68 research outputs found

    A Roadmap for Building Data Science Capacity for Health Discovery and Innovation in Africa

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    Technological advances now make it possible to generate diverse, complex and varying sizes of data in a wide range of applications from business to engineering to medicine. In the health sciences, in particular, data are being produced at an unprecedented rate across the full spectrum of scientific inquiry spanning basic biology, clinical medicine, public health and health care systems. Leveraging these data can accelerate scientific advances, health discovery and innovations. However, data are just the raw material required to generate new knowledge, not knowledge on its own, as a pile of bricks would not be mistaken for a building. In order to solve complex scientific problems, appropriate methods, tools and technologies must be integrated with domain knowledge expertise to generate and analyze big data. This integrated interdisciplinary approach is what has become to be widely known as data science. Although the discipline of data science has been rapidly evolving over the past couple of decades in resource-rich countries, the situation is bleak in resource-limited settings such as most countries in Africa primarily due to lack of well-trained data scientists. In this paper, we highlight a roadmap for building capacity in health data science in Africa to help spur health discovery and innovation, and propose a sustainable potential solution consisting of three key activities: a graduate-level training, faculty development, and stakeholder engagement. We also outline potential challenges and mitigating strategies

    Health gains and fi nancial risk protection aff orded by public fi nancing of selected interventions in Ethiopia: an extended cost-eff ectiveness analysis

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    Background The way in which a government chooses to fi nance a health intervention can aff ect the uptake of health interventions and consequently the extent of health gains. In addition to health gains, some policies such as public fi nance can insure against catastrophic health expenditures. We aimed to evaluate the health and fi nancial risk protection benefi ts of selected interventions that could be publicly fi nanced by the government of Ethiopia. Methods We used extended cost-eff ectiveness analysis to assess the health gains (deaths averted) and fi nancial risk protection aff orded (cases of poverty averted) by a bundle of nine (among many other) interventions that the Government of Ethiopia aims to make universally available. These nine interventions were measles vaccination, rotavirus vaccination, pneumococcal conjugate vaccination, diarrhoea treatment, malaria treatment, pneumonia treatment, caesarean section surgery, hypertension treatment, and tuberculosis treatment. Findings Our analysis shows that, per dollar spent by the Ethiopian Government, the interventions that avert the most deaths are measles vaccination (367 deaths averted per 100000spent),pneumococcalconjugatevaccination(170deathsavertedper100 000 spent), pneumococcal conjugate vaccination (170 deaths averted per 100 000 spent), and caesarean section surgery (141 deaths averted per 100000spent).Theinterventionsthatavertthemostcasesofpovertyarecaesareansectionsurgery(98casesavertedper100 000 spent). The interventions that avert the most cases of poverty are caesarean section surgery (98 cases averted per 100 000 spent), tuberculosis treatment (96 cases averted per 100000spent),andhypertensiontreatment(84casesavertedper100 000 spent), and hypertension treatment (84 cases averted per 100 000 spent). Interpretation Our approach incorporates fi nancial risk protection into the economic evaluation of health interventions and therefore provides information about the effi ciency of attainment of both major objectives of a health system: improved health and fi nancial risk protection. One intervention might rank higher on one or both metrics than another, which shows how intervention choice—the selection of a pathway to universal health coverage—might involve weighing up of sometimes competing objectives. This understanding can help policy makers to select interventions to target specifi c policy goals (ie, improved health or fi nancial risk protection). It is especially relevant for the design and sequencing of universal health coverage to meet the needs of poor populations

    Epidemiology of Mycobacterium tuberculosis lineages and strain clustering within urban and peri-urban settings in Ethiopia

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    Background Previous work has shown differential predominance of certain Mycobacterium tuberculosis (M. tb) lineages and sub-lineages among different human populations in diverse geographic regions of Ethiopia. Nevertheless, how strain diversity is evolving under the ongoing rapid socio-economic and environmental changes is poorly understood. The present study investigated factors associated with M. tb lineage predominance and rate of strain clustering within urban and peri-urban settings in Ethiopia. Methods Pulmonary Tuberculosis (PTB) and Cervical tuberculous lymphadenitis (TBLN) patients who visited selected health facilities were recruited in the years of 2016 and 2017. A total of 258 M. tb isolates identified from 163 sputa and 95 fine-needle aspirates (FNA) were characterized by spoligotyping and compared with international M.tb spoligotyping patterns registered at the SITVIT2 databases. The molecular data were linked with clinical and demographic data of the patients for further statistical analysis. Results From a total of 258 M. tb isolates, 84 distinct spoligotype patterns that included 58 known Shared International Type (SIT) patterns and 26 new or orphan patterns were identified. The majority of strains belonged to two major M. tb lineages, L3 (35.7%) and L4 (61.6%). The observed high percentage of isolates with shared patterns (n = 200/258) suggested a substantial rate of overall clustering (77.5%). After adjusting for the effect of geographical variations, clustering rate was significantly lower among individuals co-infected with HIV and other concomitant chronic disease. Compared to L4, the adjusted odds ratio and 95% confidence interval (AOR; 95% CI) indicated that infections with L3 M. tb strains were more likely to be associated with TBLN [3.47 (1.45, 8.29)] and TB-HIV co-infection [2.84 (1.61, 5.55)]. Conclusion Despite the observed difference in strain diversity and geographical distribution of M. tb lineages, compared to earlier studies in Ethiopia, the overall rate of strain clustering suggests higher transmission and warrant more detailed investigations into the molecular epidemiology of TB and related factors

