Search Results (824)

Public health emergencies of international concern (PHEIC) generate worldwide public health impacts, making the international dissemination of risk information critically important for both global health governance and sustainable development. The global media system facilitates this dissemination through collaborative and interdependent networks, enhancing mutual understanding and strengthening the resilience of global health communication systems. This study examines PHEIC-related information flows by constructing and analyzing news citation networks during multiple outbreaks to characterize patterns of information exchange between Africa and other regions. We identify key participants, analyze thematic structures, and investigate the structural determinants influencing information flow. The results reveal significant inequalities in public health risk information exchange between Africa and other world regions, evident in participant composition, engagement modes, thematic focus, and interaction intensity. These asymmetries reflect underlying disparities in global communication capacity and socioeconomic development, indicating that information inequality has become a critical dimension of global health and sustainability challenges. Promoting equitable access to public health information and strengthening Africa’s media and communication capacity are essential steps toward achieving inclusive, resilient, and sustainable global health governance. Full article

As a key indicator for measuring urban green visibility, the Green View Index (GVI) reflects actual visible greenery from a human perspective, playing a vital role in assessing urban greening levels and optimizing green space layouts. Existing studies predominantly rely on single-source remote sensing image analysis or traditional statistical regression methods such as Ordinary Least Squares and Geographically Weighted Regression. These approaches struggle to capture spatial variations in human-perceived greenery at the street level and fail to identify the non-stationary effects of different drivers within localized areas. This study focuses on the Luolong District in the central urban area of Luoyang City, China. Utilizing Baidu Street View imagery and semantic segmentation technology, an automated GVI extraction model was developed to reveal its spatial differentiation characteristics. Spearman correlation analysis and Multiscale Geographically Weighted Regression were employed to identify the dominant drivers of GVI across four dimensions: landscape pattern, vegetation cover, built environment, and accessibility. Field surveys were conducted to validate the findings. The Multiscale Geographically Weighted Regression method allows different variables to have distinct spatial scales of influence in parameter estimation. This approach overcomes the limitations of traditional models in revealing spatial non-stationarity, thereby more accurately characterizing the spatial response mechanism of the Global Vulnerability Index (GVI). Results indicate the following: (1) The study area’s average GVI is 15.24%, reflecting a low overall level with significant spatial variation, exhibiting a “polar core” distribution pattern. (2) Fractal dimension, normalized vegetation index (NDVI), enclosure index, road density, population density, and green space accessibility positively influence GVI, while connectivity index, Euclidean nearest neighbor distance, building density, residential density, and water body accessibility negatively affect it. Among these, NDVI and enclosure index are the most critical factors. (3) Spatial influence scales vary significantly across factors. Euclidean nearest neighbor distance, building density, population density, green space accessibility, and water body accessibility exert global effects on GVI, while fractal dimension, connectivity index, normalized vegetation index, enclosure index, road density, and residential density demonstrate regional dependence. Field survey results confirm that the analytical conclusions align closely with actual greening conditions and socioeconomic characteristics. This study provides data support and decision-making references for green space planning and human habitat optimization in Luoyang City while also offering methodological insights for evaluating urban street green view index and researching ecological spatial equity. Full article

Background/Objectives: Oman Vision 2040, the national blueprint for socio-economic transformation, aims to elevate the Sultanate to developed nation status, with the “Health” priority committed to building a “Leading Healthcare System with International Standards” via a Health in All Policies (HiAP) approach. This paper critically reviews Oman’s strategic health directions and implementation frameworks under Vision 2040, assessing their alignment with global Sustainable Development Goals (SDGs) and serving as a case model for health system transformation. Methods: This study employs a critical narrative synthesis based on a comprehensive literature search that included academic, official government reports, and international organization sources. The analysis is guided by the World Health Organization’s (WHO) Health Systems Framework, providing a structured interpretation of progress across its six building blocks. Results: Key interventions implemented include integrated governance (e.g., Committee for Managing and Regulating Healthcare), diversified health financing (e.g., public private partnership (PPPs), Health Endowment Foundation), and strategic digital transformation (e.g., Al-Shifa system, AI diagnostics). Performance metrics show progress, with a rise in the Legatum Prosperity Index ranking and an increase in the Community Satisfaction Rate. However, critical challenges persist, including resistance to change during governance restructuring, cybersecurity risks from digital adoption, and system fragmentation that complicates a unified Non-Communicable Disease (NCD) response. Conclusions: Oman’s integrated approach, emphasizing decentralization, quality improvement, and investment in preventive health and human capital, positions it for sustained progress. The transformation offers generalizable insights. Successfully realizing Vision 2040 demands rigorous, evidence-informed policymaking to effectively address equity implications and optimize resource allocation. Full article

