Global Policymaking Research Articles

Sustainability strategies: A proposal for food sector SMEs, based on the integration of life cycle assessment and ESG strategies

The significant climate change the planet has faced in recent decades has prompted global leaders, policymakers, business leaders, environmentalists, academics, and scientists from around the world to unite their efforts since 1987 around sustainable development. This development not only promotes economic sustainability but also environmental, social, and corporate sustainability, where clean production, responsible consumption, and sustainable infrastructures prevail. In this context, the present article aims to propose a development framework for sustainability in food sector SMEs, which includes Life Cycle Assessment (LCA) and the integration of Environmental, Social, and Governance (ESG) strategies as key elements to reduce CO2 emissions and improve operational efficiency. The methodology includes a comparative analysis of strategies implemented between 2019 and 2023, supported by quantitative data showing a 20% reduction in operating costs, a 10% increase in market share, and a 25% increase in productivity for companies that adopted clean technologies. This study offers a significant contribution to the field of corporate sustainability, providing a model that is adaptable and applicable across different regions, enhancing innovation and business resilience in a global context that requires collective efforts to achieve the sustainable development goals.

Evaluation of sustainable hydrogen production technologies by fuzzy AHP analysis with bootstrapping

The concept of a hydrogen economy has received increasing attention worldwide. Hydrogen is a promising energy carrier that contributes to the development of a sustainable and reliable energy sector. Selection of the most sustainable hydrogen production technology (HPT) plays a significant role in promoting a hydrogen economy. However, it is regarded as a multi-criteria decision-making (MCDM) problem with several incompatible evaluation criteria. In this study, we develop an MCDM approach based on Fuzzy Analytic Hierarchy Process (FAHP) for prioritizing HPT alternatives, focusing on Egypt as a case study. Our contributions are twofold. First, to combat the issue of a small number of subject matter experts, a bootstrap method is employed to validate the main criteria weights in FAHP. Second, we conduct a comparative FAHP analysis from a broad perspective of the national experts from a developing country and the international experts from developed countries. Our results show that PV electrolysis is the most preferable technology option from the perspectives of both the national and international experts. Since the FAHP approach proposed is a flexible framework that can be applied to countries other than Egypt, it will support global policymakers and industry stakeholders in their decision making toward a sustainable and efficient hydrogen economy strategy.

Traceability for strengthening supply chain systems and enhancing real-time visibility: Focus of NAFDAC on advancing vaccine traceability in Nigeria

This study explores the successful implementation of activities aimed at scaling traceability for COVID-19 and routine immunization (RI) vaccines to the local government area and selected healthcare facilities in Nigeria, funded by the Bill and Melinda Gates Foundation. The study was executed by the National Agency for Food and Drug Administration and Control (NAFDAC) and sought to enhance supply chain systems by deploying advanced traceability mechanisms and ensuring real-time stock visibility. The article discusses the accomplishments, challenges, and regulatory framework of NAFDAC, emphasizing GS1 technology-driven traceability, and presents the results of the field scanning activities conducted in July 2023. The approach involved a phased public sector pilot, showcasing the feasibility and challenges of tracking vaccine movement through the supply chain. The result shows the detection of 43 unique products across 1022 facilities from a total of 110,113 scans, offering valuable insights into vaccine distributions. The strategic goals of the project aligned with developing safety surveillance systems in low- and middle-income countries (LMICs) to facilitate patient access to global health products. Similarly, significant improvement in traceability through automated data capture (barcode scanning) and expanded coverage for COVID-19 and selected RI vaccines in Nigeria was found. Against this background, the information derived from this report will build confidence in patients regarding vaccine authenticity, establish a transparent and robust supply chain, and foster pharmacovigilance capability through integration with the track-and-trace systems. Thus, the study provides invaluable insights and opportunities for global health practitioners, policymakers, and researchers to incorporate track-and-trace into regulatory systems by other national regulatory authorities.