    National disability-adjusted life years(DALYs) for 257 diseases and injuries in Ethiopia, 1990–2015: findings from the global burden of disease study 2015

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    Background: Disability-adjusted life years (DALYs) provide a summary measure of health and can be a critical input to guide health systems, investments, and priority-setting in Ethiopia. We aimed to determine the leading causes of premature mortality and disability using DALYs and describe the relative burden of disease and injuries in Ethiopia. Methods: We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for non-fatal disease burden, cause-specific mortality, and all-cause mortality to derive age-standardized DALYs by sex for Ethiopia for each year. We calculated DALYs by summing years of life lost due to premature mortality (YLLs) and years lived with disability (YLDs) for each age group and sex. Causes of death by age, sex, and year were measured mainly using Causes of Death Ensemble modeling. To estimate YLDs, a Bayesian meta-regression method was used. We reported DALY rates per 100,000 for communicable, maternal, neonatal, and nutritional (CMNN) disorders, non-communicable diseases, and injuries, with 95% uncertainty intervals (UI) for Ethiopia. Results: Non-communicable diseases caused 23,118.1 (95% UI, 17,124.4–30,579.6), CMNN disorders resulted in 20,200.7 (95% UI, 16,532.2–24,917.9), and injuries caused 3781 (95% UI, 2642.9–5500.6) age-standardized DALYs per 100,000 in Ethiopia in 2015. Lower respiratory infections, diarrheal diseases, and tuberculosis were the top three leading causes of DALYs in 2015, accounting for 2998 (95% UI, 2173.7–4029), 2592.5 (95% UI, 1850.7–3495.1), and 2562.9 (95% UI, 1466.1–4220.7) DALYs per 100,000, respectively. Ischemic heart disease and cerebrovascular disease were the fourth and fifth leading causes of age-standardized DALYs, with rates of 2535.7 (95% UI, 1603.7–3843.2) and 2159.9 (95% UI, 1369.7–3216.3) per 100,000, respectively. The following causes showed a reduction of 60% or more over the last 25 years: lower respiratory infections, diarrheal diseases, tuberculosis, neonatal encephalopathy, preterm birth complications, meningitis, malaria, protein-energy malnutrition, iron-deficiency anemia, measles, war and legal intervention, and maternal hemorrhage

    National mortality burden due to communicable, non-communicable, and other diseases in Ethiopia, 1990–2015: findings from the Global Burden of Disease Study 2015

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    Background: Ethiopia lacks a complete vital registration system that would assist in measuring disease burden and risk factors. We used the Global Burden of Diseases, Injuries, and Risk factors 2015 (GBD 2015) estimates to describe the mortality burden from communicable, non-communicable, and other diseases in Ethiopia over the last 25 years. Methods: GBD 2015 mainly used cause of death ensemble modeling to measure causes of death by age, sex, and year for 195 countries. We report numbers of deaths and rates of years of life lost (YLL) for communicable, maternal, neonatal, and nutritional (CMNN) disorders, non-communicable diseases (NCDs), and injuries with 95% uncertainty intervals (UI) for Ethiopia from 1990 to 2015. Results: CMNN causes of death have declined by 65% in the last two-and-a-half decades. Injury-related causes of death have also decreased by 70%. Deaths due to NCDs declined by 37% during the same period. Ethiopia showed a faster decline in the burden of four out of the five leading causes of age-standardized premature mortality rates when compared to the overall sub-Saharan African region and the Eastern sub-Saharan African region: lower respiratory infections, tuberculosis, HIV/AIDS, and diarrheal diseases; however, the same could not be said for ischemic heart disease and other NCDs. Non-communicable diseases, together, were the leading causes of age-standardized mortality rates, whereas CMNN diseases were leading causes of premature mortality in 2015. Although lower respiratory infections, tuberculosis, and diarrheal disease were the leading causes of age-standardized death rates, they showed major declines from 1990 to 2015. Neonatal encephalopathy, iron-deficiency anemia, protein-energy malnutrition, and preterm birth complications also showed more than a 50% reduction in burden. HIV/AIDS-related deaths have also decreased by 70% since 2005. Ischemic heart disease, hemorrhagic stroke, and ischemic stroke were among the top causes of premature mortality and age-standardized death rates in Ethiopia in 2015. Conclusions: Ethiopia has been successful in reducing deaths related to communicable, maternal, neonatal, and nutritional deficiency diseases and injuries by 65%, despite unacceptably high maternal and neonatal mortality rates. However, the country’s performance regarding non-communicable diseases, including cardiovascular disease, diabetes, cancer, and chronic respiratory disease, was minimal, causing these diseases to join the leading causes of premature mortality and death rates in 2015. While the country is progressing toward universal health coverage, prevention and control strategies in Ethiopia should consider the double burden of common infectious diseases and non-communicable diseases: lower respiratory infections, diarrhea, tuberculosis, HIV/AIDS, cardiovascular disease, cancer, and diabetes. Prevention and control strategies should also pay special attention to the leading causes of premature mortality and death rates caused by non-communicable diseases: cardiovascular disease, cancer, and diabetes. Measuring further progress requires a data revolution in generating, managing, analyzing, and using data for decision-making and the creation of a full vital registration system in the country

