Search Results (689)

Background: Since the election of Hamas in 2006, Gaza has endured eight major military conflicts, culminating in the ongoing 2023–2025 war, now surpassing 520 days. This protracted violence, compounded by a 17-year blockade, has resulted in the near-total collapse of Gaza’s health system. Over 49,000 deaths, widespread displacement, and the destruction of more than 60% of health infrastructure have overwhelmed both local capacity and international humanitarian response. Objectives: This narrative review aims to examine and synthesize the current literature (October 2023–April 2025) on the health crisis in Gaza, with a specific focus on identifying key themes and knowledge gaps relevant to rebuilding a sustainable health system. The review also seeks to outline strategic pathways for recovery in the context of ongoing conflict and systemic deprivation. Methods: Given the urgency and limitations of empirical data from conflict zones, a narrative review approach was adopted. Fifty-two sources—including peer-reviewed articles, editorials, reports, and correspondence—were selected through targeted searches using Medline and Google Scholar. The analysis was framed within a public health and political economy perspective, also taking health system building blocks into consideration. Results: The reviewed literature emphasizes emergency needs: trauma care, infectious disease control, and supply chain restoration. Innovations such as mobile clinics and telemedicine offer interim solutions. Gaps include limited attention to mental health (including that of health workers), local governance, and sustainable planning frameworks. Conclusions: Sustainable reconstruction requires a durable ceasefire; international stewardship aligned with local ownership; and a phased, equity-driven strategy emphasizing primary care, mental health, trauma management, and community engagement. Full article

In West Africa, there is a very close link between the phenomenon of trafficking and migrant smuggling. This article will analyze the pressure elements and the causes that drive sub-Saharan people to migrate, placing themselves in the hands of criminal networks that end up exploiting them—women and minors sexually, and men through forced labor. The main corridors departing from West Africa and the characteristics of the criminal groups exercising criminal governance will also be addressed. This research has used both primary and secondary sources, as well as empirical fieldwork consisting of interviews with security force officials, international humanitarian aid organizations, and academic experts on migration issues related to trafficking and smuggling. Our research reveals that the origin of migration is multifactorial. The violence experienced in West Africa, but also the misgovernance, the lack of opportunities for a very young population with limited prospects, and the human insecurity affecting the entire region, are the main reasons that compel people to migrate. In these migration processes, the safety of migrants is compromised as they are forced to start their journey through clandestine means, which exposes them to trafficking networks and thus to violence and exploitation. It is along the migration routes where trafficking and migrant smuggling converge. Full article

Massive relief supplies inter-regional lateral transshipment (MRSIRLT) can significantly enhance the efficiency of disaster response, meet the needs of affected areas (AAs), and reduce deprivation costs. This paper develops an integrated allocation and intermodality optimization model (AIOM) to address the MRSIRLT challenge. A phased interactive framework incorporating adaptive differential evolution (JADE) and improved adaptive large neighborhood search (IALNS) is designed. Specifically, JADE is employed in the first stage to allocate the volume of massive relief supplies, aiming to minimize deprivation costs, while IALNS optimizes intermodal routing in the second stage to minimize the weighted sum of transportation time and cost. A case study based on a typhoon disaster in the Chinese region of Bohai Rim demonstrates and verifies the effectiveness and applicability of the proposed model and algorithm. The results and sensitivity analysis indicate that reducing loading and unloading times and improving transshipment efficiency can effectively decrease transfer time. Additionally, the weights assigned to total transfer time and costs can be balanced depending on demand satisfaction levels. Full article

