Search Results (5,551)

This study presents an approach based on machine learning (ML) techniques to analyze the relationship between emergency room (ER) admissions for cardiorespiratory diseases (CRDs) and environmental factors. The aim of this study is the development and verification of an interpretable machine learning framework applied to environmental and health data to assess the relationship between environmental factors and daily emergency room admissions for cardiorespiratory diseases. The model’s predictive accuracy was evaluated by comparing simulated values with observed historical data, thereby identifying the most influential environmental variables and critical exposure thresholds. This approach supports public health surveillance and healthcare resource management optimization. The health and environmental data, collected through meteorological sensors and air quality monitoring stations, cover eleven years (2013–2023), including meteorological conditions and atmospheric pollutants. Four ML models were compared, with XGBoost showing the best predictive performance (R² = 0.901; MAE = 0.047). A 10-fold cross-validation was applied to improve reliability. Global model interpretability was assessed using SHAP, which highlighted that high levels of carbon monoxide and relative humidity, low atmospheric pressure, and mild temperatures are associated with an increase in CRD cases. The local analysis was further refined using LIME, whose application—followed by experimental verification—allowed for the identification of the critical thresholds beyond which a significant increase in the risk of hospital admission (above the 95th percentile) was observed: CO > 0.84 mg/m³, P_atm ≤ 1006.81 hPa, Tavg ≤ 17.19 °C, and RH > 70.33%. The findings emphasize the potential of interpretable ML models as tools for both epidemiological analysis and prevention support, offering a valuable framework for integrating environmental surveillance with healthcare planning. Full article

Background: Exposure-based cognitive behavioral therapy (Ex-CBT) is widely seen as the gold-standard treatment for anxiety and obsessive-compulsive disorder (OCD). Yet, minoritized youth are underrepresented in efficacy studies, raising questions about the applicability of Ex-CBT to minoritized youth. Effectiveness data suggest systematic adaptation of Ex-CBT to address youth culture and context is likely needed, and many clinicians make adaptations and augmentations in practice. However, research on the specific strategies clinicians use to address their youth clients’ culture and context within anxiety and OCD treatment is lacking. In the current study, we assess practice-based adaptations, augmentations, and process-based approaches utilized when delivering treatment to youth for OCD and anxiety in public mental health clinics. Methods: We conducted qualitative interviews with 16 clinicians from both specialty anxiety and general mental health clinics serving youth with anxiety or OCD in the public mental health system. Participating clinicians had a mean age of 32.19 (SD = 5.87) and 69% of therapists identified as female; 69% identified as White, 25% identified as Asian, and 6% as Black or African American. In qualitative interviews, clinicians shared how they addressed clients’ culture and context (e.g., social identities, stressors and strengths related to social identities and lived environment). Thematic analysis identified the strategies clinicians employed to address culture and context. Results: Clinicians reported incorporating culture and context through process-based approaches (e.g., building trust gradually, considering clients’ social identity stressors, engaging in self-awareness to facilitate cultural responsiveness) and through culturally adapting and augmenting treatment to promote person-centered care. Core strategies included proactive and ongoing assessment of clients’ cultural and contextual factors, adapting exposures and augmenting Ex-CBT with strategies such as case management and discussion of cultural context, and taking a systems-informed approach to care. Conclusions: Examining practice-based adaptations, augmentations, and process-based approaches to treatment for minoritized youth with OCD or anxiety can inform efforts to understand what comprises person-centered culturally responsive Ex-CBT. Empirical testing of identified strategies is a needed area of future research. Full article

Design Thinking (DT) has emerged as a relevant methodology for addressing global challenges aligned with the United Nations Sustainable Development Goals (SDGs). This study presents a systematic literature review, conducted following PRISMA 2020 guidelines, which analyzes 42 peer-reviewed publications from 2013 to 2023. Through inductive content analysis, 10 core DT principles—such as empathy, iteration, user-centeredness, and systems thinking—I identified and thematically mapped to specific SDGs, including goals related to health, education, innovation, and climate action. The study also presents five real-world cases from diverse sectors such as technology, healthcare, and urban planning, illustrating how DT has been applied to address practical challenges aligned with the SDGs. However, the review identifies persistent gaps in the field: the lack of standardized evaluation frameworks, limited integration across SDG domains, and weak adaptation of ethical and contextual considerations, particularly in vulnerable communities. As a response, this paper recommends the adoption of structured impact assessment tools (e.g., Cities2030, Responsible Design Thinking), integration of design justice principles, and the development of participatory, iterative ecosystems for innovation. By offering both conceptual synthesis and applied insights, this article positions Design Thinking as a strategic and systemic approach for driving sustainable transformation aligned with the 2030 Agenda. Full article