    Network analysis of dairy cattle movement and associations with bovine tuberculosis spread and control in emerging dairy belts of Ethiopia

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    Background: Dairy cattle movement could be a major risk factor for the spread of bovine tuberculosis (BTB) in emerging dairy belts of Ethiopia. Dairy cattle may be moved between farms over long distances, and hence understanding the route and frequency of the movements is essential to establish the pattern of spread of BTB between farms, which could ultimately help to inform policy makers to design cost effective control strategies. The objective of this study was, therefore, to investigate the network structure of dairy cattle movement and its influence on the transmission and prevalence of BTB in three emerging areas among the Ethiopian dairy belts, namely the cities of Hawassa, Gondar and Mekelle. Methods: A questionnaire survey was conducted in 278 farms to collect data on the pattern of dairy cattle movement for the last 5 years (September 2013 to August 2018). Visualization of the network structure and analysis of the relationship between the network patterns and the prevalence of BTB in these regions were made using social network analysis. Results: The cattle movement network structure display both scale free and small world properties implying local clustering with fewer farms being highly connected, at higher risk of infection, with the potential to act as super spreaders of BTB if infected. Farms having a history of cattle movements onto the herds were more likely to be affected by BTB (OR: 2.2) compared to farms not having a link history. Euclidean distance between farms and the batch size of animals moved on were positively correlated with prevalence of BTB. On the other hand, farms having one or more outgoing cattle showed a decrease on the likelihood of BTB infection (OR = 0.57) compared to farms which maintained their cattle. Conclusion: This study showed that the patterns of cattle movement and size of animal moved between farms contributed to the potential for BTB transmission. The few farms with the bulk of transmission potential could be efficiently targeted by control measures aimed at reducing the spread of BTB. The network structure described can also provide the starting point to build and estimate dynamic transmission models for BTB, and other infectious disease

    Prevalence of bovine tuberculosis and its associated risk factors in the emerging dairy belts of regional cities in Ethiopia

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    Bovine tuberculosis (BTB) has become an economically important disease in dairy herds found in and around Addis Ababa City and is emerging in regional cities like Gondar, Hawassa and Mekelle because of the establishment of dairy farms in the milk sheds of these cities. A cross-sectional study to estimate the prevalence of BTB and identify associated risk factors was conducted between February 2016 and March 2017. A total of 174 herds comprising of 2,754 dairy cattle in the cities of Gondar, Hawassa and Mekelle were tested using the Single Intradermal Comparative Cervical Tuberculin (SICCT) test. Data on herd structure, animal origin, body condition, housing condition, farm hygiene, management and biosecurity practices were collected using a pre-tested structured questionnaire. Generalized Linear Models (GLM) and Generalized Linear Mixed Models (GLMM) were used to analyze the herd and animal level risk factors, respectively. The herd prevalence was 22.4% (95% CI: 17–29%) while the animal prevalence was 5.2% (95% CI: 4–6%) at the cut-off >4 mm. The herd prevalence rose to 65.5% (95% CI: 58–72%) and the animal prevalence rose to 9% (95% CI: 8–10%) when the severe interpretation of >2 mm cut-off was applied. The mean within-herd prevalence in positive farms at the cut-off >4 mm was 22.7% (95% CI: 15–31%). At the herd level, the analysis showed that herd size, farm hygiene, feeding condition and biosecurity were significantly associated with BTB status, while new cattle introductions showed only borderline significance and that age of farm, housing condition, farmers’ educational status and animal health care practice were not significant. At the animal level, the results showed that age and animal origin were identified as significant predictors for BTB positivity but sex and body condition score were not related to BTB status. Descriptive analysis revealed that herds having ‘BTB history’ showed slightly higher likelihood of being BTB positive compared to farms having no previous BTB exposure. In conclusion, this study showed relatively lower average prevalence in the emerging dairy regions as compared to the prevalence observed in and around Addis Ababa City, warranting for implementation of control program at this stage to reduce or possibly stop further transmission of BTB

    Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

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    Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations
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