Search Results (2,960)

Along with the coronavirus pandemic (COVID-19), some in the medical publication industry have observed an “infodemic”, which is more pandemic than the virus. Given the lack of sufficient pandemic preparedness measures in many countries, people started posting millions of posts on social media without questioning their veracity or accuracy, particularly within Arabic-speaking communities. This study investigates an unsupervised model for detecting fake news in Arabic to fight the infodemic. While there has been much research on fake news detection (FND) in English, this subject in Arabic has yet to be investigated enough in the literature. We examine the use of distribution-based clustering techniques for Arabic FND and show their performance compared to each other. Moreover, we conduct a comprehensive linguistic analysis, identifying significant differences in textual features between real and fake posts, which can improve fake news detection. Our research shows the potential of online learning techniques to enhance model performance, leading to high accuracy, reaching up to 92%. By addressing the unique challenges posed by Arabic-language posts, our research offers practical implications for developing effective strategies for reducing infodemics and their social consequences and for strategic planning to control the current and future infodemics. Full article

This study presents one of the first empirical assessments of artificial intelligence (AI) and machine learning (ML) adoption within architectural academia and the Architecture, Engineering, and Construction (AEC) industry in Saudi Arabia. Using a cross-sectional survey of 113 respondents—60 academics and 53 industry professionals—the research examines familiarity, current usage, perceived benefits, challenges, and future readiness for AI/ML integration. Results show high familiarity and strong perceived importance across both sectors, yet actual implementation remains uneven. Very large firms demonstrate the highest adoption capacity, while small and medium-sized firms face financial and organizational constraints. Academic institutions exhibit moderate familiarity but limited curricular and research integration due to faculty expertise gaps, restricted access to tools, and traditional pedagogical structures. Despite these barriers, both sectors consistently identify AI/ML as critical for enhancing creativity, efficiency, and industry preparedness. The study highlights organizational capacity as the primary determinant of adoption. It concludes with recommendations for curriculum reform, faculty training, industry–academia collaboration, and national policy frameworks to accelerate digital transformation aligned with Saudi Vision 2030. This research establishes a foundational baseline for future longitudinal and comparative studies on AI/ML integration in the regional architectural ecosystem. Full article

Data centers are critical digital infrastructure supporting cloud computing, artificial intelligence, and global information services. Despite their high-reliability design, they remain vulnerable to fire incidents due to continuous operation, high electrical loads, dense power systems, and the increasing use of lithium-ion batteries. Although such events are rare, their consequences can be severe, including service disruption, equipment damage, financial loss, and risks to data integrity. This study presents a systematic literature review of fire safety risk management frameworks in data centers, following PRISMA guidelines. Peer-reviewed studies published between 2020 and 2025 were retrieved from Scopus and Web of Science, screened, and appraised using structured quality criteria. Twelve empirical studies were synthesized and benchmarked against NFPA 75 and NFPA 76 standards. The findings are organized into three domains: Strategic Management, Fire Risk, and Fire Preparedness. The results show a strong focus on technical prevention and electrical hazards, while organizational readiness, emergency response, and recovery remain underexplored. Benchmarking indicates that industry standards adopt a more comprehensive lifecycle approach than the academic literature. This study reframes data center fire safety as a socio-technical reliability system and highlights critical gaps, providing a foundation for future research and improved fire safety governance and resilience. Full article

Infections caused by arboviruses, a diverse group of viral pathogens transmitted by biting arthropod vectors, mainly mosquitoes, ticks, and midges, can cause a range of illnesses in humans, from mild, influenza-like symptoms to severe neurological complications including encephalitis and viral hemorrhagic fever. According to 2024 World Health Organization statistics, vector-borne diseases collectively account for over 700,000 human deaths annually, with mosquito-borne infections such as dengue, chikungunya, Zika, and yellow fever constituting a growing and significant proportion of this burden. What was once considered a problem localized to poorly resourced settings in tropical and subtropical regions is now becoming a pervasive global challenge. This is due largely to a combination of factors including climate change, transcontinental travel, and urbanization, with the geographical spread and intensity of arboviral outbreaks reaching unprecedented levels during the current century. In much the same way that the escalating global burden of bacterial infections resistant to antibiotics has been described as a silent pandemic, the insidious rise of arboviruses begs questions regarding outbreak preparedness, prevention and control. Here, we highlight the pressing need for comprehensive strategies that incorporate various health sectors to mitigate the emergence and resurgence of arboviral diseases. Future directives that should be prioritized are outlined. As demonstrated by epidemiological trends and historical outbreak data, an orchestrated global response is critical not only for managing current threats but also for preventing future epidemics. Full article

