Search

Multiple estimates exist of global monetary and multidimensional poverty, but populations at risk of social exclusion still lack a worldwide estimate. This paper fills this gap by providing the first estimates of the share and number of populations at risk of social exclusion worldwide. The paper contributes to the literature in three important respects. First, it develops a conceptual framework of social exclusion that emphasizes the relative, multidimensional, and dynamic features of exclusion. Second, it proposes a macro-counting methodology that allows measuring populations at risk of exclusion based on identity, circumstances, and socioeconomic conditions, while advancing a protocol to avoid double counting of individuals at risk of social exclusion. Third, the empirical strategy provides to the best of our knowledge, the first estimates of populations at risk of social exclusion by dimensions of exclusion on a global and regional scale. Overall, we estimate that between 2.33 and 2.43 billion people—roughly 32 per cent of the global population—are at risk of social exclusion. The South Asia and East Asia and Pacific regions contain 1.3 billion such people, with India and China alone home to 840 million of them. Meanwhile, 52 per cent of sub-Saharan Africa's population is vulnerable to exclusion, the greatest share of any region. Our findings have important policy implications. While antipoverty policies can support household consumption and smooth its volatility among the poor, they are unlikely to address social exclusion stemming from ethnic, racial, or gender discrimination. Therefore, addressing exclusion necessitates a suite of multiple interventions tailored to distinct groups and sustained over time. [ABSTRACT FROM AUTHOR]

Background: Surgical site infection (SSI) surveillance programs are recommended to be included in national infection prevention and control (IPC) programs, yet few exist in low- or middle-income countries (LMICs). Our goal was to identify components of surveillance in existing programs that could be replicated elsewhere and note opportunities for improvement to build awareness for other countries in the process of developing their own national surgical site infection surveillance (nSSIS) programs. Methods: We administered a survey built upon the U.S. Centers for Disease Control and Prevention's framework for surveillance system evaluation to systematically deconstruct logistical infrastructure of existing nSSIS programs in LMICs. Qualitative analyses of survey responses by thematic elements were used to identify successful surveillance system components and recognize opportunities for improvement. Results: Three respondents representing countries in Europe and Central Asia, sub-Saharan Africa, and South Asia designated as upper middle-income, lower middle-income, and low-income responded. Notable strengths described by respondents included use of local paper documentation, staggered data entry, and limited data entry fields. Opportunities for improvement included outpatient data capture, broader coverage of healthcare centers within a nation, improved audit processes, defining the denominator of number of surgical procedures, and presence of an easily accessible, free SSI surveillance training program for healthcare workers. Conclusions: Outpatient post-surgery surveillance, national coverage of healthcare facilities, and training on how to take local SSI surveillance data and integrate it within a broader nSSIS program at the national level remain areas of opportunities for countries looking to implement a nSSIS program. [ABSTRACT FROM AUTHOR]

This paper attempts to empirically analyze the compatibility of national trade liberalization policies with regards to promoting widespread use of renewable energy resources across 71 low, lower-middle and upper-middle income countries from South Asia, East Asia, Pacific, Central Asia, Latin America, Caribbean islands and Sub-Saharan Africa. Annual time series data from 2000 to 2017 is employed to perform panel data cointegration and regression analyses. The results from the cointegration analyses show long-run associations between trade liberalization policies and the renewable energy consumption indicators. The Instrumental Variable Two-Stage Least Squares panel data estimator is employed to control for the endogeneity in the dataset. The overall results broadly point towards the effectiveness of greater trade openness in facilitating renewable energy transition only in the low-income economies while prolonging the transition periods in the lower and upper-middle income countries. The marginal impact of a rise in the trade openness index is estimated to enhance the renewable energy share in total energy consumption within low-income countries by 0.24% as opposed to lowering this share by 0.19% within lower-middle income economies. However, trade liberalization is found to attribute to greater efficiency of renewable energy use across all the three income groups. Thus, these findings have critically important policy implications for the respective governments. • Trade liberalization exerts heterogeneous impacts on renewable energy transition. • Trade openness increases renewable energy consumption only across the LIC. • Liberal trade policies enhance renewable energy shares only within LIC and UMIC. • Efficiency of renewable energy-use is amplified via trade liberalization. • Higher trade openness accounts for greater access to clean cooking fuels in LMIC. [ABSTRACT FROM AUTHOR]