Environmental, social, and governance, board gender diversity, and firm efficiency: Evidence from the global mining industry pre‐ and post‐COVID‐19 pandemic

AbstractWe examine (i) the impacts of environmental, social, and governance (ESG) on firm efficiency and (ii) how board gender diversity (BGD) moderates these impacts in mining multinational enterprises (MNCs). We first employ a two‐stage network data envelopment analysis (DEA) approach to estimate eco‐efficiency (EE) and profitability efficiency (PE), and a network‐based ranking model to rank the mining MNCs. Second, we utilize multivariate regression analysis on 294 firm‐year observations of 49 global MNCs spanning from 2016 to 2021 to achieve our research objectives. Based on our findings, it appears that mining MNCs have a bigger room for improvement when it comes to their profitability efficiency than their eco‐efficiency. The DEA average efficiency scores for EE and PE stand at around 83% and 50%, respectively. Moreover, our regression results reveal that ESG significantly and positively influences EE but insignificantly affects PE. Environmental pillar score (EPS), social pillar score (SPS), and governance pillar score insignificantly influence EE, whereas EPS and SPS significantly affect PE. In addition, BGD significantly moderates the effect of ESG on EE. BGD significantly moderates only the impact of SPS on PE. Overall, this study emphasizes the significance of focusing on BGD when examining the relationship between ESG and firm efficiency, which thus provides crucial insights for stakeholders in the global mining industry, including investors, policymakers, and researchers.

Navigating trust and health in India: the influence of social status and neighbourhood environment

BackgroundThe research on the relationship between interpersonal trust and health has primarily focused on Western contexts, with scarce attention in developing contexts. Addressing this gap, the study examines the association between interpersonal trust (both generalised and particularised) and health outcomes (self-rated health /SRH, and depression) among Indian adults, considering the moderating roles of social statuses (gender and caste) and macro-level factors like district-level income inequality.MethodsThe study draws on data from the World Health Organization's (WHO) Study on global AGEing and adult health (SAGE) Wave-1, collected between 2007 and 2010. This dataset provides a comprehensive overview of health outcomes, including self-rated health (SRH) and depression, socio-cultural status of adults aged 18 and above in India. Additionally, district-level data on income inequality, quantified through the Gini index, were incorporated to examine the influence of contextual socioeconomic influence on the trust-health relationship. Multilevel regression analysis with interaction effects with social statuses and income inequality at district was employed in the analysis to investigate the intricate relationship between interpersonal trust (both generalised and particularised) and health outcomes.ResultsThe study reveals that while generalised trust does not directly influence depression or SRH, particularised trust acts as a protective factor for both health outcomes. Gender-specific interaction effect shows that generalised trust reduces depression among males and improves SRH among females. Notably, caste does not significantly moderate the trust-health relationship. High district-level income inequality, however, modifies these associations: generalised trust is associated with improved SRH in areas of high inequality, whereas particularised trust correlates with increased depression in these districts.ConclusionThe findings highlight the complex dynamics between interpersonal trust, social status, and income inequality in shaping health outcomes in India. Generalised trust emerges as a potential buffer against the health-detrimental effects of income inequality, providing crucial insights for developing targeted health interventions. These results offer valuable guidance for global health policymakers and practitioners in effectively allocating development aid to enhance health outcomes, especially among the most marginalised groups.

Post-COVID pandemic: The new normal and aftermath

ABSTRACT Background: The COVID-19 pandemic has brought about unparalleled worldwide transformations, impacting all facets of human existence, including health systems, economies, societal norms, and individual behaviors. Aim: The goal is to comprehend the enduring alterations in public health strategies, economic recuperation processes, changes in work and education paradigms, and the psychological consequences for populations globally. Methods and Materials: This analysis uses a multidisciplinary approach by incorporating data from healthcare studies, economic reports, educational research, and psychological assessments. It aims to offer a comprehensive perspective on the world after the pandemic. Results: The findings suggest that the “New Normal” encompasses a wide range of changes, such as a greater dependence on digital technology, a transition toward remote work and learning, substantial modifications in global supply chains, and a revised outlook on health and wellness. The potential long-term consequences of these changes indicate that some may provide opportunities for innovation and expansion, whereas others present challenges that necessitate strategic planning and policy interventions. Conclusion: The aftermath of the COVID-19 pandemic presents a critical moment for global leaders, policymakers, and individuals to navigate the complexities of a transformed world, emphasizing the need for resilience, adaptability, and a renewed commitment to collective well-being.