Background: The resurgence of Mpox (formerly known as monkeypox) since the 2022 global outbreak has exposed weaknesses in surveillance, diagnosis, and public risk communication systems. Despite increased clinical understanding, limitations in knowledge, attitudes, and practices (KAP) among both healthcare workers (HCWs) and the general population continue to challenge prevention and control measures. Numerous systematic reviews have been published on KAP toward Mpox, yet their findings remain fragmented. This review aimed to consolidate the existing evidence from published systematic reviews to provide a unified understanding of global KAP levels related to Mpox. Methods: We followed the PRISMA guidelines for this systematic review of systematic reviews. The article search was conducted in PubMed, Embase, and the Cochrane Library for systematic reviews published between January 2010 and October 2025. Data was extracted on study design, population, and reported quantitative outcomes. Results: Five studies met the inclusion criteria: three focused on HCWs, while two focused on the general population. Among HCWs, knowledge ranged from 26.0% to 46.7%, and attitudes from 28.2% to 62.2%. In the general population, knowledge ranged from 33.0% to 46.6%, attitudes from 40.0% to 71.9%, and perceptions averaged around 40.0%. Across both groups, Mpox knowledge was limited, attitudes were moderately positive, and preventive behaviors remained consistently low, revealing a persistent gap between awareness and practice. Conclusions: This review highlights persistent gaps in knowledge, attitudes, and practices among HCWs and the general population. Although global attention increased substantially following the 2022 outbreak, important weaknesses remain in translating knowledge into consistent preventive behaviors. Addressing these gaps requires structured and context-specific interventions. Integrating Mpox-focused modules into mandatory Continuing Medical Education credits for HCWs could ensure sustained competency in diagnosis, infection prevention, and outbreak response beyond peak epidemic periods. For the general population, strategic risk communication campaigns should leverage trusted community leaders and social media influencers in high-risk regions to counter misinformation, reduce stigma, and promote evidence-based preventive behaviors. Embedding these targeted strategies within broader pandemic preparedness and global health security frameworks will be essential to strengthening early detection, public trust, and coordinated outbreak response in future Mpox or other emerging infectious disease events. Full article

Environmental sustainability has emerged as a strategic requirement of those organizations that want to remain competitive in the long run, but most companies continue to adopt green human resource management (GHRM) practices and organizational change initiatives individually, thus restraining their potential transformation. This paper constructs and confirms a combined approach of how the fit between GHRM practices and adaptive change management processes results in high performance in sustainable innovation. In this study, 83 organizations from both the manufacturing and service sectors were selected using a purposive sampling method, to ensure diversity across developed and developing countries and varying levels of GHRM integration (low, moderate, and high). The sample was chosen to represent a broad spectrum of sustainability maturity levels, allowing for a comprehensive analysis of how GHRM practices influence green product, process, and business model innovation. This selection, alongside 30 peer-reviewed studies published between 2020 and 2025, underpins the conceptual framework used to activate change preparedness and link GHRM dimensions with innovation outcomes. I demonstrate that organizations with a high GHRM–change management fit have much higher levels of innovation performance—both in terms of the number of green product innovations (485%) and more sustainable performance improvement (90.5 on average)—than low-integration organizations. Findings also reveal that leadership commitment, employee engagement, organizational learning, and systemic reinforcement are key mediating processes that enhance the effect of GHRM activities. Temporal trajectory analysis demonstrates that integrated organizations go through deployment, consolidation, and optimization phases, as well as increasing returns to performance, with an accelerating trend of 36 months. This paper is important in management research as it fills in gaps in the literature, providing an explanation of how human resource practices facilitate organizational change at the system level. In practice, this study offers evidence-based recommendations to managers who want to establish sustainability-oriented innovation capability by implementing a coordinated GHRM and adaptive change management approach. Full article

