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Working in health : financing and managing the public sector health workforce
'Working in Health' addresses two key questions related to health workforce policy in developing countries: • What is the impact of government wage bill policies on the size of the health wage bill and on health workforce staffing levels in the public sector? • Do current human resources management policies and practices lead to effective use of wage bill resources in the public sector? Health workers play a key role in increasing access to health services for poor people in developing countries. Global and country level estimates show that staffing levels in many developing countries—particularly in sub-Saharan Africa—are far below what is needed to deliver essential health services to the population. One factor that potentially limits scaling up the health workforce in developing countries is the government overall wage bill policy which sometimes creates restrictions. Through a review of literature, analysis of data, and country case studies in Kenya, Zambia, Rwanda, and the Dominican Republic, this book examines the process that determines the health wage bill budget in the public sector, how this is linked to overall wage bill policies, how this affects staffing levels in the health sector, and the relevant policy options. But staff numbers are not everything and more money for the health wage bill alone will not solve the health workforce problems of developing countries. 'Working in Health' looks at how effectively governments use the available wage bill resources in the health sector and policy options. Policies and practices in recruitment, deployment, promotion, transfer, sanctioning, and remuneration for health workers are reviewed to identify their influence on budget execution rates, geographic distribution, and productivity of health workers.
eBook
Interpreting Kigali, Rwanda: architectural inquiries and prospects for a developing African city
In 1935 a fledging government agency embarked on a project to photograph Americans hit hardest by the Great Depression. Over the next eight years, the photographers of the Farm Security Administration captured nearly a quarter-million images of tenant farmers and sharecroppers in the South, migrant workers in California, and laborers in northern industries and urban slums.Of the roughly one thousand FSA photographs taken in Arkansas, approximately two hundred have been selected for inclusion in this volume. Portraying workers picking cotton for five cents an hour, families evicted from homes for their connection with the Southern Tenant Farmers Union, and the effects of flood and drought that cruelly exacerbated the impact of economic disaster, these remarkable black-and-white images from Ben Shahn, Arthur Rothstein, Dorothea Lange, Walker Evans, Russell Lee, and other acclaimed photographers illustrate the extreme hardships that so many Arkansans endured throughout this era.These powerful photographs continue to resonate, providing a glimpse of life in Arkansas that will captivate readers as they connect to a shared past.
eBook
Combining satellite imagery and machine learning to predict poverty
Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolution satellite imagery. Using survey and satellite data from five African countries–Nigeria, Tanzania, Uganda, Malawi, and Rwanda–we show how a convolutional neural network can be trained to identify image features that can explain up to 75% of the variation in local-level economic outcomes. Our method, which requires only publicly available data, could transform efforts to track and target poverty in developing countries. It also demonstrates how powerful machine learning techniques can be applied in a setting with limited training data, suggesting broad potential application across many scientific domains.
Journal Article
Predicting poverty and wealth from mobile phone metadata
Accurate and timely estimates of population characteristics are a critical input to social and economic research and policy. In industrialized economies, novel sources of data are enabling new approaches to demographic profiling, but in developing countries, fewer sources of big data exist. We show that an individual's past history of mobile phone use can be used to infer his or her socioeconomic status. Furthermore, we demonstrate that the predicted attributes of millions of individuals can, in turn, accurately reconstruct the distribution of wealth of an entire nation or to infer the asset distribution of microregions composed of just a few households. In resource-constrained environments where censuses and household surveys are rare, this approach creates an option for gathering localized and timely information at a fraction of the cost of traditional methods.
Journal Article
A First Step up the Energy Ladder? Low Cost Solar Kits and Household’s Welfare in Rural Rwanda
More than 1.1 billion people in developing countries are lacking access to electricity. Based on the assumption that electricity is a prerequisite for human development, the United Nations has proclaimed the goal of providing electricity to all by 2030. In recent years, Pico-Photovoltaic kits have become a low-cost alternative to investment intensive grid electrification. Using a randomized controlled trial, we examine uptake and impacts of a simple Pico-Photovoltaic kit that barely exceeds the modern energy benchmark defined by the United Nations. We find significant positive effects on household energy expenditures and some indication for effects on health, domestic productivity, and on the environment. Since only parts of these effects are internalized, underinvestment into the technology is likely. In addition, our data show that adoption will be impeded by affordability, suggesting that policy would have to consider more direct promotion strategies such as subsidies or financing schemes to reach the UN goal.
Journal Article
Hospital Incidence and Outcomes of the Acute Respiratory Distress Syndrome Using the Kigali Modification of the Berlin Definition
Estimates of the incidence of the acute respiratory distress syndrome (ARDS) in high- and middle-income countries vary from 10.1 to 86.2 per 100,000 person-years in the general population. The epidemiology of ARDS has not been reported for a low-income country at the level of the population, hospital, or intensive care unit (ICU). The Berlin definition may not allow identification of ARDS in resource-constrained settings.
To estimate the incidence and outcomes of ARDS at a Rwandan referral hospital using the Kigali modification of the Berlin definition: without requirement for positive end-expiratory pressure, hypoxia cutoff of SpO2/FiO2 less than or equal to 315, and bilateral opacities on lung ultrasound or chest radiograph.