Bibliometric analysis of Indian research trends in air quality forecasting research using machine learning from 2007–2023 using Scopus database

Machine-learning air pollution prediction studies are widespread worldwide. This study examines the use of machine learning to predict air pollution, its current state, and its expected growth in India. Scopus was used to search 326 documents by 984 academics published in 231 journals between 2007 and 2023. Biblioshiny and Vosviewer were used to discover and visualise prominent authors, journals, research papers, and trends on these issues. In 2018, interest in this topic began to grow at a rate of 32.1 percent every year. Atmospheric Environment (263 citations), Procedia Computer Science (251), Atmospheric Pollution Research (233) and Air Quality, Atmosphere, and Health (93 citations) are the top four sources, according to the Total Citation Index. These journals are among those leading studies on using machine learning to forecast air pollution. Jadavpur University (12 articles) and IIT Delhi (10 articles) are the most esteemed institutions. Singh Kp's 2013 "Atmospheric Environment" article tops the list with 134 citations. The Ministry of Electronics and Information Technology and the Department of Science and Technology are top Indian funding agency receive five units apiece, demonstrating their commitment to technology. The authors' keyword co-occurrence network mappings suggest that machine learning (127 occurrences), air pollution (78 occurrences), and air quality index (41) are the most frequent keywords. This study predicts air pollution using machine learning. These terms largely mirror our Scopus database searches for "machine learning," "air pollution," and "air quality," showing that these are among the most often discussed issues in machine learning research on air pollution prediction. This study helps academics, professionals, and global policymakers understand "air pollution prediction using machine learning" research and recommend key areas for further research.

Contested quantification for planetary health – A sociotechnical analysis of Bangladesh's water salinity monitoring infrastructure

In climate change and planetary health, the datafication of natural processes and their effects on human health is gaining importance, not least due to data's role in international funding mechanisms. In Bangladesh, water salinity has become the focus of much research and could emerge as an asset to access climate funding. Taking Bangladesh's water salinity monitoring infrastructure as a case study, this paper problematizes the “neutrality” of water salinity data. Adopting the methodological approach of an “infrastructural inversion”, we foreground the relational nature of data production. The study draws on ethnographic fieldwork in Bangladesh along the data production chain. We highlight how the involvement of a large variety of actors gave rise to vastly different data infrastructures and explicate the influence of actors' “problematization”. We further illustrate the importance of pre-existing materiality for the implementation of data collection systems on the ground and their power to influence whose reality is represented and whose is left out. Discussing these findings in the context of the international development sector reveals the complex interplay between the dual function of data as a mediator of knowledge and proof of legitimacy. Attention is paid to the tendencies of perpetuating patterns of exclusion and inclusion through data in a setting of project-based funding. We thereby provide global health researchers, policy makers and development practitioners with a detailed case study whilst stimulating reflection on the hegemony of datafication.

Acceptance and uptake of vaccines against tetanus, influenza, pertussis, and COVID-19 among pregnant and postpartum women in low- and middle-income countries: a systematic review and meta-analysis protocol

BackgroundPregnant women, fetuses, and neonates are particularly vulnerable to vaccine-preventable diseases (VPDs). These VPDs are associated with high morbidity and mortality among expectant mothers and their fetuses and neonates. Vaccination during pregnancy can protect the expectant mother from VPDs to which she may be especially vulnerable while pregnant. In addition, the passive transfer of maternal neutralizing immunoglobulin G (IgG) and secretory immunoglobulin A (IgA) also protects the fetus against congenital infections and may further protect the neonate from infection during the first few months of life. Despite this, coverage of recommended maternal vaccines remains suboptimal globally, especially in resource-constrained settings. Determinants of vaccine acceptance and uptake are frequently understudied in low- and middle-income countries (LMICs) and among specific groups such as pregnant and postpartum women. This proposed systematic review will assess the acceptance and uptake of vaccines against tetanus, influenza, pertussis, and COVID-19 among pregnant and postpartum women in LMICs.MethodsA Boolean search strategy employing common and medical subject heading (MeSH) terms for tetanus, influenza, pertussis, and COVID-19 vaccines, as well as vaccine acceptance, hesitancy, together with uptake, pregnancy, and postpartum, will be used to search electronic databases for relevant literature published between 2009 and 2024. Only studies conducted in LMICs that investigated determinants of acceptance, hesitancy, and uptake of tetanus, influenza, pertussis, and COVID-19 vaccines among pregnant and postpartum women will be eligible for inclusion in the review. The quality and the risk of bias of all eligible full-text articles will be assessed using the Joanna Briggs Institute’s (JBI) critical appraisal tools.DiscussionThis protocol proposes a systematic review and meta-analysis that aims to assess the uptake of maternal vaccines and to systematically appraise and quantify determinants of the acceptance and uptake of recommended vaccines during pregnancy and postpartum in LMICs. A better understanding of these factors and how they influence maternal vaccine decision-making will enable public health practitioners as well as global and national policymakers to design more effective interventions as we look towards expanding the scope and reach of maternal immunization programs.

