVID-19 CFR and infection rate were 1.65% and 233.46%, respectively. Results of multiple regression analysis for predicting COVID-19 infection rate indicated that COVID-19 government response stringency index (ß = 0.038; 95% CI 0.001, 0.076; P = 0.046), per capita gross domestic product (GDP) (ß = 0.514; 95% CI 0.158, 0.87; P = 0.006) and infectious disease components of UHC (ß = 0.025; 95% CI 0.005, 0.045; P = 0.016) were associated with COVID-19 infection rates, while noncommunicable disease components of UHC (ß = -0.064; 95% CI -0.114; -0.015; P = 0.012), prevalence of obesity among adults (ß = 0.112; 95% CI 0.044; 0.18; P = 0.002) and per capita GDP (ß = -0.918; 95% CI -1.583; -0.254; P = 0.008) were associated with COVID-19 CFR. CONCLUSIONS: The findings indicate that good governance practices, favourable economic indicators and UHC have a bearing on COVID-19 infection rate and CFR. Effective health system response through a primary healthcare approach and progressively taking measures to grow their economy and increase funding to the health sector to mitigate the risk of similar future pandemics would require African countries to move towards UHC, improve governance practices and ensure economic growth in order to reduce the impact of pandemics on populations.

Good governance, public health expenditures, urbanization and child undernutrition Nexus in Ethiopia: an ecological analysis.

BACKGROUND: Child undernutrition remains the major public health problem in low and middle-income countries including Ethiopia. The effects of good governance, urbanization and public health expenditure on childhood undernutrition are not well studied in developing countries. The objective of the study is to examine the relationship between quality of governance, public health expenditures, urbanization and child undernutrition in Ethiopia. METHODS: This is pooled data analysis with ecological design. We obtained data on childhood undernutrition from the Ethiopian Demographic and Health Surveys (EDHS) that were conducted in 2000, 2005, 2011 and 2016. Additionally, data on quality of governance for Ethiopia were extracted from the World Governance Indicators (WGI) and public health spending and urbanization were obtained from the World Development Indicators and United Nations' World Population Prospects (WPP) respectively. Univariate and multivariate analysis were done to assess the relationship between governance, public health expenditure and urbanization with childhood undernutrition. RESULT: Government effectiveness (adjusted odd ratio (AOR) = 20.7; p = 0.046), regulatory quality (AOR = 0.0077; p = 0.026) and control of corruption (AOR = 0.0019; p = 0.000) were associated with stunting. Similarly, government effectiveness (AOR = 72.2; p = 0.007), regulatory quality (AOR = 0.0015; p = 0.004) and control of corruption (AOR = 0.0005; p = 0.000) were associated with underweight. None of the governance indicators were associated with wasting. On the other hand, there is no statistically significant association observed between public health spending and urbanization with childhood undernutrition. However, other socio-demographic variables play a significant effect on reducing of child undernutrition. CONCLUSION: This study indicates that good governance in the country plays a significant role for reducing childhood undernutrition along with other socio-demographic factors. Concerned bodies should focus on improving governance and producing a quality policy and at the same time monitor its implementation and adherence.

Does Economic Growth Reduce Childhood Undernutrition in Ethiopia?

BACKGROUND: Policy discussions and debates in the last couple of decades emphasized efficiency of development policies for translating economic growth to development. One of the key aspects in this regard in the developing world is achieving improved nutrition through economic development. Nonetheless, there is a dearth of literature that empirically verifies the association between economic growth and reduction of childhood undernutrition in low- and middle-income countries. Thus, the aim of the study is to assess the interplay between economic growth and reduction of childhood undernutrition in Ethiopia. METHODS: The study used pooled data of three rounds (2000, 2005 and 2010) from the Demographic and Health Surveys (DHS) of Ethiopia. A multilevel mixed logistic regression model with robust standard errors was utilized in order to account for the hierarchical nature of the data. The dependent variables were stunting, underweight, and wasting in children in the household. The main independent variable was real per capita income (PCI) that was adjusted for purchasing power parity. This information was obtained from World Bank. RESULTS: A total of 32,610 children were included in the pooled analysis. Overall, 11,296 (46.7%) [46.0%-47.3%], 8,197(33.8%) [33.2%-34.4%] and 3,175(13.1%) [12.7%-13.5%] were stunted, underweight, and wasted, respectively. We found a strong correlation between prevalence of early childhood undernutrition outcomes and real per capita income (PCI). The proportions of stunting (r = -0.1207, p<0.0001), wasting (r = -0.0338, p<0.0001) and underweight (r = -0.1035, p<0.0001) from the total children in the household were negatively correlated with the PCI. In the final model adjustment with all the covariates, economic growth substantially reduced stunting [ß = -0.0016, SE = 0.00013, p<0.0001], underweight [ß = -0.0014, SE = 0.0002, p<0.0001] and wasting [ß = -0.0008, SE = 0.0002, p<0.0001] in Ethiopia over a decade. CONCLUSION: Economic growth reduces child undernutrition in Ethiopia. This verifies the fact that the economic growth of the country accompanied with socio-economic development and improvement of the livelihood of the poor. Direct nutrition specific and nutrition sensitive interventions could also be recommended in order to have an impact on the massive reduction of childhood undernutrition in the country.