Higher education is back in the spotlight, with post-2015 sustainable development goals emphasising equality of access. In this paper, we highlight the long distance still to travel to achieve the goal of equal access to higher education for all, with a focus on poorer countries which tend to have lower levels of enrolment in higher education. Analysing Demographic and Health Survey data from 35 low- and middle-income countries in sub-Saharan Africa and South Asia, we show wide wealth inequalities in particular, with few if any of the poorest gaining access to higher education in some countries. We further identify that wealth and gender inequalities interact and tend to be wider in countries where levels of higher education are higher. This implies that expansion in access to higher education may predominantly benefit the rich, unless measures are taken to tackle inequalities. We find that that the rates of increase necessary for the attainment of the equal access goal by 2030 are particularly high. They pose a particularly difficult challenge given the access inequalities present from primary and secondary education in a wide majority of countries in our analysis. We therefore suggest that any measures aimed at attaining the goal need to tackle inequalities in access within a system-wide approach, focusing on the level of education at which inequalities initially manifest, alongside higher education. [ABSTRACT FROM AUTHOR]

This paper critically examines the literature on the grid-offgrid debate and discusses the role of and the relationship between different electricity access options through a synthesis and critical reflection. This paper finds that models using greater resolution and capturing low voltage distribution infrastructure appear to recommend decentralised electricity solutions, whereas central grid extension emerges as the preferred outcome of more aggregated analysis, concentrated population clusters and for higher demand scenarios. However, model results are seriously influenced by assumptions, data limitations, technology choice options, and model flexibility. Exclusion of cost of generation for grid systems, lack of village level information, inherent bias towards scale and type of technology, and absence of social equity considerations in the analysis remain major weaknesses of the existing models. Universal electrification requires a strong leadership and an enabling environment. An appropriate organizational set-up, a robust regulatory framework with reporting and evaluation oversight and a more inclusive approach to promote alternative options are vital ingredients. Power sector decarbonization pathways may affect electrification choices but our understanding is limited or lacking. Further work is required to develop a programmatic approach to delivery and more affordable and fairer outcome for all. • The paper presents the up-to-date review of the debate on grid and off-grid electrification. • We find a strong leadership and an enabling environment is essential for universal electrification by the year 2030. • Appropriate organizational set-up, robust regulatory framework and shift from grid-centric focus to a more inclusive approach to promote alternative options is equally important. • Important to develop a programmatic approach to delivery and more affordable and fairer outcome. [ABSTRACT FROM AUTHOR]

Crop residues (CR) have become a limited resource in mixed crop-livestock farms. As a result of the increasing demand and low availability of alternative resources, CR became an essential resource for household activities, especially for livestock keeping; a major livelihood element of smallholder farmers in the developing world. Farmers’ decisions on CR use are determined by farmers’ preferences, total crop production, availability of alternative resources and demand for CR. Interaction of these determinants can result in pressures and trade-offs of CR use. Determinants, pressures and trade-offs are shaped by the specific socio-economic and agro-ecological context of these mixed farms. The objective of this paper is to provide a comparative analysis of the determinants of CR use and to examine some options to cope with pressures and trade-offs in 12 study sites across Sub-Saharan Africa and South Asia. Drawing on socio-economic data at household and village level, we describe how cereal intensification and livestock feed demand influence use, pressures and trade-offs of CR use across study sites, specifically cereal residue. Our results show that in low cereal production and livestock feed demand sites, despite a low demand for CR and availability of alternative biomass, pressures and trade-offs of CR use are common particularly in the dry season. In sites with moderate cereal production, and low–moderate and moderate livestock feed demand, alternative biomass resources are scarce and most residues are fed to livestock or used to cover household needs. Subsequently, pressures and potential trade-offs are stronger. In sites with low cereal production and high livestock feed demand, pressures and trade-offs depend on the availability of better feed resources. Finally, sites with high cereal production and high livestock feed demand have been able to fulfil most of the demand for CR, limiting pressures and trade-offs. These patterns show that agricultural intensification, better management of communal resources and off-farm activities are plausible development pathways to overcome pressures and trade-offs of CR use. Although technologies can largely improve these trends, research and development should revisit past initiatives so as to develop innovative approaches to tackle the well-known problem of low agricultural production in many smallholder mixed systems, creating more sustainable futures. [ABSTRACT FROM AUTHOR]