Understanding flood scenes is essential for effective disaster response. Previous research has primarily focused on computer vision-based approaches for analyzing flood scenes, capitalizing on their ability to rapidly and accurately cover affected regions. However, most existing methods emphasize static image analysis, with limited attention given to dynamic video analysis. Compared to image-based approaches, video analysis in flood scenarios offers significant advantages, including real-time monitoring, flow estimation, object tracking, change detection, and behavior recognition. To address this gap, this study proposes a computer vision-based multi-object tracking (MOT) framework for intelligent flood scene understanding. The proposed method integrates an optical-flow-based module for short-term undetected mask estimation and a deep re-identification (ReID) module to handle long-term occlusions. Experimental results demonstrate that the proposed method achieves state-of-the-art performance across key metrics, with a HOTA of 69.57%, DetA of 67.32%, AssA of 73.21%, and IDF1 of 89.82%. Field tests further confirm its improved accuracy, robustness, and generalization. This study not only addresses key practical challenges but also offers methodological insights, supporting the application of intelligent technologies in disaster response and humanitarian aid. Full article

Background: Surgical care in conflict regions like Tigray, Ethiopia, faces severe challenges due to limited resources, infrastructural deficiencies, and high trauma burden. From 2019 to 2023, a multidisciplinary team conducted five humanitarian missions focusing on orthoplastic reconstruction of extremity and mandibular injuries from high-energy gunshot trauma. Methods: A retrospective analysis was performed on 98 patients who underwent free or pedicled flap reconstruction. Data included demographics, flap type, technique, complications, follow-up, and early clinical outcomes score as well as mobility scores. Flaps were harvested using loupes anastomosis performed using microscopes, depending on availability. Results: Among 98 patients (25.5% female, 74.5% male), 69 free flaps and 38 pedicled flaps were performed. Free fibula flaps (n = 54) included 33 mandibular and 21 extremity reconstructions. Additional flaps included ALT, gracilis, and LD flaps. Pedicled flaps included 18 fibula and 20 ALT/LD flaps. Mean age was 35.5 years; mean operative time was 429.5 min, with mandibular fibula transfers being longest. Microsurgical techniques were used in 34% of cases. Median follow-up was 10 months. Microsurgical complications occurred in 18.4%, mainly in fibula transfers (25.9%). Non-microsurgical issues included wound infections (n = 15), graft loss (n = 3), and bleeding (n = 5). Flap loss occurred in 16.3% overall. Early clinical outcome results were good (30.6%), acceptable (28.6%), and moderate (24.5%). Conclusions: Orthoplastic reconstruction using both free and pedicled flaps is feasible in low-resource, conflict settings. Despite infrastructural challenges, functional outcomes were achievable, supporting the value of adaptable microsurgical strategies in humanitarian surgery. Full article

To obtain actionable information for humanitarian and other emergency responses, an accurate classification of news or events is critical. Daily news and social media are hard to classify based on conveyed information, especially when multiple categories of information are embedded. This research used large language models (LLMs) and traditional transformer-based models, such as BERT, to classify news and social media events using the example of the Sudan Conflict. A systematic evaluation framework was introduced to test GPT models using Zero-Shot prompting, Retrieval-Augmented Generation (RAG), and RAG with In-Context Learning (ICL) against standard and hyperparameter-tuned bert-based and bert-large models. BERT outperformed GPT in F1-score and accuracy for multi-label classification (MLC) while GPT outperformed BERT in accuracy for Single-Label classification from Multi-Label Ground Truth (SL-MLG). The results illustrate that a larger model size improves classification accuracy for both BERT and GPT, while BERT benefits from hyperparameter tuning and GPT benefits from its enhanced contextual comprehension capabilities. By addressing challenges such as overlapping semantic categories, task-specific adaptation, and a limited dataset, this study provides a deeper understanding of LLMs’ applicability in constrained, real-world scenarios, particularly in highlighting the potential for integrating NLP with other applications such as GIS in future conflict analyses. Full article