Rabies remains a significant global public health concern, causing an estimated 59,000–69,000 human fatalities annually. Despite being entirely preventable through vaccination, rabies continues to impose substantial economic burdens worldwide. This study presents a scoping review of the economic research on rabies to determine overlaps and gaps in knowledge and inform future research strategies. We selected 150 studies (1973–2024) to analyze. The review categorizes the literature based on geographic distribution, species focus, and type of study. Findings indicate that economic studies are disproportionately concentrated in developed countries, such as the United States and parts of Europe, where rabies risk is low, while high-risk regions, particularly in Africa and Asia, remain underrepresented. Most studies focus on dog-mediated rabies, reflecting its dominant role in human transmission, while fewer studies assess the economic impacts of wildlife and livestock-mediated rabies. Case studies and modeling approaches dominate the literature, whereas cost–benefit and cost–effectiveness analyses—critical for informing resource allocation—are limited. The review highlights the need for more economic evaluations in rabies-endemic regions, expanded research on non-dog reservoirs, and broader use of economic methods. Addressing these gaps will be crucial for optimizing rabies control and supporting global initiatives to eliminate dog-mediated rabies by 2030. Full article

Background: Access to safe and reliable water and sanitation remains a critical public health and development challenge, with rural and low-income communities being disproportionately affected by inadequate services and heightened exposure to waterborne diseases. Despite global efforts and infrastructure-based progress indicators, significant disparities persist, and these often overlook users’ perceptions of water quality, reliability, and safety. This study explores the determinants of household satisfaction with drinking water in rural areas, comparing subjective user feedback with official access data to reveal gaps in current monitoring approaches and support more equitable, user-centered water governance. Methods: This study was conducted in Kazakhstan’s Atyrau Region, where 1361 residents from 86 rural villages participated in a structured survey assessing household access to drinking water and perceptions of its quality. Data were analyzed using descriptive statistics and multinomial logistic regression to identify key predictors of user satisfaction, with results compared against official records to evaluate discrepancies between reported experiences and administrative data. Results: The field survey results revealed substantial discrepancies between official statistics and residents’ reports, with only 58.1% of respondents having in-house tap water access despite claims of universal coverage. Multinomial logistic regression analysis identified key predictors of user satisfaction, showing that uninterrupted supply and the absence of complaints about turbidity, odor, or taste significantly increased the likelihood of higher satisfaction levels with drinking water quality. Conclusions: This study underscores the critical need to align official water access statistics with household-level experiences, revealing that user satisfaction—strongly influenced by supply reliability and sensory water quality—is essential for achieving equitable and effective rural water governance. Full article

Although organizational resilience is well established, refining the systematic quantitative evaluation of health systems resilience (HSR) remains an ongoing opportunity for advancement. Research either focuses on individual HSR indicators, such as social welfare policy, public expenditure, health insurance, healthcare quality, and technology, or broadly examines socio-economic factors, highlighting the need for a more comprehensive methodological approach. This study employed the Slacks-Based Measure (SBM) within Data Envelopment Analysis (DEA) to analyze efficiency by maximizing outputs. It systematically examined key HSR factors across countries, providing insights for improved policymaking and resource allocation. Taking a five-year (2016–2020) dataset that covered 55 to 56 countries and evaluating 17 indicators across governance, health systems, and economic aspects, the paper presents that all sixteen top-ranked countries with a perfect efficiency score of 1 belonged to the high-income group, with ten in Europe, highlighting regional HSR differences. This paper concludes that adequate economic resources form the foundation of HSR and ensure stability and sustained progress. A properly supported healthcare workforce is essential for significantly enhancing health systems and delivering quality care. Last, effective governance and the equitable allocation of resources are crucial for fostering sustainable development and strengthening HSR. Full article

The extensive use of pesticides has significant implications for public health and the environment. Breeding crop plants is the most effective and environmentally friendly approach to improve the plants’ resistance. However, it is time-consuming and costly, and it is sometimes difficult to achieve satisfactory results. Plants induce defense responses to natural elicitors by interpreting multiple genes that encode proteins, including enzymes, secondary metabolites, and pathogenesis-related (PR) proteins. These responses characterize systemic acquired resistance. Humic substances trigger positive local and systemic physiological responses through a complex network of hormone-like signaling pathways and can be used to induce biotic and abiotic stress resistance. This study aimed to assess the effect of humic substances on the activity of phenylalanine ammonia-lyase (PAL), peroxidase (POX), and β-1,3-glucanase (GLU) used as a resistance marker in various plant species, including orange, coffee, sugarcane, soybeans, maize, and tomato. Seedlings were treated with a dilute aqueous suspension of humic substances (4 mM C L⁻¹) as a foliar spray or left untreated (control). Leaf tissues were collected for enzyme assessment two days later. Humic substances significantly promoted the systemic acquired resistance marker activities compared to the control in all independent assays. Overall, all enzymes studied in this work, PAL, GLUC, and POX, showed an increase in activity by 133%, 181%, and 149%, respectively. Among the crops studied, citrus and coffee achieved the highest activity increase in all enzymes, except for POX in coffee, which showed a decrease of 29% compared to the control. GLUC exhibited the highest response to HS treatment, the enzyme most prominently involved in increasing enzymatic activity in all crops. Plants can improve their resistance to pathogens through the exogenous application of HSs as this promotes the activity of enzymes related to plant resistance. Finally, we consider the potential use of humic substances as a natural chemical priming agent to boost plant resistance in agriculture Full article

