Search Results (594)

Ebola alerts reveal the truth about preparedness. They show whether a health system can recognize danger early, protect health workers, isolate and care for patients, trace contacts, communicate clearly, and sustain public trust before fear replaces cooperation. In the Pandemic Agreement Era, this truth has become harder to ignore. The 2026 Bundibugyo virus disease outbreak in the Democratic Republic of the Congo and Uganda is a sharp reminder that the principles of pandemic prevention, preparedness, response, equity, and cooperation become meaningful only when they work where the first cases occur. In the absence of licensed vaccines and specific treatments for Bundibugyo virus disease, preparedness depends on the basic functions of public health: surveillance, diagnosis, infection prevention and control, referral, risk communication, community engagement, and operational coordination. These functions are often described as routine. They are not. During high-consequence infectious disease alerts, they serve as the primary protective infrastructure. Ebola also exposes a deeper ethical failure. Frontline countries and communities are expected to contain threats of global relevance, but international support often intensifies only after the risk becomes visible beyond the affected area. This reactive model is neither fair nor efficient. The WHO Pandemic Agreement defines a political direction for a more equitable and coordinated global response. Here, Ebola is not presented as a typical pandemic event but as an operational test of preparedness, solidarity, early support to affected settings, and international cooperation. Ebola alerts test whether that direction can become an operational reality before escalation. Digital tools, telemedicine, and artificial intelligence may strengthen this agenda but only when they make local systems faster, safer, more trusted, and more usable. Ebola preparedness is therefore not only a technical task. It is a test of responsibility. Full article

The sustainability of buildings and the built environment extends beyond energy and environmental performance to circular resource use, health and safety, digital infrastructure, and stakeholder collaboration. This exploratory integrative literature review examines how these established but insufficiently connected domains reshape business models in the built environment. Since the built environment is a major source of global carbon emissions and waste, a primary research stream concerns the transition toward circular economy principles beyond traditional profit-maximization logics. The literature also highlights the potential of health- and safety-oriented innovations to reduce risks and improve indoor environments. Other studies highlight the potential of digital innovations to improve life-cycle management, resource efficiency, and risk mitigation. However, their widespread adoption faces systemic barriers, including data interoperability and cybersecurity issues, implementation costs, skills shortages, organizational resistance, and regulatory and governance challenges. The literature often emphasizes technical potential while paying less attention to value-capture mechanisms and the allocation of costs, risks, benefits, and responsibilities among the actors involved. Integrating sustainable practices, digital infrastructures, circular-economy principles, and collaborative governance is therefore essential to develop economically viable, organizationally feasible, and ethically responsible business models for the built environment, across the building life cycle and among public and private stakeholders. Full article

Decisions about vector-borne zoonotic disease control often have to be made before the evidence is complete. Human surveillance, entomological observations, animal reservoir or sentinel data, environmental indicators, and modelling outputs may provide warning before human disease patterns are clear. In some settings, early action can prevent harm, yet it can also impose social, economic, ecological, animal-welfare, liberty-related, and trust-related burdens. Technical risk assessment remains necessary, although it may need to be complemented by ethical analysis. In this conceptual manuscript, we propose a seven-step One Health ethical decision-making framework that links integrated evidence and transmission plausibility to precaution, proportionality, equity, One Health trade-offs, legitimacy, feedback, impact evaluation, and adaptation. Its contribution lies not in introducing new ethical principles, but in integrating them into an iterative governance sequence and proposing medical bioethics mediation for persistent value conflict. Illustrative domains include West Nile virus, dengue, Zika, Crimean–Congo haemorrhagic fever, and other mosquito-, tick-, and sand fly-borne zoonotic threats. Full article

