Empirical analysis of procedures that schedule unit length jobs subject to precedence constraints forming in- and out-stars

This paper addresses the problem of scheduling unit length jobs subject to precedence constraints forming in- and out-stars. There are several different procedures that can be used to solve this problem and our aim in this paper is to compare these procedures empirically. We found that one algorithm that was thought to solve the problem optimally didn't do so for the general set of instances and that all procedures that we tested did not perform well if the number of stars in the instance was close but below the number of machines in the instance

Setting up child health and mortality prevention surveillance in Ethiopia

Background: Mortality rates for children under five years of age, and stillbirth risks, remain high in parts of sub-Saharan Africa and South Asia. The Child Health and Mortality Prevention Surveillance (CHAMPS) network aims to ascertain causes of child death in high child mortality settings (>50 deaths/1000 live-births). We aimed to develop a “greenfield” site for CHAMPS, based in Harar and Kersa, in Eastern Ethiopia. This very high mortality setting (>100 deaths/1000 live-births in Kersa) had limited previous surveillance capacity, weak infrastructure and political instability. Here we describe site development, from conception in 2015 to the end of the first year of recruitment. Methods: We formed a collaboration between Haramaya University and the London School of Hygiene & Tropical Medicine and engaged community, national and international partners to support a new CHAMPS programme. We developed laboratory infrastructure and recruited and trained staff. We established project specific procedures to implement CHAMPS network protocols including; death notifications, clinical and demographic data collection, post-mortem minimally invasive tissue sampling, microbiology and pathology testing, and verbal autopsy. We convened an expert local panel to determine cause-of-death. In partnership with the Ethiopian Public Health Institute we developed strategies to improve child and maternal health. Results: Despite considerable challenge, with financial support, personal commitment and effective partnership, we successfully initiated CHAMPS. One year into recruitment (February 2020), we had received 1173 unique death notifications, investigated 59/99 MITS-eligible cases within the demographic surveillance site, and assigned an underlying and immediate cause of death to 53 children. Conclusions: The most valuable data for global health policy are from high mortality settings, but initiating CHAMPS has required considerable resource. To further leverage this investment, we need strong local research capacity and to broaden the scientific remit. To support this, we have set up a new collaboration, the “Hararghe Health Research Partnership”

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Exclusive breastfeeding (EBF)—giving infants only breast-milk for the first 6 months of life—is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization’s Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030

Impact of contract farming on smallholders in Ethiopia: the case of chickpea growers

Contract farming (CF) is an institutional arrangement by which agribusinesses replace or supplement primary agricultural production with supply from smallholders. In developing countries where farms are typically small and resource poor, questions have been asked about its impact on smallholders, particularly the poorest. This study examined these aspects of a Contract Farming Arrangement (CFA) between a chickpea processing firm and a farmers’ cooperative union in central Ethiopia. A random sample of 95 growers was drawn from a list of CF participants. In addition, a representative sample of 114 households was drawn from seven counties where the CFA was active. A subset of non-participating households with characteristics similar to those of participants was identified as a control group using propensity scores predicted by a logit model. The logit model indicated that the CFA was biased against farmers who were relatively poor, risk averse and short of farming skills and experience. However, there was no evidence that participation was influenced by gender, education, farm size or household labour endowments. Univariate comparisons revealed significant differences in key outcomes between participants and households in the control group. A multivariate ‘treatment’ model estimated to isolate the impact of the CFA found that participation had a substantial positive impact on household cash revenue (ETB 3,658 per adult equivalent) and net cash income (ETB 3,411 per adult equivalent) earned from crop production. Local Average Treatment Effects (LATEs) computed for ‘complier’ households were also sizeable for these outcomes at ETB 2,879 and ETB 1,896 per adult equivalent respectively. Participants attributed increases in net income to improved seed, a stable product price, higher yields and a guaranteed market. Descriptive analysis of other perceived outcomes suggested that participants also benefited from improved food security and better access to preferred markets, credit, new technology, information and technical advice. Levels of satisfaction with the terms and administration of the CFA were high. Interventions that improve farming skills and mitigate risk are recommended to enhance inclusiveness. Efforts to strengthen producer organisations, cooperative unions and the legal infrastructure required to enforce contracts are also recommended

Setting up child health and mortality prevention surveillance in Ethiopia.

BACKGROUND: Mortality rates for children under five years of age, and stillbirth risks, remain high in parts of sub-Saharan Africa and South Asia. The Child Health and Mortality Prevention Surveillance (CHAMPS) network aims to ascertain causes of child death in high child mortality settings (>50 deaths/1000 live-births). We aimed to develop a “greenfield” site for CHAMPS, based in Harar and Kersa, in Eastern Ethiopia. This very high mortality setting (>100 deaths/1000 live-births in Kersa) had limited previous surveillance capacity, weak infrastructure and political instability. Here we describe site development, from conception in 2015 to the end of the first year of recruitment. METHODS: We formed a collaboration between Haramaya University and the London School of Hygiene & Tropical Medicine and engaged community, national and international partners to support a new CHAMPS programme. We developed laboratory infrastructure and recruited and trained staff. We established project specific procedures to implement CHAMPS network protocols including; death notifications, clinical and demographic data collection, post-mortem minimally invasive tissue sampling, microbiology and pathology testing, and verbal autopsy. We convened an expert local panel to determine cause-of-death. In partnership with the Ethiopian Public Health Institute we developed strategies to improve child and maternal health. RESULTS: Despite considerable challenge, with financial support, personal commitment and effective partnership, we successfully initiated CHAMPS. One year into recruitment (February 2020), we had received 1173 unique death notifications, investigated 59/99 MITS-eligible cases within the demographic surveillance site, and assigned an underlying and immediate cause of death to 53 children. CONCLUSIONS: The most valuable data for global health policy are from high mortality settings, but initiating CHAMPS has required considerable resource. To further leverage this investment, we need strong local research capacity and to broaden the scientific remit. To support this, we have set up a new collaboration, the “Hararghe Health Research Partnership”