Lyme disease is the most common vector-borne disease in North America. Predicting Lyme disease incidence is a key component of public health preparedness. Previously, we demonstrated that the volume of data searches on Google Trends for terms related to Lyme disease, such as “Lyme” and “tick bite”, can be used as a tool to predict monthly human Lyme disease incidence at the state level. The objective of this project was to build upon our previous work by adding environmental and canine data to our predictive models for the prediction of state-level human and canine Lyme disease incidence. Human data were acquired from state health departments. Canine data were acquired from IDEXX Laboratories. We hypothesized that incorporating a One Health approach with human, animal, and environmental data would improve the predictive ability of the models. The One Health model performed significantly better (Mean Absolute Error [MAE] = 12.1) in predicting human disease incidence in 6 out of 16 states compared to the environmental data model (MAE = 16.5), human search terms model (MAE = 21.4), canine data (search terms + case count) model (MAE = 31.1), and the canine case data model (MAE = 32.0). For canine Lyme disease incidence, the One Health model performed worse (MAE = 330.5) compared to the canine search data model (MAE = 282.3), the human data (search terms + cases) model (MAE = 248.4), and the environmental data (MAE = 221.5) model. However, even the best-performing models had large prediction errors, which limit practical utility. Future studies should incorporate alternative data streams, such as electronic health records and insurance claims, to test predictive ability. Full article

Emergency Alert and Warning Systems (EAWSs) are essential components of sustainable disaster risk reduction, providing communities with timely information to prepare for and respond to impending hazards. In the Philippines, one of the world’s most disaster-prone countries, earthquakes, typhoons, and other natural hazards occur frequently. However, national statistics from 2018 indicated that only 40% of Filipinos considered themselves well prepared for disasters, while 31% reported being slightly prepared or not prepared at all. This study investigates the perceived effectiveness of EAWSs in enhancing disaster awareness and preparedness among Filipino residents. Guided by the Theory of Planned Behavior (TPB), the research develops an integrated framework to examine behavioral, technical, and perceptual factors influencing preparedness intentions. Data were collected from 200 respondents through a structured survey. Structural Equation Modeling (SEM) was employed to identify significant linear relationships among the constructs, while an Artificial Neural Network (ANN) analysis was subsequently applied to capture nonlinear patterns and rank the relative importance of key predictors. Unlike previous studies that rely solely on SEM or descriptive approaches, the combined SEM–ANN framework enables a more comprehensive understanding of both causal relationships and complex behavioral dynamics influencing disaster preparedness. The findings reveal that behavioral intention, system reliability, message clarity, and trust in EAWS substantially affect individuals’ preparedness behavior and risk mitigation actions. These results underscore the importance of strengthening EAWS design and communication strategies to support long-term disaster resilience. The study provides practical insights for national agencies, local governments, and policymakers on refining emergency communication systems and developing sustainable, evidence-based disaster preparedness initiatives. Full article

The COVID-19 pandemic highlighted both the transformative potential of mRNA vaccines and the structural challenges associated with their supply chains. Unlike traditional vaccine platforms, mRNA vaccines depend on highly specialized raw materials, including plasmid DNA (pDNA), nucleotides, enzymes, and lipid nanoparticles (LNP), that are produced by a limited number of global suppliers. These dependencies, combined with platform-specific manufacturing processes and stringent cold chain requirements, introduce vulnerabilities across production, distribution, and regulatory oversight. This narrative review examines the distinctive features of mRNA vaccine supply chains and identifies key challenges and opportunities across three interconnected domains: manufacturing systems, logistics and distribution, and regulatory governance. Drawing on literature published between January 2021 and March 2026, the review synthesizes evidence on supply chain bottlenecks revealed during the COVID-19 pandemic, including upstream raw-material dependencies, limitations in manufacturing scale-up, cold chain constraints, and regulatory fragmentation. Particular attention is given to the implications of these challenges for low- and middle-income countries, where infrastructure, technical capacity, and regulatory resources may limit participation in mRNA vaccine production and deployment. The review also highlights emerging strategies to strengthen supply chain resilience, including diversification of input suppliers, development of regional manufacturing hubs, improvements in vaccine thermostability, regulatory harmonization initiatives, and the use of digital technologies for supply chain management. By integrating insights from manufacturing, logistics, and regulatory perspectives, this study contributes to a better understanding of the structural characteristics shaping mRNA vaccine supply chains and identifies priority areas for strengthening global preparedness for future health emergencies. Full article