디지털 콘텐츠 유통을 위한 OTT 비즈니스 모델 연구

The way cultural content is being distributed is rapidly changing in the digital age. This study focuses on the business model of Netflix, a dominant player in the global market for digital content distribution. The aim is to identify strategies and insights that can be useful for domestic OTT (Over-The-Top) companies seeking to distribute Korean content worldwide. Netflix is a global OTT company that provides a diverse range of content to consumers, including original productions. The STOF (Service, Technology, Organization, Finance) model is used to analyze Netflix's business model, which is suitable for Internet-based businesses. The study highlights the shift from traditional and physical methods of producing and distributing content, such as movies using the existing film method, to completely digital methods in the field of cultural content. The study is valuable for global and domestic OTT operators and policymakers, scholars, entertainment and media companies, and the general public who enjoy cultural content.

EXCHANGE RATES AND STOCK MARKET DYNAMICS: ISLAMIC VERSUS CONVENTIONAL FINANCIAL SYSTEMS

This study investigates the changes and persistence in dynamic connectedness between stock market performance and exchange rate fluctuations, comparing conventional and Islamic financial systems. With an eye on a global financial landscape characterized by the integration of capital markets and the adoption of floating exchange rate regimes, it examines the effects of exchange rate variations on the dynamics of the stock market in nine different countries - the United Kingdom, Australia, Japan, Singapore, Canada, China, India, Korea, and South Africa. The study employs daily data spanning from November 2015 to July 2023 and uses a comprehensive analysis of three-step methodology, including nonparametric causality-in-quantiles tests, asymmetric slope Conditional Autoregressive Valueat-Risk (CAViaR), and Time-Varying Parameter Vector Autoregressive (TVP-VAR) Connectedness measure. Our results underline the asymmetric impact of exchange rate fluctuations on stock markets and highlights the distinctive characteristics of Islamic financial markets. Comparing Islamic and conventional stock markets in the context of exchange rate fluctuations, this study not only serves to fill a gap in the existing literature but also emphasizes the significance of currency exchange rate swings for global investors, policymakers, and practitioners trying to understand the intricacies of global financial markets.

Navigating urban human settlement sustainability: A multi-indicator assessment based on sustainable development goal 11

The sustainability of cities determines human sustainable development. Human settlement is an important element of cities, and scientific monitoring and assessment of it can help cities accurately identify unsustainable issues. Taking Sustainable Development Goal 11 as the basic framework, the study constructs a global development goal-oriented sustainability assessment system for urban human settlement (UHS), including 7 fields and 26 indicators, which serves as a reference for cities globally. And an empirical analysis is conducted using panel data of 143 typical cities in China from 2015 to 2019. The results show that: (1) the score of China's UHS sustainability improved from 54.84 to 58.52, with some cities already achieving the goal of sustainable UHS. More than 50% of the cities were on track to achieve the goal by 2030. (2) Regional scores varied, being higher in the south and lower in the north, with the highest score in the eastern coastal region and the lowest score in the northeastern region. (3) Economy size is significantly and positively correlated with UHS sustainability, which is consistent with the regional performance, but with a marginal decreasing trend. (4) The performance of cities with different population size varied more significantly. The scores of UHS sustainability showed a U-shaped relationship with population size. In response to these findings, this study proposes corresponding strategic measures. The insights gained from the empirical analysis of Chinese cities can inform global policymaking.