Cardiovascular diseases (CVDs) are the leading cause of death globally. Electrocardiograms (ECGs) are crucial diagnostic tools; however, their traditional interpretations exhibit limited sensitivity and reproducibility. This systematic review discusses the recent advances in artificial intelligence (AI), including deep learning and machine learning, applied to ECG analysis for CVD detection. It examines over 100 studies from 2019 to 2025, classifying AI applications by disease type (heart failure, myocardial infarction, and atrial fibrillation), model architecture (convolutional neural networks, long short-term memory, and hybrid models), and methodological innovation (signal denoising, synthetic data generation, and explainable AI). Comparative tables and conceptual figures highlight performance metrics, dataset characteristics, and implementation challenges. Our findings indicated that AI models outperform traditional methods, especially in terms of detecting subclinical conditions and enabling real-time monitoring via wearable technologies. Nonetheless, issues such as demographic bias, lack of dataset diversity, and regulatory hurdles persist. The review concludes by offering actionable recommendations to enhance clinical translation, equity, and transparency in AI-ECG applications. These insights aim to guide interdisciplinary efforts toward the safe and effective adoption of AI in cardiovascular diagnostics. Full article

Previous research on financial contagion has mostly looked at volatility spillovers using static or fixed parameter models. These models don’t always take into account how inter-market links change and depend on frequency during big crises. This study fills in that gap by looking at how changes in volatility in the G20 equity markets affected four big global events: the global financial crisis of 2008, the European debt crisis, the COVID-19 pandemic, and the Russia-Ukraine war. The study uses a Time-Varying Parameter Vector Autoregression (TVP VAR) framework along with the Baruník-Křehlík frequency domain spillover measure to look at how connectedness changes over short-term (1–5 days) and long-term (5–Inf days) time periods. The results show that systemic connectedness changes a lot during crises. For example, the Total Connectedness Index (TCI) was 24–25 percent during the GFC and EDC, 34 percent during COVID-19, and a huge jump to 60 percent during the Russia-Ukraine war. During the global financial crisis and the war between Russia and Ukraine, the US constantly emerged as the largest transmitter. During the European debt crisis, on the other hand, emerging markets like Turkey, South Africa, and Japan acted as net transmitters. During all crisis times, short-term spillovers are the most common. This shows how important high-frequency volatility transmission is. This study is different from others because it uses both time-varying and frequency domain views. This gives us a better idea of how crises change the way global finances are linked. The results are very important for policymakers and investors because they show how important it is to coordinate risk management, improve market safety, and make systemic stress testing better in a global financial world. Full article

Sustainability assessment has emerged as a critical research area given the pressing challenges of balancing economic growth, environmental protection, and social equity. This study aims to develop an objective and reproducible framework to evaluate sustainability efficiency across countries by integrating multiple development dimensions into a unified decision model. Despite substantial prior research, inconsistencies often arise due to data heterogeneity and conflicting criteria. To address this gap, a hybrid multi-criteria decision-making (MCDM) framework was developed by combining the Double Normalization Method based on Removal Effects of Criteria (DNMEREC) for objective weighting and the Double Normalization Measurement of Alternatives and Ranking according to Compromise Solution (DNMARCOS) method for ranking alternatives. This integration ensures balanced consideration of beneficial and non-beneficial criteria while minimizing subjectivity. The model was empirically validated through a comparative assessment of G7 and BRICS countries using twelve sustainability indicators covering economic, environmental, and social dimensions. Results show significant variations in sustainability efficiency, with G7 countries generally demonstrating higher overall performance, while BRICS nations exhibit strong growth potential but face environmental and structural constraints. These findings confirm the robustness of the DNMEREC-DNMARCOS framework and highlight its adaptability to complex, multidimensional datasets. The study contributes a transparent methodological tool for researchers and policymakers seeking evidence-based strategies to enhance global sustainability performance and bridge development gaps. Full article