This study examines how university type (public vs. private) and disciplinary background influence the adoption of Information and Communication Technologies (ICT) and self-perceived digital competence among university professors in Latin America. Identifying institutional and disciplinary disparities is essential in the context of accelerated digital transformation in higher education. The sample comprised 1114 professors from public and private universities, and data was collected using a validated instrument measuring ICT valuation, frequency of use, and perceived digital competence. Multivariate analyses were conducted to assess differences by institutional type and disciplinary field. The results show significant differences in ICT valuation, usage frequency, and perceived digital competence across university types and disciplines. Professors from private universities reported higher digital preparedness, while disciplinary areas displayed distinct ICT adoption patterns. Although ICT use increased across all groups during the pandemic, the digital gap between public and private institutions narrowed but was not fully eliminated. These findings support the development of targeted professional training, strategic resource allocation, and institutional policies, particularly in public universities, to enhance digital competence and promote sustainable ICT integration, contributing to educational equity and progress toward Sustainable Development Goals. Full article

Understanding how viruses engage host cell surfaces is fundamental to infection biology and therapeutic development. While vaccines remain central to prevention, recent global crises have emphasized the need for complementary antiviral strategies that can be mobilized rapidly against both known and emerging pathogens. In this context, artificial intelligence (AI) systems for biomolecular structure prediction, culminating in AlphaFold 3, are reshaping what is experimentally and conceptually achievable. Here, we present “Interactys-AI”, a framework designed to exploit AI-based structural modeling to systematically map virus–host protein–protein interactions (PPIs) and connect them to actionable drug repurposing opportunities. Beyond a technical workflow, Interactys-AI reflects a broader transformation toward predictive and anticipatory antiviral discovery. We describe the conceptual foundations of the platform, its implementation, and its application to influenza A H5N1 hemagglutinin. We further discuss how structural AI may redefine preparedness strategies, highlight current limitations, and outline future directions toward real-time therapeutic hypothesis generation. Full article

This study bridges the existing gaps in quantifying risk and enhancing community defences by applying a cohesive five-pillar risk and resilience framework developed within the C2IMPRESS project. We assessed the anticipated impacts of various C2IMPRESS tools on community resilience across four European case study areas (CSAs): Egaleo (Greece), Mallorca (Spain), Ordu (Turkey), and the Centro Region (Portugal). Methodologically, a targeted survey asked CSA representatives to estimate the expected changes across 42 resilience indicators—encompassing social, institutional, economic, infrastructural, and environmental dimensions—following tool implementation. A public–private-civil partnership (PPCP) framework was also assessed across all sites to enable a comparative analysis. The results indicate that individual vulnerability and emergency preparedness are the most responsive dimensions, exhibiting significant projected improvements alongside institutional capacities and community trust. Conversely, the community economy emerged as the least flexible dimension, exhibiting minimal anticipated change. In conclusion, the C2IMPRESS framework effectively bridges disaster risk reduction and climate adaptation by integrating local knowledge into actionable interventions. However, while social and institutional resilience can be actively enhanced, improving economic resilience requires long-term structural adjustments beyond the scope of these localised tools. Full article