Sexual health constitutes a fundamental aspect of overall well-being, with direct implications for individual development and the broader social and economic progress of communities. Promoting environments that ensure sexual experiences free from coercion, discrimination, and violence is a key public health priority. Sexuality, in this regard, should be understood as an inherent dimension of human experience, shaped by biological, cultural, cognitive, and ideological factors. Accordingly, sexual health education requires a holistic and multidimensional approach that integrates sociocultural, biographical, and professional perspectives. This study aims to examine the level of knowledge and training in sexual health among nursing students and healthcare professionals, as well as to assess the extent to which sexual health content is incorporated into nursing curricula at Spanish universities. A scoping review was conducted using the Dialectical Structural Model of Care (DSMC) as the theoretical framework. The findings indicate a significant lack of knowledge regarding sexual health among both nursing students and healthcare professionals, largely due to educational and structural limitations. Furthermore, sexual health education remains underrepresented in nursing curricula and is frequently addressed from a narrow, fragmented biomedical perspective. These results highlight the urgent need for the comprehensive integration of sexual health content into nursing education. Strengthening curricular inclusion is essential to ensure the preparation of competent professionals capable of delivering holistic, inclusive, and empowering care in this critical area of health. Full article

Urban green infrastructure plays a vital role in the sustainable development of cities. As urban areas expand, green spaces are increasingly affected. The pressure from new developments leads to a reduction in vegetation and raises new public health risks. Addressing this challenge requires effective planning, maintenance, and continuous monitoring. To enhance traditional approaches, remote sensing is becoming a vital tool for city-wide observations. Publicly available large-scale data, combined with machine learning models, can improve our understanding. We explore the potential of Sentinel-2 to classify and extract meaningful features from urban landscapes. Using advanced machine learning techniques, we aim to develop a robust and scalable framework for classifying urban environments. The proposed models will assist in monitoring changes in green spaces across diverse urban settings, enabling timely and informed decisions to foster sustainable urban growth. Full article

Incineration at sea is a significant source of marine pollution, threatening biodiversity and public health. Although Peru ratified the 1996 London Protocol in 2018, key deficiencies persist in its domestic legal framework, particularly the absence of clear and internationally aligned definitions for “incineration” and “incinerator.” These gaps hinder effective enforcement by the National Maritime Authority (NMA-DICAPI) and limit regulatory compliance with international obligations. This study analyzes Peru’s current legislation in light of the London Protocol and includes a comparative overview of regional regulatory approaches in Latin America. Based on this analysis, the study identifies regulatory inconsistencies that compromise environmental protection and proposes three key legal reforms: (1) refining the definition of “incineration” to reflect international standards; (2) formally incorporating a definition for “incinerator”; and (3) establishing specific administrative and economic sanctions for related infractions. Through comparative analysis with Mexico and Colombia’s approaches, we propose targeted amendments including refined definitions aligned with IMO standards and explicit administrative/economic sanctions. Implementing these recommendations would enhance Peru’s legal clarity, enforcement capacity, and compliance with international maritime law, reinforcing its role as a responsible actor in marine environmental governance. Full article

Background: Brain health is a growing public health priority due to the high global burden of neurological and mental disorders. Promoting brain health across the lifespan supports individual and societal well-being, creativity, and productivity. Objective: To address the need for specialized education in this field, the University of Bern developed a Certificate of Advanced Studies (CAS) in Brain Health. This article outlines the program’s rationale, structure, and goals. Program Description: The one-year, 15 ECTS-credit program is primarily online and consists of four modules: (1) Introduction to Brain Health, (2) Brain Disorders, (3) Risk Factors, Protective Factors and Interventions, and (4) Brain Health Implementation. It offers a multidisciplinary, interprofessional, life-course approach, integrating theory with practice through case studies and interactive sessions. Designed for healthcare and allied professionals, the CAS equips participants with skills to promote brain health in clinical, research, and public health contexts. Given the shortage of trained professionals in Europe and globally, the program seeks to build a new generation of brain health advocates. It aims to inspire action and initiatives that support the prevention, early detection, and management of brain disorders. Conclusions: The CAS in Brain Health is an innovative educational response to a pressing global need. By fostering interdisciplinary expertise and practical skills, it enhances professional development and supports improved brain health outcomes at individual and population levels. Full article