Public social-media content often contains self-disclosed personal attributes that appear low-risk in isolation but become privacy-relevant when linked across posts, platform accounts, or user-level traces. Existing research has advanced privacy-sensitive content detection, de-anonymization analysis, social-media research ethics, and privacy-compliance workflows; however, limited work operationalizes how personal-data disclosures combine structurally and how these structures can be translated into auditable governance actions. This paper proposes SEM-PDPL, a computational, privacy-law-informed risk-assessment framework for modeling public social-media exposure as semantic exposure graphs and mapping graph patterns to controls aligned with the United Arab Emirates Personal Data Protection Law (PDPL) and compatible with GDPR principles. SEM-PDPL combines governance scoping; a PDPL-informed disclosure taxonomy; hybrid extraction using rule-based methods; named-entity recognition; fine-tuned BERT; and schema-constrained large language model annotation, followed by graph construction at post, platform, corpus, and persona levels. The framework is evaluated on a synthetic multi-platform corpus of 1095 posts generated for 150 personas across 290 platform accounts. Results show that, within this controlled synthetic corpus, fine-tuned BERT provides the strongest extraction performance among six evaluated methods, achieving a macro-F1 of 0.975. Graph analysis shows that exposure density increases with aggregation, rising from 0.275 at post level to 1.000 at corpus level, and from 0.859 at platform level to 0.967 at persona level. Across all graph resolutions, quasi-identifiers emerge as the dominant weighted-degree and betweenness node, indicating that ordinary location, employer, school, and demographic cues often function as bridges connecting sensitive categories such as health and biometric data to identifying information. These findings indicate that, within this controlled corpus, privacy risk in public social-media data is not only attribute-based but also structurally graph-shaped. SEM-PDPL contributes an explainable and reproducible framework for identifying exposure hubs, sensitive bridges, and aggregation risks before applying masking, minimization, exclusion, retention, or review controls. The framework does not automate legal compliance; rather, it provides evidence-based decision support for privacy-aware social-media analytics. Full article

Background: The health sector is getting transformed with the usage of AI, be it diagnosis, treatment planning, disease prediction, and or health system management. Research in this field has picked up in the last few years, which was made possible with the emergence of machine learning, natural language processing and the increasing number of e-health records. Objectives: The study aims to investigate the current trends in the implementation of artificial intelligence (AI) applications in medical settings by investigating the global scientific output/landscape on this theme, such as the annual publication trends, country-wise contributions, and publishing patterns. Methods: The current study is based on systematic review by combining bibliometric analysis and cluster analysis using VOSviewer version 1.6.20, R software version 4.5.0, and Biblioshiny (Bibliometrix package in R) along with preferred reporting items for systematic reviews and meta analyses (PRISMA), 2020 which provides transparency and rigorous visualization to examine the articles published in English on the use of AI in healthcare, after the onset of COVID-19 till date i.e., from 2020 to 2026 on the Scopus database. Results: Using the relevant search string, 5940 documents were identified between 2020 and 2026, 1434 were included for analysis after screening and relevant filters. The publications have increased remarkably after 2020 on this theme and more than half of the publications have their roots in the discipline of Medicine. The USA, China, and the United Kingdom have contributed the most to the volume of research. Natural language processing and diagnosis are the emerging themes. The Journal of Medical Internet Research, BMC Medical Informatics and Decision Making, Computers in Biology and Medicine, IEEE Journal of Biomedical and Health Informatics, Frontiers in Public Health, and Digital Health are some of the most influential sources in the field. Li J and Liu X are among the authors with remarkable local impact. Conclusions: The work aims to assist investigators, health care professionals, and policymakers to learn about modern trends and focus on critical areas of future research and collaboration in AI-enhanced health care. The limitation of the study is that it considered only the Scopus database but it has opened up opportunities for researchers for analysis using other databases such as Dimensions, Lens, and PubMed. Also, this review is considering the publication record since the onset of COVID-19 but a comparative analysis of pre and post-pandemic studies can also be conducted to get a holistic view of drastic collaboration of research in this field. Discussions: The findings suggest that the role of artificial intelligence in health care has paramount over recent years, with other supporting technologies but a technologically hesitant population as well as low acceptance of AI due to ethical issues, cannot be ignored for ensuring efficiency in the health sector. Full article

Facility dogs are increasingly incorporated throughout higher-education institutions as integrative conduits for supporting students by reducing stress, anxiety, and emotional exhaustion. While these programs are designed to enhance student well-being, little is known about the experiences of the handlers who train, care for, and work with these dogs—specifically within military-affiliated programs. The handlers’ role necessitates a unique dynamic of caregiving, emotional labor, and professional responsibility and management that can create role conflict and additional stress among those graduate students who dedicate their time to the working dogs. Despite the growing presence of animal-assisted interventions in university settings, handler experiences in military graduate contexts are largely unexplored. In an effort to establish ethical and sustainable animal-assisted interventions and facility dog programs that contribute to population-level mental-health resilience and institutional public health, there must be greater understanding of the demands and implications of the handler’s workload to develop sustainability. Therefore, this paper highlights the need for qualitative inquiry to explore the intersection of handler experience and educational responsibilities, as integrated into the military environment. Full article