Background: Regulations in some countries of the world allow self-driving vehicles (private cars and robo-taxis) to operate on geofenced, public roads, yet governments are slow to plan as how best to use this automated technology. We pose research questions about the Australian government’s preparedness, planning gaps for a transition to an autonomous public transport system, and specific system components that require attention. Method: We review the relevant literature, and podcasts of automobile manufacturing experts, and draw on our extensive professional experience advising governments in applying the systems approach to a planning system that includes autonomous transport. Results: Governments must include risk management in Type-II road corridors; develop mobility hubs that connect terminals for fully self-driving vehicles and robo-taxis to connect with public transport systems; and include body corporates when engaging the community in precinct planning. In the discussion, we argue the case for an autonomous urban public transport system where private ownership of vehicles is progressively reduced. Conclusions: Australian governments are not prepared with a systems-wide urban planning process that includes autonomous transport and self-driving vehicles. During the transition period, the existing and new transport systems must operate together, emphasising the leading role for governments. A roadmap for further research and development is outlined and this could provide the framework for urban planning in other jurisdictions. Full article

Foodborne botulism, caused by ingestion of pre-formed botulinum neurotoxin, is the most common form of botulism. While large outbreaks linked to commercial foods are rare, smaller outbreaks associated with home-processed products are more frequent, reflecting local dietary habits and traditional preservation practices. The aim of this paper is to provide a public health overview of reported foodborne botulism outbreaks in Romania over an 18-year period to raise awareness among clinicians and public health officials. Between 2007 and 2024, a total of 337 foodborne botulism cases were reported in Romania, of which 43% (147) were related to 55 outbreaks (median number of cases per outbreak: 2; IQR: 2–3). Most outbreaks were reported in Bihor County (11 outbreaks with 29 cases) and its neighboring county, Satu Mare (seven outbreaks, accounting for a total number of 20 cases). Outbreak-related cases were observed in younger persons with a median age of 31 years (compared to 45 years for sporadic cases) and were statistically significantly associated with consumption of pork products (p < 0.001). Fifteen deaths occurred (case fatality ratio: 4%), including three outbreak-related cases (case fatality ratio: 2%). These findings highlight the ongoing public health challenge of foodborne botulism in Romania and the need for robust surveillance, targeted educational initiatives in high-incidence counties to deliver information about safe food preparation and preservation practices, and the continuous availability of botulinum antitoxin supplies. Full article

Background/Objectives: Nonpharmaceutical interventions such as social distancing and face mask use were central to controlling infectious disease transmission during the early phases of the COVID-19 pandemic, particularly when vaccines and treatments were limited or unevenly available. Although public health strategies emphasized individual compliance, adherence varied widely. Empirical evidence remains limited regarding how individuals integrate influences across individual, interpersonal, and community levels when assessing their ability and readiness to socially distance. This study examined how residents evaluated, prioritized, and experienced multi-level factors shaping perceived ability and readiness to practice social distancing during the early phase of the COVID-19 epidemic. Methods: We conducted a cross-sectional online survey of adults (≥18 years) residing in St. Louis City and St. Louis County, Missouri, between April and July 2020. Participants selected and ranked individual/interpersonal and community-level factors influencing social distancing and provided open-ended explanations of their choices. Quantitative data were analyzed descriptively to assess selection frequency and ranking priority. Qualitative responses were analyzed using iterative thematic coding to examine how participants interpreted and combined these factors. Results: The analytic sample included 1692 respondents. At the individual/interpersonal level, family and friends’ distancing behavior (58.9%), desire for in-person interaction (52.4%), and personal risk of COVID-19 (48.9%) were frequently selected, while personal risk, caring for others, and ability to work from home were most often ranked as the highest priority. At the community level, others’ distancing in public spaces (66.2%), availability of COVID-19 testing (58.9%), and businesses’ ability to ensure distancing and sanitation (57.2%) were most frequently selected, with epidemic severity, testing availability, and treatment availability ranked as most influential. Qualitative findings indicated that respondents experienced these influences as interconnected, integrating personal and relational risk, local epidemic conditions, healthcare access, visible community norms, and employer policies. Conclusions: Perceived ability and readiness to practice social distancing emerge from interdependent social and structural conditions rather than isolated individual motivations. Public health responses to emerging infectious diseases may be more effective when individual-level guidance is complemented by accessible testing and treatment, supportive workplace policies, and community environments that visibly reinforce protective behaviors. Full article