In the context of the transformation of the modern higher education system, the supra-professional competencies (soft skills) necessary for future specialists in the humanitarian field, in particular, social educators, are of particular importance. The present study is aimed at studying the effectiveness of problem-based learning (PBL) as a method of forming key soft skills among students of the educational program “Social Pedagogy” of the L.N. Gumilyov Eurasian National University. The theoretical part of the study includes an overview of international and domestic scientific discourse on flexible skills and a problem-oriented approach. In the empirical part, the methods of pedagogical experimentation, questionnaires, self-assessment of competencies, and quantitative analysis of the dynamics of soft skill development during the semester were applied. The results indicate a positive correlation between the intensity of students’ participation in PBL practices and the level of development of skills such as critical thinking, teamwork, communicative competence, and time management. The study also identified institutional and methodological barriers to the implementation of PBL in Kazakhstan’s educational practice, including the lack of trained facilitators and the lack of adapted cases. Based on the data obtained, a model of a localized PBL strategy integrated into the training of social educators is proposed. The research contributes to the development of the methodological culture of teacher education and opens up prospects for creating a sustainable system of soft skills formation in universities in Kazakhstan. Full article

Face recognition systems often falter when deployed in uncontrolled settings, grappling with low light, unexpected occlusions, motion blur, and the degradation of sensor signals. Most contemporary algorithms chase raw accuracy yet overlook the pragmatic need for uncertainty estimation and multispectral reasoning rolled into a single framework. This study introduces HUE-Net—a Human-centric, Uncertainty-aware, Event-fused Network—designed specifically to thrive under severe environmental stress. HUE-Net marries the visible RGB band with near-infrared (NIR) imagery and high-temporal-event data through an early-fusion pipeline, proven more responsive than serial approaches. A custom hybrid backbone that couples convolutional networks with transformers keeps the model nimble enough for edge devices. Central to the architecture is the perturbed multi-branch variational module, which distills probabilistic identity embeddings while delivering calibrated confidence scores. Complementing this, an Adaptive Spectral Attention mechanism dynamically reweights each stream to amplify the most reliable facial features in real time. Unlike previous efforts that compartmentalize uncertainty handling, spectral blending, or computational thrift, HUE-Net unites all three in a lightweight package. Benchmarks on the IJB-C and N-SpectralFace datasets illustrate that the system not only secures state-of-the-art accuracy but also exhibits unmatched spectral robustness and reliable probability calibration. The results indicate that HUE-Net is well-positioned for forensic missions and humanitarian scenarios where trustworthy identification cannot be deferred. Full article

Introduction: Humanitarian Corridors are part of Protected Entry Procedures (PEPs), which allow for the safe and legal arrival in Europe of refugees in need of protection (art. 25 of Regulation (CE) n.810/2009) and were implemented for the first time in Italy in 2015. They represent an alternative to dangerous journeys, and they also bring benefits to local communities. The National Institute for Health, Migration and Poverty (NIHMP) represents the first filter at entry with regard to health needs, as it guarantees an overall individual health assessment to verify the possible presence of ongoing infectious pathologies and of issues that may require management and medical investigation. The aim of this study is to expose the organizational activity and analyze the sociodemographic and health data relating to the Humanitarian Corridors implemented in Italy and in which the NIHMP has participated from 2018 to 2024. Materials and Methods: The organizational lists and health data of each corridor were collected. The analysis was carried out in relation to trend, sociodemographic characteristics of the sample, identification, reception and health. The p-value was considered statistically significant if less than 0.01. In all cases in which the p-value was found to be statistically significant, Cramer’s V was calculated to evaluate the strength of the individual correlation. Results: The NIHMP has participated in 14 Humanitarian Corridors, allowing 1250 refugees to enter Italy; a total of 174 unaccompanied foreign minors (UFMs) arrived, and there were 451 refugees reported as vulnerable (36.1%). Contagious infectious conditions were identified in 223 refugees (17.8%), and other health findings were identified in 414 refugees (33.1%). In the analysis by sex, there are statistically significant differences in the reports of vulnerability and in nationality and education. The inferential analysis carried out by age groups presents statistically significant differences in the reports of vulnerability and in sex and nationality. The analysis relating to the differences by nationality shows statistically significant results in the individual corridors in the reports of vulnerability and in schooling, skin manifestations and infectious diseases and the presence of other health findings. Conclusions: The data reported and analyzed in this work can be considered the first attempt at a complete and detailed analysis regarding the actual implementation and effectiveness of Humanitarian Corridors as programs for legal and safe entry into Italy. The significant gap in research is the reason why there are characteristics of our sample that have no counterpart in the literature. Despite this, for other characteristics, it is possible to find statistical significance and scientific value in line with the data reported both on the websites dedicated to the topic and on the limited scientific literature on the subject. Full article