Gambling disorder is a public health concern, but research on the early detection of gambling-related harm is limited by the scarcity of ethically shareable online conversations. This study presents a framework for generating an entirely synthetic dataset for natural language processing research on gambling-related behavioral signals. Behavioral dimensions from the Online Gambling Disorder Questionnaire were used to construct 2100 risk-aligned user profiles and generate X/Twitter-style monologues and multi-user threads across gambling and non-gambling subtopics. The dataset contains 35,346 monologues and 1716 threads. The generated text was evaluated using automatic metrics, manual target-consistency assessment, and downstream classification under user-disjoint and parent-topic-disjoint protocols. Automatic and manual evaluations indicated acceptable linguistic quality and consistency with predefined behavioral targets. In the stricter parent-topic-disjoint setting, logistic regression achieved a macro-$F_1$ of 0.884 for binary gambling-content detection, whereas four-level risk prediction remained more difficult. These results show that the dataset contains learnable signals for computational detection of gambling-related content without exposing real-user data. However, the dataset was not externally validated against authentic social-media conversations and is not intended for clinical diagnosis. The resulting resource is designed to support reproducible research on gambling disorder and mental health while preserving user privacy. Full article

Behavioural nudges modify choice architecture to steer food choices without removing alternatives or substantially changing economic incentives. This critical narrative review synthesises 62 sources from behavioural public policy, public health nutrition, food ethics, and sustainable food-system governance. It distinguishes healthy food nudges, sustainable food nudges, green nudges, and responsible food-system interventions, and compares availability, placement, defaults, labels, digital architecture, and mixed policy packages. The evidence shows that nudges influence immediate food selection, but effects are heterogeneous and weaker for sustained environmental outcomes. Price instruments address affordability, nudges address attention and convenience, and boosts strengthen decision competence; none can substitute for the others. Ethical acceptability requires a transparent, calibrated opt-out process, equity monitoring, disclosure of commercial motives, democratic accountability, and integration with structural policy. Public institutions and profit-driven digital platforms therefore require different governance safeguards. Nudges are most defensible as components of coordinated food-system policy rather than stand-alone solutions. Full article

Background: The rapid adoption of artificial intelligence (AI) in healthcare and management information systems has posed both opportunities and challenges in assessing value across clinical, operational, governance and societal dimensions. Existing healthcare value models are inadequate for the dynamic, data-rich, and ethically complex nature of AI-enabled care and thus necessitate a broader evaluative framework. Objective: This paper proposes an AI-Augmented Healthcare Value Framework (AI-HVF) designed as a multidimensional evaluative lens for assessing value in AI-enabled healthcare across structural, process, outcome, cost, and governance domains. Methods: A narrative, theory-driven literature review was undertaken of healthcare quality frameworks, value-based healthcare, digital health, AI in medicine and public health to identify limitations of existing models and to derive the required dimensions for an updated framework. The dimensions were synthesized into an integrated conceptual model linking structures, processes, outcomes, costs and governance in AI-enabled healthcare. Results: AI-HVF transforms traditional healthcare value models in a data-rich and automated care era. Structural dimensions include digital infrastructure, workforce readiness, learning health systems, and operational efficiency; process dimensions include AI-supported clinical excellence, patient experience, prevention, and explainability; and outcome dimensions go beyond traditional clinical metrics to include equity, safety, continuity, provider well-being, sustainability, and societal value. It also includes real cost accounting and has governance, ethics and trust as an overarching layer that supports accountability, transparency and fairness across all domains. Conclusions: AI-HVF provides a multi-dimensional framework to assess, plan and govern AI in health care at the patient, organization, and system levels. It is intended to enable retrospective evaluation and prospective implementation. The framework offers a foundation for developing future indicators, pilot testing and for comparative evaluation of ethical, equitable and sustainable AI integration in healthcare. Full article

Neonatal screening using Dried Blood Spot (DBS) cards is an important and successful public health facility in Europe, enabling early detection of congenital disorders for early treatment and prevention of overt disease. Biobanks of stored DBS cards offer significant potential for biomedical research. Biobanking and secondary use of DBS cards also raise ethical and legal issues, particularly concerning the rights of parents and children. This study provides a comprehensive overview of legislation and legal practices governing DBS biobanking across 29 European countries, based on a survey conducted in collaboration with the International Society for Neonatal Screening. Findings reveal a highly heterogeneous landscape: 15 countries have national legislation, five have regional guidelines, and nine lack formal regulations. Only four countries require explicit parental consent for DBS storage, with considerable variation in approval processes for research use. A harmonization of practices, with the European General Data Protection Regulation (GDPR) as a basis for future regulation, supplemented by clearer guidance on ‘public interest’ and robust safeguards for individual rights may lead to more transparent and consistent governance, which is essential to balance scientific progress with the protection of parental and children’s rights in DBS-based research across Europe. Full article