Against the global rollout of Carbon Border Adjustment Mechanisms (CBAMs), carbon tariffs have emerged as a core tool for developed economies to internalize environmental externalities—especially for energy-intensive imports that dominate cross-border carbon flows. However, emission information asymmetry, a critical barrier to implementing cross-border energy and environmental policies, undermines the design of optimal carbon tariffs, as it distorts the link between tariff levels and actual fossil energy-related emissions. This study develops a two-country analytical model to examine how biased assessments of exporters’ carbon intensity influence optimal tariff settings, exporters’ strategic behavior, and aggregate carbon emissions—with a focus on energy-intensive production contexts. The results show that underestimating carbon intensity reduces exporters’ compliance costs, incentivizing emission concealment; this weakens tariffs’ environmental stringency and may raise global emissions. Overestimation, by contrast, inflates exporters’ marginal costs, discouraging green investment and causing emission displacement rather than reduction. The analysis highlights a policy feedback loop wherein misjudged emission information distorts both trade competitiveness and environmental performance. This study concludes that a transparent, accurate, and internationally verifiable carbon accounting system is essential: it not only facilitates the effective implementation of CBAM but also aligns optimal carbon tariffs with CBAM’s dual goals of climate action and trade equity, while supporting global energy transition efforts. Full article

This study explores sustainable urbanism in the three largest Saudi Arabian cities—Riyadh, Jeddah, and NEOM—in the context of Vision 2030. Qualitative methodology was used, which incorporated environmental, social, economic, governance, and mobility aspects. The analysis of ten semi-structured interviews with planners, engineers, and policy officials was based on Strategic Environmental Assessment (SEA), Sustainable Urbanism, and Participatory Governance models. The results indicate that Riyadh presents structural congruence and consistency of policies, Jeddah is characterized by disjointed governance and poor coordination, and NEOM is characterized by futuristic aspirations with unpredictable social inclusiveness. The paper highlights that more powerful integration of governance, participatory planning, and realistic implementation is required to create a balance between technological innovations and equity in society. It adds to the current knowledge of how the global sustainability models can be localized in the fast-changing cities of the Gulf. Full article

Syphilis, a curable sexually transmitted infection, has resurged globally, challenging public health systems in both high-income countries and low- and middle-income countries (LMICs). In nations like the United States, the United Kingdom, parts of Europe, Canada, and Japan, cases have surged due to declining condom use, digital platforms facilitating casual sex, and practices like chemsex and broader drug use for sex, with rising congenital syphilis rates. In LMICs, such as those in East Africa, South Asia, Latin America, and Southeast Asia, limited healthcare access, inadequate prenatal screening, and socioeconomic barriers drive persistent high prevalence, particularly among pregnant women and vulnerable populations. Despite contextual differences, shared drivers include stigma, health disparities, and outdated surveillance systems. This resurgence underscores the need for globally coordinated, equity-focused strategies, including universal syphilis testing, modernized surveillance, and context-specific sexual health education. Addressing structural and behavioral factors through collaborative international efforts is critical to reversing this trend and strengthening global STI control. Full article