Every minute, vast amounts of video and image data are uploaded worldwide to the internet and social media platforms, creating a rich visual archive of human experiences—from weddings and family gatherings to significant historical events such as war crimes and humanitarian crises. When properly analyzed, this multimodal data holds immense potential for reconstructing important events and verifying information. However, challenges arise when images and videos lack complete annotations, making manual examination inefficient and time-consuming. To address this, we propose a novel event-based focal visual content text attention (EFVCTA) framework for automated past event retrieval using visual question answering (VQA) techniques. Our approach integrates a Long Short-Term Memory (LSTM) model with convolutional non-linearity and an adaptive attention mechanism to efficiently identify and retrieve relevant visual evidence alongside precise answers. The model is designed with robust weight initialization, regularization, and optimization strategies and is evaluated on the Common Objects in Context (COCO) dataset. The results demonstrate that EFVCTA achieves the highest performance across all metrics (88.7% accuracy, 86.5% F1-score, 84.9% mAP), outperforming state-of-the-art baselines. The EFVCTA framework demonstrates promising results for retrieving information about past events captured in images and videos and can be effectively applied to scenarios such as documenting training programs, workshops, conferences, and social gatherings in academic institutions Full article

The frequent occurrence of natural disasters creates a symmetry-breaking scenario between pre-disaster planning and post-disaster rescue operations, such as post-disaster supply–demand mismatches for materials and the risk of potential facility failures. Thus, we propose a dual-uncertainty multi-scenario multi-period facility location allocation model for humanitarian rescue. The model employs two polyhedral uncertainty sets to represent facility failure risks and demand uncertainty at disaster points. Moreover, by constructing diverse disaster scenarios, it simulates material distribution schemes across different relief periods, enhancing its realism. Given that the model integrates three subproblems—facility location, supply–demand matching analysis, and emergency material allocation—we design a hybrid algorithm (DCSA-MA) that combines the discrete crow search algorithm (DCSA) and the material allocation (MA) method for its solution. Experimental results demonstrate that the model maintains a relatively high material satisfaction rate even under significant demand fluctuations. The number of facility failures has a direct bearing on emergency rescue effectiveness. The DCSA-MA method achieves a superior material satisfaction rate compared to other algorithms across various disaster scenarios and multiple rescue periods. Furthermore, DCSA-MA outperforms other algorithms in terms of solution quality, convergence, computational time, and stability. These findings indicate that DCSA-MA is an effective and highly stable approach. Full article

In the Asia–Pacific, where rice is an essential crop for food security and economic activity, tropical cyclones and consecutive floods can cause substantial damage to rice fields. Humanitarian organizations have developed impact-based forecasting models to be able to trigger early actions before floods arrive. In this study we show how Sentinel-1 SAR data and Otsu thresholding can be used to estimate flooding and damage caused to rice fields, using the case study of tropical storm Talas (2017). The current most accurate global Digital Elevation Model FABDEM was used to derive flood depths. Subsequently, rice yield loss curves and rice field maps were used to estimate economic damage. Our analysis results in a total of 475 km² of inundated rice fields in seven Northern Vietnam provinces. Flood depths were mostly shallow, with 2 km² having a flood depth of more than 0.5 m. Using these flood extent and depth values with rice damage curves results in lower damage values than the ones based on ground reporting, indicating a likely underestimation of flood depth. However, this study demonstrates that Sentinel-1-derived flood maps with the high-resolution DEM can deliver rapid damage estimates, also for those areas where there is no ground-based reporting of rice damage, showing its potential to be used in impact-based forecasting model training. Full article