Background: Depression and anxiety disorders remain among the leading contributors to global disability and represent a major public health challenge. Although evidence-based psychotherapies are available, access to treatment remains limited due to structural, economic, geographical, and workforce-related barriers. Digital mental health interventions have emerged as scalable approaches to reducing this treatment gap, with artificial intelligence (AI)-guided cognitive behavioral therapy (CBT) representing a rapidly developing and clinically relevant extension of digital psychotherapy. Objective: This review aims to synthesize current evidence on digital and AI-guided CBT interventions for depression and anxiety, with a focus on clinical utility, scalability, mechanisms of change, safety considerations, and public health relevance. In addition, the review proposes a clinically oriented conceptual framework for understanding the role of AI-guided CBT within contemporary digital psychiatry. Methods: A focused narrative review was conducted using PubMed, Scopus, and Google Scholar databases, covering publications from 2010 to 2025. Relevant peer-reviewed studies, systematic reviews, meta-analyses, and conceptual papers addressing digital CBT, AI-assisted CBT, conversational agents, symptom monitoring, and digital mental health implementation were identified and analyzed qualitatively. Results: Existing evidence suggests that internet-delivered CBT, mobile applications, and AI-based conversational agents may reduce depressive and anxiety symptoms, particularly in individuals with mild to moderate conditions. However, the evidence base remains heterogeneous, with limitations including short follow-up periods, variability in intervention quality, reliance on self-reported outcomes, and insufficient data on long-term effectiveness, safety, and real-world implementation. Emerging concepts such as digital therapeutic alliance, continuous symptom monitoring, adaptive intervention delivery, and AI-driven personalization may represent key factors influencing engagement and clinical outcomes. Conclusions: AI-guided CBT represents a promising but still evolving component of modern mental health care. These technologies have the potential to improve accessibility, optimize resource allocation, and support stepped-care and hybrid models of treatment. Future research should prioritize rigorous clinical validation, long-term outcome evaluation, transparent safety protocols, ethical governance, and integration into real-world health systems. AI-guided CBT should not be understood as a replacement for clinicians, but as a complementary and scalable extension of evidence-based psychotherapy. Full article

Background: An estimated 25 million children globally miss routine vaccinations each year, with 14.3 million classified as zero-dose and the majority residing in low- and lower-middle-income countries (LMICs). Pharmacies are recognised as accessible healthcare delivery points, yet their role in paediatric immunisation in LMICs is not well defined. This literature review sought to evaluate pharmacist-provided vaccination services for paediatric patients in LMICs. Methods: A systematic review was conducted following Cochrane and PRISMA guidelines. Five databases and grey literature were searched for articles published between January 2005 and June 2026. Studies were reviewed by multiple authors to reduce the risk of individual bias and included if they reported original research involving pharmacists in LMICs delivering vaccination-related services to children aged 12 years and under. For each study, items intended for extraction included country, pharmacy setting, specific vaccines administered, patient age range, and specific roles for the pharmacist in the vaccination administration process. The protocol for this systematic review was registered with the Nelson Mandela University Faculty of Health Sciences Postgraduate Studies Committee and the Research Ethics Committee for Humans (H23-HEA-PHA-007). Results: Of 162 identified records, four studies from Bangladesh, Ethiopia, India, and Jordan met inclusion criteria. No study described pharmacists routinely administering paediatric vaccines. Instead, findings focused on indirect involvement, system readiness, and public perception. Significant barriers included limited infrastructure, inadequate training, and lack of regulatory authority. Study results were limited by a lack of information published and inclusion of only articles available in English. Conclusions: Evidence on pharmacist-administered paediatric vaccinations in LMICs is scarce. Expanding pharmacist roles could improve access and reduce zero-dose prevalence, but would require policy support, infrastructure investment, and further implementation research. Full article

The digitalization of healthcare systems has transformed the production, storage, and sharing of clinical information. While electronic health records (EHRs) enhance care efficiency, accessibility, and continuity, they simultaneously introduce complex ethical, legal, and cybersecurity challenges that directly affect patient interests. This narrative review examines the emerging rights associated with digital health records, particularly the right to privacy and the right to be forgotten, alongside threats to confidentiality, cybersecurity, and patient safety. A comprehensive literature search was conducted across PubMed, Web of Science, MEDLINE, and the Cochrane Library. First, the right to be forgotten appears particularly relevant for oncological patients facing financial discrimination and for individuals asserting gender identity rights, yet it cannot be unconditionally extended to genetic data, given its relevance to relatives and future generations. Second, confidentiality risks are amplified by re-identification vulnerabilities, unauthorized access by personnel, and the broad connectivity of digital systems. Third, the secondary use of data from EHRs, including artificial intelligence (AI) integration, commercial exploitation, and large language model training, raises substantial privacy concerns. Fourth, ransomware, phishing, and data breaches can erode patient trust. In this article, we analyze these issues within the evolving European regulatory framework, highlighting the tension between individual privacy rights and broader public interests. We argue that robust data protection must be balanced with scientific progress and that this requires opt-in consent frameworks, staff training, and transparent AI governance. Full article