Background: The COVID-19 pandemic led to an unprecedented global health and economic crisis, and vaccination emerged as a critical intervention to control the spread of the virus and mitigate its impact on health systems and economies. Despite the rapid development and deployment of vaccines, the financial commitments required for these vaccination programs are substantial, necessitating a comprehensive understanding of the associated costs to inform future public health strategies and resource allocation. Method: This analysis estimates the global, regional, and national economic costs of COVID-19 vaccination across 234 countries and regions in the period 2020–2023, consisting of vaccine procurement costs and administration costs. Result: As of 31 December 2023, the global costs of COVID-19 vaccination programs were estimated at USD 246.2 billion, with vaccine procurement accounting for approximately USD 140.2 billion and administration costs totaling USD 96.4 billion. Globally, a cumulative total of 136.9 billion doses of COVID-19 vaccines had been administered. Factoring in an estimated wastage rate of 10%, it is projected that approximately 150.6 billion doses were used. On a global scale, the average number of vaccine doses administered per capita was estimated at 1.73. The mean cost per capita was USD 17.70 (95% CI: USD 15.84–19.56) for vaccine procurement and USD 12.16 (95% CI: USD 10.29–14.02) for administration, resulting in a total average cost of USD 29.85 (95% CI: USD 26.33–33.37) per capita. Significant disparities in costs were observed across income groups and regions. High-income countries incurred a notably higher average cost per capita of USD 76.90 (95% CI: USD 72.38–81.41) in contrast to low-income countries, where the per capita cost was USD 7.20 (95% CI: USD 5.38–9.02). For middle-income countries, the average per capita costs were USD 15.02 (95% CI: USD 10.64–19.40) in lower-middle-income countries and USD 28.21 (95% CI: USD 23.60–32.83) in upper-middle-income countries. Regionally, the Americas (AMR) reported the highest total cost at USD 70.8 billion, with an average per capita cost of USD 65.23 (95% CI: USD 56.18–74.28). The Western Pacific Region (WPR) followed with a total cost of USD 63.9 billion and an average per capita cost of USD 31.93 (95% CI: USD 20.35–43.51). Conversely, the African Region (AFR) had the lowest total spending at USD 10.8 billion and a per capita cost of USD 8.85 (95% CI: USD 5.34–12.37), reflecting both lower vaccine procurement and administration costs. The European Region (EUR) recorded a high average per capita cost of USD 53.36 (95% CI: USD 46.79–59.94), with procurement costs at USD 31.28 (95% CI: USD 27.41–35.14) and administration costs of USD 22.09 (95% CI: USD 19.31–24.87). Conclusions: The global rollout of COVID-19 vaccination revealed substantial variation in cost structures across income groups. Procurement costs imposed greater burdens on low- and lower-middle-income countries, whereas delivery and administration costs dominated in higher-income settings. These disparities highlight persistent fiscal inequities and emphasize the need for stronger international coordination and cost transparency to enhance equity, efficiency, and preparedness in future vaccination efforts. Full article

Point-of-care (POC) infectious disease diagnostics are reshaping global health by delivering rapid, decentralized, and clinically actionable results that link bedside testing to population-level surveillance. Valued at approximately USD 53 billion in 2024 and projected to nearly double by 2033, the global POC diagnostics market is driven by infectious disease assays and accelerated by innovations in molecular amplification, biosensors, microfluidics, and artificial intelligence (AI). This review integrates current evidence across technological, clinical, regulatory, and public health domains. Immunoassays remain the backbone of volume deployment, while molecular nucleic acid amplification tests (NAATs) and emerging CRISPR-based platforms achieve laboratory-grade sensitivity at the point of care. AI has transitioned from an experimental tool to an embedded analytical layer that enhances image interpretation, multiplex signal deconvolution, and automated quality control. Rigorous validation, including analytical accuracy, clinical performance in intended-use settings, and usability testing under CLIA guidance, remains central to ensuring reliability in decentralized environments. Regulatory frameworks are adapting in parallel: FDA’s lifecycle oversight of AI-enabled devices, the European IVDR’s expanded evidence requirements, and the WHO Prequalification all emphasize continuous post-market surveillance. From a public health perspective, POC diagnostics have improved early case detection, treatment initiation, and outbreak containment for HIV, tuberculosis, malaria, influenza, RSV, and COVID-19. Yet persistent challenges (including limited harmonization of standards, uneven reimbursement, and scarce real-world data from low- and middle-income countries) continue to constrain equitable adoption. POC infectious disease diagnostics are thus entering a pivotal phase of digitization and regulatory maturity. Addressing remaining gaps in validation, lifecycle monitoring, and implementation equity will determine whether these technologies achieve their full promise as clinical accelerators and as cornerstones of global infectious disease preparedness. Full article

This research investigates the extent to which behavioral biases—specifically overconfidence and representativeness heuristic—affect linguistic tone, narrative structure, and predictive accuracy of financial reports produced by investment analysts operating across diverse global markets. Drawing upon a comprehensive dataset comprising 1575 equity recommendation reports authored by 15 analysts from four major international investment banks between 2019 and 2022, the study evaluates how cognitive tendencies shape report composition and forecast precision. A mixed-methods approach was employed, incorporating qualitative textual analysis and quantitative modeling through random-effects panel regressions. Key constructs assessed include narrative complexity, optimism, visual content usage, and forecast deviation metrics. Our findings reveal that overconfidence significantly influences the tone and detail of analyst reports but does not demonstrably impact projection accuracy. Conversely, representativeness heuristics were not found to consistently affect either report language or earnings-per-share forecast errors. Institutional affiliation emerged as a significant determinant of predictive success, while demographic factors such as gender, native language, and geographic region had limited explanatory power. These findings imply that investors should treat report tone as an indicator of analyst disposition rather than forecast quality, while financial institutions may benefit from training programs aimed at mitigating narrative and stylistic biases in analyst communication. Full article