This study explores the impact of DW’s news coverage on the perceptions, knowledge, and behavioural changes of the Syrian diaspora in Germany regarding the Syrian crisis. Grounded in the Uses and Gratifications theory, data were collected from 207 Syrian immigrants residing in Germany between September and November 2023 using a convenience sampling approach. The findings reveal that DW is perceived as a credible and objective news source that provides comprehensive and balanced coverage of the Syrian crisis. Exposure to DW’s reporting significantly enhanced respondents’ understanding of the crisis, enabling them to engage in informed discussions. DW’s coverage motivated behavioural changes, encouraging participation in social media discussions and humanitarian initiatives. This study highlights the critical role of trusted international media in shaping diaspora communities’ perceptions, knowledge, and actions during crises. These findings also highlight DW’s influence as a key information source for the Syrian diaspora, fostering both awareness and proactive engagement with the ongoing crisis. Full article

Background/Objectives: Non-Communicable Diseases (NCDs) place an excessive strain on health systems in disaster-affected settings and may lead to a parallel public health emergency lasting months or years after a disaster. Although NCDs are increasingly recognized as a major challenge in disasters and humanitarian emergencies, a dedicated and standardized response plan is missing, as well as a shortage of evidence-based guidelines for NCD management in theses contexts. Over the years, Emergency Medical Teams (EMTs) have traditionally been deployed to manage acute conditions such as trauma and infectious diseases that quickly impact health systems. However, greater attention is needed to address acute exacerbation of NCDs and to ensure continuity of care for people with chronic health needs in disasters and emergencies. Methods: We conducted a scoping review exploring the EMTs’ management of chronic NCDs during disasters and humanitarian emergencies, in order to identify the strategies adopted, the challenges faced, and the recommendations provided to address this health problem. The online databases PubMed, Scopus, and EBSCO were searched to identify relevant papers. Results: After screening the papers against the eligibility criteria, 17 publications were retrieved. Five different areas of intervention concerning EMTs and NCDs management were identified: (i) EMTs pre-departure preparation, operational time, and length of stay; (ii) EMTs staff composition and training; (iii) EMTs logistics; (iv) EMTs integration with local health services; (v) EMTs clinical data record. Conclusions: The findings emerging from this study showed that NCDs significantly impact disaster response in different settings, underlining the need to implement a range of EMTs activities to guarantee assistance for chronic health needs. In view of strengthening the ability of health systems to cope with the NCDs’ burden, the EMTs’ initiatives should be considered as a bridge between the support provided during the acute phase of an emergency and the continuation of care ensured by the system in its early recovery phase. Full article

From an outside perspective, it is not clear whether the Catholic Church is an active digital entity, or at least, it is not perceived as such. This paper analyses this issue. The methodology involved the monitoring of ecclesiastical Internet activity, SWOT analysis and in-depth interviews (seven) with clergy and technological suppliers of the Church in both Spain and Latin America. Results: Catholic Church digitalisation is spontaneous, as a reflection of society at large, and is heterogeneous due to its decentralised management. There is more inner acceptance of digital mediatisation for proclamation or support in faith (i.e., apps for praying) and less acceptance for the digitalised practice of rites (digital mediation in the celebration of sacraments is an open debate); however, the presence of ICTs in sacred places is increasing (i.e., liturgical books on screen). The evangelisation of the digital continent is an objective of the Church, whereby clergy influencers are the most striking but less solid case. There is almost full digital implementation at the functional level (i.e., digitised accounting and archives). Only charitable action with vulnerable groups remains analogue. Polarisation is also present, as ultra-Catholic groups are over-represented on the Internet. Conclusion: The Catholic Church is integrated in the Information and Digital Age but is also concerned with spiritual impoverishment, as online fragmentation does not feed real humanitarian communities. Full article