• Deep learning-based pneumonia detection in x-ray images is done in this work. • Different models of deep learning and transfer learning are analysed in this work for the image classification application. • An extensive analysis is carried out in this work with several experimental results. A large number of children die due to pneumonia every year worldwide. An estimated 1.2 million episodes of pneumonia were reported in children up to 5 years of age, of which 880,000 died in 2016. Hence, pneumonia is a major cause of death amongst children, with high prevalence rate in South Asia and Sub-Saharan Africa. Even in a developed country like the United States, pneumonia is among the top 10 causes of deaths. Early detection and treatment of pneumonia can reduce mortality rates among children significantly in countries having a high prevalence. Hence, this paper presents Convolutional Neural Network models to detect pneumonia using x-ray images. Several Convolutional Neural Networks were trained to classify x-ray images into two classes viz., pneumonia and non-pneumonia, by changing various parameters, hyperparameters and number of convolutional layers. Six models have been mentioned in the paper. First and second models consist of two and three convolutional layers, respectively. The other four models are pre-trained models, which are VGG16, VGG19, ResNet50, and Inception-v3. The first and second models achieve a validation accuracy of 85.26% and 92.31% respectively. The accuracy of VGG16, VGG19, ResNet50 and Inception-v3 are 87.28%, 88.46%, 77.56% and 70.99% respectively. [ABSTRACT FROM AUTHOR]

Background: This article describes a bibliometric review of the scientific production, geographical distribution, collaboration, impact, and subject area focus of pneumonia research indexed on the Web of Science over a 15-year period.Methods: We searched the Web of Science database using the Medical Subject Heading (MeSH) of "Pneumonia" from January 1, 2001 to December 31, 2015. The only document types we studied were original articles and reviews, analyzing descriptive indicators by five-year periods and the scientific production by country, adjusting for population, economic, and research-related parameters.Results: A total of 22,694 references were retrieved. The number of publications increased steadily over time, from 981 publications in 2001 to 1977 in 2015 (R2 = 0.956). The most productive country was the USA (38.49%), followed by the UK (7.18%) and Japan (5.46%). Research production from China increased by more than 1000%. By geographical area, North America (42.08%) and Europe (40.79%) were most dominant. Scientific production in low- and middle-income countries more than tripled, although their overall contribution to the field remained limited (< 15%). Overall, 18.8% of papers were the result of an international collaboration, although this proportion was much higher in sub-Saharan Africa (46.08%) and South Asia (23.43%). According to the specific MeSH terms used, articles focused mainly on "Pneumonia, Bacterial" (19.99%), followed by "Pneumonia, Pneumococcal" (7.02%) and "Pneumonia, Ventilator-Associated" (6.79%).Conclusions: Pneumonia research increased steadily over the 15-year study period, with Europe and North America leading scientific production. About a fifth of all papers reflected international collaborations, and these were most evident in papers from sub-Saharan Africa and South Asia. [ABSTRACT FROM AUTHOR]

Visas are an important means for countries to regulate the potential access of non-nationals to their territory. Past datasets and quantitative research on visas have focused on visa waivers, ignoring the fact that visas, where demanded, can vary greatly by cost. This paper presents a novel dataset based on a manual collection of visa costs for travel between a global set of country pairs in seven different categories (tourist, work, student, family reunification, business, transit, and other). Our analyses reveal a strong global visa cost divide that exposes the injustice in the right to travel for people located in different areas of the world. Whereas Europeans usually hardly have to work at all for travel permits, visa costs often amount to several weeks of mean income in Sub-Saharan Africa and South Asia. The result is a fundamentally paradoxical situation: The richer a country, the less its citizens pay for visas to go abroad (both in absolute terms and relative to their income). Poisson pseudo-maximum likelihood regression analyses reveal that a variety of factors influence the costs of visas between countries: reciprocal treatment, processing costs, historical-cultural ties, geographic proximity and regional, religious, economic, and political discrimination. This confirms the important role of visa costs as a tool for states to control population movements and simultaneously position themselves in international relations. [ABSTRACT FROM AUTHOR]