Precision prevention and control of genetic diseases represent a major public health challenge. This paper provides a structured narrative review of advances in molecular diagnostic technologies across the preconception, preimplantation, and prenatal stages over the past five years. In the preconception phase, next-generation sequencing has become central to carrier screening, while long-read sequencing significantly enhances detection capabilities for complex variants. In the preimplantation phase, research has increasingly focused on non-invasive preimplantation genetic testing, leveraging maternal contamination quantification algorithms and deep learning models to address DNA contamination challenges. During the prenatal phase, stratified diagnostic strategies combining chromosomal microarray analysis and whole-exome sequencing have improved the diagnostic evaluation of fetal structural anomalies. Simultaneously, non-invasive prenatal testing is expanding to include microdeletion/duplication and monogenic disease screening, though positive screening results still require invasive diagnostic confirmation. Future trends lie in multi-technology integration, multi-omics data fusion, and artificial intelligence-assisted decision-making, aiming to enhance resolution while balancing health-economic considerations and ethical standards. Full article

Objective: Varicella zoster virus (VZV), a member of the Herpesviridae family, is known as the causative agent of chickenpox (varicella). Following primary infection, VZV can remain latent for life and may reactivate over time to cause herpes zoster (shingles). Advanced age, immunodeficiency, and certain chronic illnesses are major risk factors for the development of herpes zoster. To prevent herpes zoster, a live zoster vaccine was licensed in 2006, followed by a recombinant zoster vaccine with higher efficacy in 2018. In Türkiye, the recombinant zoster vaccine was licensed in 2024. Raising awareness among healthcare workers is important both for their own health and the safety of vulnerable patients. This study aimed to evaluate healthcare workers’ knowledge and awareness of herpes zoster infection and zoster vaccines across the country, as well as to determine the prevalence of prior herpes zoster infection among them. Methods: After obtaining ethical approval, a nationwide multicenter survey was conducted. A questionnaire was distributed to healthcare workers via an online link. Participation was entirely voluntary. The survey collected demographic information (age, sex, profession, years of experience) and included questions on knowledge of herpes zoster, history of zoster infection, symptoms and severity (if applicable), awareness of the zoster vaccine, and vaccination attitudes. Results: A total of 5180 healthcare workers participated, of whom 3505 were female. The participants ranged in age from 18 to 79 years (mean age: 34.24 ± 11.52). Regarding professions: 47.9% were physicians, 21.3% were nurses or midwives, 0.8% were dentists or dental technicians, and 30% were from other healthcare professions. Among participants, 54.4% had ≤10 years of professional experience, 20% had comorbidities, and 10.5% were using immunosuppressive medications. It was found that 9.6% had previously had herpes zoster, 8.8% had no knowledge of the disease, 39.6% were aware of the vaccine, and 20.1% were unwilling to pay for vaccination. Multivariate binary logistic regression analysis revealed that being a physician significantly increased the likelihood of having correct knowledge by 1.961 times compared to other professions (p < 0.001, CI: 1.608–2.392). Similarly, those who had heard of herpes zoster were 3.191 times more likely to answer correctly than those who had not (p = 0.011, CI: 1.650–6.172). Male gender was significantly associated with a lower likelihood of having accurate knowledge compared to females (p = 0.001, OR = 0.720, CI: 0.594–0.874). Conclusions: This study revealed that healthcare workers’ knowledge and awareness regarding herpes zoster and its vaccines are generally insufficient. The recent licensing of the vaccine in Türkiye may explain this, but it is critical for healthcare professionals to be more informed about risk groups and vaccination indications in order to enhance the effectiveness of preventive healthcare services. Given the potential for serious complications of herpes zoster in elderly and immunocompromised individuals, the importance of vaccination should be emphasized more strongly to healthcare workers. Furthermore, the finding that 20.1% of those aware of the vaccine were deterred by its cost highlights the need to improve vaccine accessibility. Economic barriers preventing healthcare workers from being vaccinated emphasize the importance of making the vaccine widely available through public support to protect both healthcare workers and patient safety. Full article