“It's very much part of this movement to undermine democracy”: A qualitative study of European Union level opposition strategies against reproductive health and rights

Despite increasing contestations of agreed global commitments on sexual and reproductive health and rights (SRHR), our understanding of strategies of opposition in global health policymaking remains limited. This article explores the opposition to SRHR at the European level focusing on the decision-making institutions of the European Union (EU). The central research questions ask i) how SRHR opposition actors seek to influence EU institutions and ii) what challenges their actions pose for health policymaking at the EU level. Our empirical focus is based on the qualitative method of framework analysis, with data collected from multiple sources, including documentary data on European Parliamentary debates, Council conclusions of the European Union, reports of nongovernmental organisations, and key informant interviews. Our study is in line with observations on globally coordinated efforts to restrict access to SRH services. This is a challenge for specific forums and countries, but as well for European Union's wider internal and external policies. We present a toolbox of strategies and actors operational at the European Union level. Our findings on opposition to SRHR indicate that it can be seen as a political tool that is part of a broader anti-democratic movement. Understanding strategies of anti-SRHR opposition is important for health policymakers as it shapes debates and the achievement of universal health coverage (UHC).

Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI)

This study examines the multifaceted impact of artificial intelligence (AI) on environmental sustainability, specifically targeting ecological footprints, carbon emissions, and energy transitions. Utilizing panel data from 67 countries, we employ System Generalized Method of Moments (SYS-GMM) and Dynamic Panel Threshold Models (DPTM) to analyze the complex interactions between AI development and key environmental metrics. The estimated coefficients of the benchmark model show that AI significantly reduces ecological footprints and carbon emissions while promoting energy transitions, with the most substantial impact observed in energy transitions, followed by ecological footprint reduction and carbon emissions reduction. Nonlinear analysis indicates several key insights: (i) a higher proportion of the industrial sector diminishes the inhibitory effect of AI on ecological footprints and carbon emissions but enhances its positive impact on energy transitions; (ii) increased trade openness significantly amplifies AI’s ability to reduce carbon emissions and promote energy transitions; (iii) the environmental benefits of AI are more pronounced at higher levels of AI development, enhancing its ability to reduce ecological footprints and carbon emissions and promote energy transitions; (iv) as the energy transition process deepens, AI’s effectiveness in reducing ecological footprints and carbon emissions increases, while its role in promoting further energy transitions decreases. This study enriches the existing literature by providing a nuanced understanding of AI’s environmental impact and offers a robust scientific foundation for global policymakers to develop sustainable AI management frameworks.

Estimating and planning hospital costs of public hospitals in Brazil.

While the estimate of hospital costs concerns the past, its planning focuses on the future. However, in many low and middle-income countries, public hospitals do not have robust accounting health systems to evaluate and project their expenses. In Brazil, public hospitals are funded based on government estimates of available hospital infrastructure, historical expenditures and population needs. However, these pieces of information are not always readily available for all hospitals. To solve this challenge, we propose a flexible simulation-based optimisation algorithm that integrates this dual task: estimating and planning hospital costs. The method was applied to a network of 17 public hospitals in Brazil to produce the estimates. Setting the model parameters for population needs and future hospital infrastructure can be used as a cost-projection tool for divestment, maintenance, or investment. Results show that the method can aid health managers in hospitals' global budgeting and policymakers in improving fairness in hospitals' financing.

Enhancing equity in arts-based research engagement: Methodological considerations from a policy-oriented community-development study

ABSTRACT This paper provides reflexive account of an arts-based communication tool used for a community development project in Manitoba, Canada. Drawing upon an intersectional perspective of social, health, and environmental inequalities, the multi-phase engagement involved citizens (n = 17; n = 9) as well as global policymakers (n = 6) in healthy cities, age-friendly cities, and sustainable city policy arenas. A visual graphic was employed to foster bidirectional dialogue between concerned local residents and global policymakers, forming the backbone of a community engagement strategy. Reflective analysis demonstrates how art can be mobilized toward reducing inequalities while notable challenges remain—including omission of highly-sidelined perspectives amidst complex interdisciplinarity; potential reductionism leading to manufactured consent; and considerations of communities inherently excluded in a qualitative, arts-based community engagement. The impacts of art on power hierarchies, emotion, project efficiency, and privilege are reviewed, with the objective of supporting more inclusive arts-based communications in future research.

Ronapreve (REGN-CoV; casirivimab and imdevimab) reduces the viral burden and alters the pulmonary response to the SARS-CoV-2 Delta variant (B.1.617.2) in K18-hACE2 mice using an experimental design reflective of a treatment use case.