This entry examines how wage-setting institutions (WSIs) shape wages across advanced economies. It focuses on four core mechanisms—minimum wages, collective bargaining, wage coordination, and wage centralization—drawing on theoretical insights, empirical evidence, and cross-country comparisons. The analysis shows that minimum wages safeguard low-paid workers but have heterogeneous employment effects depending on their level and enforcement. Collective bargaining raises average wages and compresses wage inequality, though it can reduce flexibility and create insider–outsider dynamics. Wage coordination stabilizes wage growth, prevents inflationary spirals, and fosters equity, while wage centralization promotes solidarity wages and macroeconomic discipline but may limit adaptability. Using The Organization for Economic Co-operation and Development (OECD) and Institutional Characteristics of Trade Unions, Wage Setting, State Intervention and Social Pacts (ICTWSS) data, the study highlights institutional diversity, ranging from coordinated Nordic models to fragmented liberal systems, and identifies trends toward “organized decentralization”. Policy implications suggest that WSIs should be viewed not as rigidities but as adaptable frameworks that can balance efficiency, equity, and stability when carefully designed. The conclusion emphasizes that the future of wage-setting lies in leveraging institutional complementarities to respond to globalization, technological change, and shifting labor market conditions. Full article

The world is far from meeting the goals of the Paris Agreement of limiting the rise of global temperature to below 1.5 °C, with dire consequences for Small Island Developing States (SIDS) in particular. If SIDS are to address their climate vulnerabilities through policy-induced resilience building, they need to have a robust governance framework in place that coherently addresses climate change adaptation and disaster risk reduction. What would such a governance framework look like? To address this question, we carried out a systematic literature review of papers published between 1992 and 2023. Our review reveals that the governance around climate change adaptation and disaster risk reduction is relatively weak in SIDS. However, the analysis of barriers and enablers unveils the contours of a proposed three-tiered governance framework, the application of which needs to be contextualised: Tier 1 comprises three key pillars: Policy Planning, Institutional Arrangements, and Laws and Regulations; Tier 2 identifies the principles of transparency, accountability, equity, legitimacy, and subsidiarity; the core pillars and the principles are nested within a broader Tier 3 comprising democratic processes (rule of law), religious and cultural values, and political commitment. In order for SIDS to fight the existential threat of climate change, the proposed framework will allow SIDS to better understand their climate governance framework and deliver low-carbon, climate resilient development within the broader ambit of sustainable development. This framework also addresses the weakness in previous studies, which consider dimensions, principles, and enabling an environment of good governance on equal footing. We illustrate this framework using the analogy of the lotus flower. Full article

South Africa’s overlapping crises, namely ecological overshoot, energy insecurity, unemployment, and inequality, are not isolated challenges but systemic outcomes of a political economy dependent on growth. This article advances a degrowth by design framework that positions systems thinking as the primary driver of transformative change. By embedding Meadows’ leverage points within canonical archetypes such as Limits to Growth, Shifting the Burden, Success to the Successful, and Tragedy of the Commons the analysis demonstrates how reinforcing and balancing feedbacks perpetuate overshoot and social inequity and how targeted leverage strategies can reorient systems toward sufficiency, equity, and ecological repair. The framework integrates decolonial ethics, Ubuntu-informed relational dignity, pluriversal design perspectives, and legislative anchors such as South Africa’s Climate Change Act and Just Energy Transition. While the contribution is primarily conceptual, it is strengthened by illustrative vignettes, descriptive statistics, and the proposal of measurable indicators including material footprint per capita and energy intensity of wellbeing. Acknowledging the limitations of qualitative mapping and partial empirical application, the article outlines a research agenda centred on empirical validation, comparative municipal case studies, participatory action research, and open indicator repositories. The unique contribution lies in reframing degrowth as a diagnostic and prescriptive leverage strategy that is both contextually grounded and transferable. Rooted in South Africa yet relevant across the Global South, the degrowth compass functions as a normative and analytical benchmark to guide contested transitions toward just and ecologically restorative futures. Full article