29 research outputs found

    Public health implications of Bovine Cysticercosis from Cattle slaughtered at Dilla Municipal abattoir, Southern Ethiopia

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    A cross-sectional study was conducted from November 2013 to June 2014 to estimate the prevalence of Cysticercosis from abattoir survey and Taeniasis within the society found in and surrounding Dilla town. Active abattoir survey and questionnaire survey were performed to accomplish the study. Of the total of 400 inspected cattle carcasses, 17 had a varying number of C. bovis giving an overall prevalence of 4.25% (17/400). Anatomical distribution of the cyst showed that highest proportions of C. bovis cyst were observed in shoulder muscle and tongue (29.41%), followed by, masseter muscle (23.53%), heart (11.76%) and liver (5.88%). Of the total 69 interviewed respondents, 57.79% (40/69) had contracted T. saginata infection. The majority of the respondent had an experience of raw meat consumption (65.2%; 45/69) as a result of traditional and cultural practice. Of those raw meat consumers, 62.2% (28/45) were experienced taeniasis. However, no significant association was observed between raw meat consumption and teanisis (P< 0,05). The findings of this study including the prevalence of C. bovis and questionnaire survey of taeniasis prevalence indicated the importance of Cysticercosis and Taeniasis in public health aspects. Therefore, due attention should be given to the public awareness and strict routine meat inspection in order to safe guard the public health

    Study on clinically manifested reproductive health problems of dairy cows managed under intensive and semi-intensive production systems in Wondo Genet district, Southern Ethiopia

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    Reproductive disorders in cows are crucial as reproduction and fertility are the two key pillars of dairy production profitability. The study was conducted to identify and estimate the prevalence of clinically manifested postpartum reproductive disorders, to identify the associated risk factors and to estimate the sero-prevalence of brucellosis in dairy cows kept under intensive and semi-intensive dairy farms in Wondo Genet district from November 2019 to September 2020. Out of the total 205 cows examined, 90 cows (43.90%) had at least one of the reproductive problems identified by either questionnaire interview or regular follow up of individual cows. Out of 146 cows retrospectively and 59 cows prospectively assessed for the presence of any reproductive disorder, 62 (42.47%) and 28 (47.46%) cows had at least one reproductive disorders, respectively. Retained fetal membrane, abortion, uterine infections, anestrous and repeat breeding are the major reproductive disorders encountered followed by dystocia, milk fever and prolapses of the vagina and/or uterus. Among the considered host and management related risk factors, only presence of previous reproductive disorder had statistically significant association with the occurrence of reproductive disorder (p<0.05). This study also demonstrated that none of the serum samples collected from Wondo Genet and other towns (namely Hawassa, Wolaita Sodo and Arsi Negelle) and tested using Indirect Multi-species ELISA was positive for bovine brucellosis. Further studies, preferably laboratory based, should be conducted to identify the underlined causes of these problems in different parts of the country. Meanwhile, awareness should be created to farm owners/attendants to improve their farm management system

    Prevalence, risk factors and bacterial causes of bovine mastitis in southern Ethiopia