With some exceptions, global policymakers have recommended against the use of existing monoclonal antibodies in COVID-19 due to loss of neutralization of newer variants. The purpose of this study was to investigate the impact of Ronapreve on compartmental viral replication using paradigms for susceptible and insusceptible variants. Virological efficacy and impact on pathogenicity was assessed in K18-hACE2 mice inoculated with either the Delta or BA.1 Omicron variants. Ronapreve reduced sub-genomic viral RNA levels in lung and nasal turbinate, 4 and 6 days post-infection, for the Delta variant but not the Omicron variant. It also blocked brain infection, which is seen with high frequency in K18-hACE2 mice after Delta variant infection. At day 6, the inflammatory response to lung infection with the Delta variant was altered to a multifocal granulomatous inflammation in which the virus appeared to be confined. The current study provides evidence of an altered tissue response to SARS-CoV-2 after treatment with a monoclonal antibody combination that retains neutralization activity. These data demonstrate that experimental designs that reflect treatment use cases are achievable in animal models for monoclonal antibodies. Extreme caution should be taken when interpreting prophylactic experimental designs that may not be representative of treatment.IMPORTANCEFollowing the emergence of the SARS-CoV-2 Omicron variant, the WHO recommended against the use of Ronapreve in its COVID-19 treatment guidelines due to a lack of efficacy based on current pharmacokinetic-pharmacodynamic understanding. However, the continued use of Ronapreve, specifically in vulnerable patients, was advocated by some based on in vitro neutralization data. Here, the virological efficacy of Ronapreve was demonstrated in both the lung and brain compartments using Delta as a paradigm for a susceptible variant. Conversely, a lack of virological efficacy was demonstrated for the Omicron variant. Comparable concentrations of both monoclonal antibodies were observed in the plasma of Delta- and Omicron-infected mice. This study made use of a reliable murine model for SARS-CoV-2 infection, an experimental design reflective of treatment, and demonstrated the utility of this approach when assessing the effectiveness of monoclonal antibodies.

Global policymaking: the patchwork of global governance

Global policymaking: the patchwork of global governance

Global burden of skin and subcutaneous diseases and its association with socioeconomic status in children and adolescents: an analysis of the Global Burden of Diseases Study 2019.

Skin and subcutaneous diseases are one of the most common problems affecting the health of children and adolescents. The purpose of this study was to investigate the burden of skin and subcutaneous diseases among children and adolescents and its association with socioeconomic status. Data was obtained from the Global Burden of Disease Study 2019. The number of cases, incidence rate, number of deaths, and death rate in 204 countries and territories from 1990 to 2019 were extracted and stratified by age, sex, and socioeconomic status. In 2019, the global incidence and death rates of skin and subcutaneous diseases in children and adolescents were 57966.98 (95% Uncertainty Interval [UI] 53776.15 to 62521.24) per 100,000 and 0.21 (95% UI 0.13 to 0.26) per 100,000, respectively. From 1990 to 2019, the global incidence rate increased by 5.80% (95% UI 4.82-6.72%) and the death rate decreased by 43.68% (95% UI 23.04-65.27%). The incidence and death rates were negatively correlated with socioeconomic status. Incidence rates were not different between females and males, but death rates were higher among females than males. The highest incidence and death rates were found in the 1-4-year age group and < 1-year age group, respectively. The global burden of skin and subcutaneous diseases in children and adolescents was characterized by regional imbalances. The global burden of skin and subcutaneous diseases in children and adolescents from poorer regions requires more attention. This study provides strong evidence for global policymaking for childhood and adolescent diseases.

Exploring the Impact of Lead on Health and Strategies to Prevent the Adverse Consequences

Lead is one of the ten chemicals of major public health concern, and has been linked to environmental degradation and significant deterioration of human health. Multiple age-group-specific harmful effects in children, pregnant women, and adults have been reported secondary to lead exposure. Even though lead-associated adverse effects have been recognized in different parts of the world, the key barrier is the least priority assigned to it by public health officials worldwide. To conclude, owing to both short- and long-term effects of lead in different age groups, it is high time that global policymakers should prioritize lead poisoning and take appropriate measures to effectively deal with the public health menace of lead.