We screened every adult patient for hypoxia at a public referral hospital in Rwanda for 6 weeks. For every patient with hypoxia, we collected data on demographics and ARDS risk factors, performed lung ultrasonography, and evaluated chest radiography when available.
Forty-two (4.0%) of 1,046 hospital admissions met criteria for ARDS. Using various prespecified cutoffs for the SpO2/FiO2 ratio resulted in almost identical hospital incidence values. Median age for patients with ARDS was 37 years, and infection was the most common risk factor (44.1%). Only 30.9% of patients with ARDS were admitted to an ICU, and hospital mortality was 50.0%. Using traditional Berlin criteria, no patients would have met criteria for ARDS.
ARDS seems to be a common and fatal syndrome in a hospital in Rwanda, with few patients admitted to an ICU. The Berlin definition is likely to underestimate the impact of ARDS in low-income countries, where resources to meet the definition requirements are lacking. Although the Kigali modification requires validation before widespread use, we hope this study stimulates further work in refining an ARDS definition that can be consistently used in all settings.
Journal Article
Economic impact of refugees
In 2015, the United Nations High Commission for Refugees accommodated over 15 million refugees, mostly in refugee camps in developing countries. The World Food Program provided these refugees with food aid, in cash or in kind. Refugees’ impacts on host countries are controversial and little understood. This unique study analyzes the economic impacts of refugees on host-country economies within a 10-km radius of three Congolese refugee camps in Rwanda. Simulations using Monte Carlo methods reveal that cash aid to refugees creates significant positive income spillovers to host-country businesses and households. An additional adult refugee receiving cash aid increases annual real income in the local economy by $205 to $253, significantly more than the $120–$126 in aid each refugee receives. Trade between the local economy and the rest of Rwanda increases by $49 to $55. The impacts are lower for in-kind food aid, a finding relevant to development aid generally.
Journal Article
Epidemiology of pediatric surgical needs in low-income countries
According to recent estimates, at least 11% of the total global burden of disease is attributable to surgically-treatable diseases. In children, the burden is even more striking with up to 85% of children in low-income and middle-income countries (LMIC) having a surgically-treatable condition by age 15. Using population data from four countries, we estimated pediatric surgical needs amongst children residing in LMICs.
A cluster randomized cross-sectional countrywide household survey (Surgeons OverSeas Assessment of Surgical Need) was done in four countries (Rwanda, Sierra Leone, Nepal and Uganda) and included demographics, a verbal head to toe examination, and questions on access to care. Global estimates regarding surgical need among children were derived from combined data, accounting for country-level clustering.
A total of 13,806 participants were surveyed and 6,361 (46.1%) were children (0-18 years of age) with median age of 8 (Interquartile range [IQR]: 4-13) years. Overall, 19% (1,181/6,361) of children had a surgical need and 62% (738/1,181) of these children had at least one unmet need. Based on these estimates, the number of children living with a surgical need in these four LMICs is estimated at 3.7 million (95% CI: 3.4, 4.0 million). The highest percentage of unmet surgical conditions included head, face, and neck conditions, followed by conditions in the extremities. Over a third of the untreated conditions were masses while the overwhelming majority of treated conditions in all countries were wounds or burns.
Surgery has been elevated as an \"indivisible, indispensable part of health care\" in LMICs and the newly formed 2015 Sustainable Development Goals are noted as unachievable without the provision of surgical care. Given the large burden of pediatric surgical conditions in LMICs, scale-up of services for children is an essential component to improve pediatric health in LMICs.
Journal Article
Evaluating Synergies and Trade-Offs among Sustainable Development Goals (SDGs): Explorative Analyses of Development Paths in South Asia and Sub-Saharan Africa
Understanding the linkages between multiple targets of Sustainable Development Goals (SDGs) may help to integrate different sectoral programmes and develop coherent cross-sectoral policy to explore synergies. Synergy is interaction among two or more actions, which will lead to an impact greater or less than the sum of individual effects. Therefore, synergy can be positive or negative (trade-off). This paper aims at developing an analytical framework to evaluate sectoral linkages and examine potential synergies and trade-offs among various SDGs’ goals and targets. Synergies and trade-offs related to energy access (SDG7), clean water and sanitation access (SDG6), food security and sustainable agriculture (SDG2) and poverty alleviation (SDG1) have been evaluated from the perspective of developing countries using examples from South Asia (Bangladesh, Nepal, and Sri Lanka) and Sub-Saharan Africa (Ghana, Ethiopia and Rwanda), and historical data for the period between 1990 and 2012. The analytical framework includes both qualitative and quantitative methods. Network analysis technique has been used for exploring the conceptual linkage among different indicators, and capturing the targets associated with SDGs. Advanced Sustainability Analysis (ASA) developed under the European framework programme has been used for quantifying the synergies and trade-offs among sustainability indicators. The analysis showed strong synergy among various SDG targets. Interestingly, the potential synergy differs from country to country and over time. Ghana and Sri Lanka had relatively higher potential synergy, whereas Rwanda and Nepal had relatively lower potential synergy among the various targets. Higher synergy values were evidenced in those cases where the policy have recognized and emphasized on linkages among cross-sectoral targets.
Journal Article