This study presents an extended approach to compartmental modeling of infectious disease spread, focusing on regional heterogeneity within affected areas. Using classical SIS, SIR, and SEIR frameworks, we simulate the dynamics of COVID-19 across two major regions of Ukraine—Dnipropetrovsk and Kharkiv—during the period 2020–2024. The proposed mathematical model incorporates regionally distributed subpopulations and applies a system of differential equations solved using the classical fourth-order Runge–Kutta method. The simulations are validated against real-world epidemiological data from national and international sources. The SEIR model demonstrated superior performance, achieving maximum relative errors of 4.81% and 5.60% in the Kharkiv and Dnipropetrovsk regions, respectively, outperforming the SIS and SIR models. Despite limited mobility and social contact data, the regionally adapted models achieved acceptable accuracy for medium-term forecasting. This validates the practical applicability of extended compartmental models in public health planning, particularly in settings with constrained data availability. The results further support the use of these models for estimating critical epidemiological indicators such as infection peaks and hospital resource demands. The proposed framework offers a scalable and computationally efficient tool for regional epidemic forecasting, with potential applications to future outbreaks in geographically heterogeneous environments. Full article

Urban heat islands (UHIs) are a growing sustainability challenge impacting public health, energy use, and climate resilience, especially in hot, arid cities like San Antonio, Texas, where land surface temperatures reach up to 47.63 °C. This study advances a data-driven, interdisciplinary approach to UHI mitigation by integrating Machine Learning (ML) with physical and socio-demographic data for sustainable urban planning. Using high-resolution spatial data across five functional zones (residential, commercial, industrial, official, and downtown), we apply three ML models, Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM), to predict land surface temperature (LST). The models incorporate both environmental variables, such as imperviousness, Normalized Difference Vegetation Index (NDVI), building area, and solar influx, and social determinants, such as population density, income, education, and age distribution. SVM achieved the highest R² (0.870), while RF yielded the lowest RMSE (0.488 °C), confirming robust predictive performance. Key predictors of elevated LST included imperviousness, building area, solar influx, and NDVI. Our results underscore the need for zone-specific strategies like more greenery, less impervious cover, and improved building design. These findings offer actionable insights for urban planners and policymakers seeking to develop equitable and sustainable UHI mitigation strategies aligned with climate adaptation and environmental justice goals. Full article

Biofilms are structured microbial communities that pose significant challenges to food safety and quality within the food-processing industry. Their formation on equipment and surfaces enables persistent contamination, microbial resistance, and recurring outbreaks of foodborne illness. This review provides a comprehensive synthesis of current knowledge on biofilm formation mechanisms, genetic regulation, and the unique behavior of multi-species biofilms. The review evaluates modern detection and monitoring technologies, including PCR, biosensors, and advanced microscopy, and compares their effectiveness in industrial contexts. Real-world outbreak data and a global economic impact analysis underscore the urgency for more effective regulatory frameworks and sanitation innovations. The findings highlight the critical need for integrated, proactive biofilm management approaches to safeguard food safety, reduce public health risks, and minimize economic losses across global food sectors. Full article

Background and Objectives: Diabetes is a global public health challenge, with increasing prevalence worldwide. The implementation of artificial intelligence (AI) in the management of this condition offers potential benefits in improving healthcare outcomes. This study primarily investigates the barriers and facilitators perceived by healthcare professionals in the adoption of AI. Secondarily, by analyzing both quantitative and qualitative data collected, it aims to support the potential development of AI-based programs for diabetes management, with particular focus on a possible bottom-up approach. Materials and Methods: A scoping review was conducted following PRISMA-ScR guidelines for reporting and registered in the Open Science Framework (OSF) database. The study selection process was conducted in two phases—title/abstract screening and full-text review—independently by three researchers, with a fourth resolving conflicts. Data were extracted and assessed using Joanna Briggs Institute (JBI) tools. The included studies were synthesized narratively, combining both quantitative and qualitative analyses to ensure methodological rigor and contextual depth. Results: The adoption of AI tools in diabetes management is influenced by several barriers, including perceived unsatisfactory clinical performance, high costs, issues related to data security and decision-making transparency, as well as limited training among healthcare workers. Key facilitators include improved clinical efficiency, ease of use, time-saving, and organizational support, which contribute to broader acceptance of the technology. Conclusions: The active and continuous involvement of healthcare workers represents a valuable opportunity to develop more effective, reliable, and well-integrated AI solutions in clinical practice. Our findings emphasize the importance of a bottom-up approach and highlight how adequate training and organizational support can help overcome existing barriers, promoting sustainable and equitable innovation aligned with public health priorities. Full article