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    Mastitis is one of the most economically important diseases in dairy farms worldwide. It is particularly important in Ethiopia where no routine prevention and control practices are in place. This cross-sectional study was carried out between October 2017 and June 2018 to estimate the prevalence of mastitis, identify the associated risk factors and isolate bacterial causes in dairy farms located in southern Ethiopia using standard microbiological methods and questionnaire survey. A total of 686 lactating cows which were found in 122 selected dairy farms were investigated by physical examination and California mastitis test. The overall cow-level prevalence of mastitis was 54.2% (95% CI: 50.5 – 57.9%). Based on the study site, the prevalence was 55.7% in Hawassa, 54.3% in Arsi Negele, 52.6% each in Wondo Genet and Wolayta Soddo towns with no significant (p > 0.05) difference among the sites. The majority of mastitis cases were subclinical (48.1%) while the clinical mastitis was only 6.1%. Of the 122 herds tested, 109 (89.3%; 95% CI: 82.1 – 93.9%) had at least a cow positive for mastitis. The study showed that high parity number (OR = 1.6; p = 0.015), flat (OR = 4.5; p <0.001) and round (OR = 2; p <0.001) teat end shape, history of mastitis in preceding lactation (OR = 3.3; p <0.001), and slightly (OR = 3.5; p < 0.001), moderately (OR = 4.9; p < 0.001), and very dirty (OR = 9.2; p < 0.001) udder and legs were the major risk factors which are significantly associated with higher prevalence of mastitis. Based on the available media and reagents, the major bacteria isolated from subclinical mastitic milk samples were Staphylococcus spp. (57.3%), Streptococcus spp. (18.6%), E. coli (17.3%) and Bacillus spp. (7.5%) in order of their abundance. The present study revealed a high prevalence of mastitis, particularly the subclinical one, and the associated risk factors. Enhancing the awareness of dairy farmers, regular screening of cows for subclinical mastitis, proper treatment of the clinical cases, improving the hygienic condition of the cows, and culling of chronically infected cows are critically important to prevent and control bovine mastitis. Keywords: Mastitis, Prevalence, Risk factors, Southern Ethiopi

    Costs and resource needs for primary health care in Ethiopia: evidence to inform planning and budgeting for universal health coverage

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    IntroductionThe Government of Ethiopia (GoE) has made significant progress in expanding access to primary health care (PHC) over the past 15 years. However, achieving national PHC targets for universal health coverage will require a significant increase in PHC financing. The purpose of this study was to generate cost evidence and provide recommendations to improve PHC efficiency.MethodsWe used the open access Primary Health Care Costing, Analysis, and Planning (PHC-CAP) Tool to estimate actual and normative recurrent PHC costs in nine Ethiopian regions. The findings on actual costs were based on primary data collected in 2018/19 from a sample of 20 health posts, 25 health centers, and eight primary hospitals. Three different extrapolation methods were used to estimate actual costs in the nine sampled regions. Normative costs were calculated based on standard treatment protocols (STPs), the population in need of the PHC services included in the Essential Health Services Package (EHSP) as per the targets outlined in the Health Sector Transformation Plan II (HSTP II), and the associated costs. PHC resource gaps were estimated by comparing actual cost estimates to normative costs.ResultsOn average, the total cost of PHC in the sampled facilities was US11,532(range:US 11,532 (range: US 934–40,746) in health posts, US254,340(range:US 254,340 (range: US 68,860–832,647) in health centers, and US634,354(range:US 634,354 (range: US 505,208–970,720) in primary hospitals. The average actual PHC cost per capita in the nine sampled regions was US4.7,US 4.7, US 15.0, or US20.2dependingontheestimationmethodused.WhencomparedtothenormativecostofUS 20.2 depending on the estimation method used. When compared to the normative cost of US 38.5 per capita, all these estimates of actual PHC expenditures were significantly lower, indicating a shortfall in the funding required to deliver an expanded package of high-quality services to a larger population in line with GoE targets.DiscussionThe study findings underscore the need for increased mobilization of PHC resources and identify opportunities to improve the efficiency of PHC services to meet the GoE’s PHC targets. The data from this study can be a critical input for ongoing PHC financing reforms undertaken by the GoE including transitioning woreda-level planning from input-based to program-based budgeting, revising community-based health insurance (CBHI) packages, reviewing exempted services, and implementing strategic purchasing approaches such as capitation and performance-based financing

    Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017 : a systematic analysis for the Global Burden of Disease Study 2017

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    Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.Peer reviewe

    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

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    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 performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: A systematic analysis from the Global Burden of Disease Study 2016

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    Copyright © 2018 The Author(s). Published by Elsevier Ltd. Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8-98·1) in Iceland, followed by 96·6 (94·9-97·9) in Norway and 96·1 (94·5-97·3) in the Netherlands, to values as low as 18·6 (13·1-24·4) in the Central African Republic, 19·0 (14·3-23·7) in Somalia, and 23·4 (20·2-26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1-93·6) in Beijing to 48·0 (43·4-53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6-68·8) in Goa to 34·0 (30·3-38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle- SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view - and subsequent provision - of quality health care for all populations

    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.

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    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
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