Abstract:

Air pollution poses a significant health risk worldwide, with mortality rates from ambient particulate matter pollution increasing in many regions. This study focuses on forecasting air pollution-related mortality rates in two Central Asian cities, Bishkek (Kyrgyzstan) and Almaty (Kazakhstan). Utilizing time-series models, specifically Long Short-Term Memory (LSTM) networks and Prophet, the research aims to provide accurate predictions that can inform public health policies and interventions. The proposed methodology integrates advanced data preprocessing techniques, robust model architectures, and hyperparameter tuning to achieve an accuracy exceeding 85%. The findings reveal that time-series forecasting can effectively model the trend and seasonality of mortality rates, offering actionable insights for policymakers.

Abstract: Background: The time lapse between the acute event and the beginning of rehabilitation seems to play a significant role in determining the effectiveness of rehabilitation together with the severity of neurological deficits and impairment of motor and cognitive functions. The present study aims to further explore the prognostic role of cognitive and motor functions, concerning the different times of the beginning of neurorehabilitation. Methods: A secondary examination was conducted by applying a cluster analysis on the data of 386 stroke patients in the subacute phase who were enrolled in the Cognitive and Recovery of Motor Functions (CogniReMo) study. Results: Barthel Index at the admission predicts clinical outcome: if BI was 0 it was on average 28.7±24.1 at discharge. For patients with Barthel Index <15 at discharge, the discriminant was unaltered executive functions to have an average output of 61.3 instead of 45.5. In the range of BI at admission between 16 and 45 the discriminant variable was to have a NIHSS≤5 to obtain a high outcome (BI=75.4 instead of BI=61.9). Subjects with a BI at admission >45 were the best responders to rehabilitation, with a mean BI at discharge of 85 if they have alteration in spatial attention, and 95.3 if they have no deficits in spatial attention. Also, for in-patients hospitalized in a period ranging from the 20th to the 37th day after stroke, spatial attention was a discriminant variable to have a poor outcome (BI=34.3) vs. a good one (BI=76.7). Conclusions: the algorithm identified a hierarchical decision tree that might assume a significant role for clinicians in defining an appropriate rehabilitation pathway, depending on the time of rehabilitation beginning and the severity of motor and cognitive deficits.

Abstract:

Antimicrobial resistance (AMR) remains a persistent world-wide health concern. Poultry production in Nigeria has become a large-scale venture and is largely characterised by intensive management system. This intensive management system disposes to more antibiotic use and thus a greater risk of AMR. Previous reviews on AMR data in Nigeria have not considered the accuracy of methods and interpretation criteria. Therefore, in contribution to the “One Health” AMR Surveillance system, which is one of the five focus areas described by the Nigeria action plan on AMR control, this comprehensive review collates, curate, and analyse AMR published data in the Nigeria poultry sector and assessed the AST methods and interpretation criteria. A search of AMR reports from poultry in Nigeria prior to 2020 after screening for relevance yielded 69 studies from 2005-2020 with 91 AMR reports (some studies reported more than one organism). From these studies we reviewed the organisms reported, antibiotics tested, resistance to tested antibiotics, distribution of reports within the country’s geopolitical zones, multidrug resistance pattern, the inclusion or absence of control strains in antimicrobial testing, the antimicrobial testing method and interpretative criteria used.There was no AMR study in poultry earlier than 2005 in Nigeria, highest number of study was in 2019 (n=12). South-Western region has the highest number (n = 27) of study and the North-Western region has the lowest (n = 5). Organisms mostly reported were Salmonella, 31%, Escherichia coli, 26% and Staphylococcus aureus, 15%). Other organisms (≤5%) were Campylobacter, Klebsiella, Bacillus, Listeria, Enterobacter, Proteus, Norcardia, Streptococcus, Alkaligenes, Shigella, Micrococcus, Enterococcus, Ochrobacturm, and Yersinia. The antimicrobial susceptibility testing (AST) method mostly used was disc diffusion (80%), also majority (95.7%) of the studies used the CLSI standards for interpretation and 79.7% of the studies did not mention the use of control strains for AST. The 69 studies reviewed tested 69 antimicrobials belonging to 17 classes of Antibiotics; the most tested classes of antimicrobial were β-lactams (33%), quinolones (21%) and aminoglycosides (15.4%). All of the organisms showed varying multi-drug resistance; greater proportion (50-100%) has MAR Index greater than 0.2. The review of the various studies showed very high multi-drug resistance among the various organisms of poultry origin and also a gap in AST carried out in Nigeria. We therefore recommend that AST research methods must be of global standard and additional efforts should be made towards education of the general public on best practices of antibiotics usage and the dangers of AMR.

Abstract: Breastfeeding in Syria is fraught with many challenges due to the ongoing war. In Hungary, recent statistics show that exclusive breastfeeding is significantly lower than the recommendation of the World Health Organization. Understanding the perspectives of educated young ladies is crucial for discovering the difficulties of breastfeeding practices within Syrian and Hungarian societies. This study explores the socio-cultural factors and their impact on breastfeeding behaviours among female students in Syria and Hungary. A comprehensive, multi-section questionnaire was administered to 317 students from Damascus University and 303 from Hungarian universities, designed to assess breastfeeding behaviours evaluated through The Breastfeeding Behaviour Questionnaire (BBQ). The results in both societies showed remarkable awareness and understanding among participants regarding breastfeeding. Traditions and religion affect Syrian society more than Hungarian society; the two societies have restricted responses toward breastfeeding in public and different reactions to breastfeeding in front of males or females. Most students disagree with preferring formula feeding to breastfeeding when it is related to the family or the husband’s desire only. At the same time, agreement with choosing the bottle when the mother returns to work instead of exclusively breastfeeding is valued differently in the two societies. This study shows essential socio-cultural factors influencing breastfeeding attitudes among Syrian and Hungarian female students, highlighting the need for culturally suitable strategies to improve breastfeeding practices in both countries.

Abstract: Subjective suffering due to oral diseases and disorders has been conceptualized as oral health-related quality of life and is often assessed with a multidimensional version of the Oral Health Impact Profile (OHIP). In the current study, a secondary analysis of a Dutch-language translated version of the original OHIP-14 was performed in different samples of approximately 1000 participants from diverse contexts (i.e., the Netherlands, the Caribbean, and Nepal). The dimensional structure and reliability of the scales resulting from these analyses were also examined. Based on a number of Confirmatory Factor Analyses (CFA) and Simultaneous Components Analysis (SCA) of the OHIP-14 scale, testing various models with different numbers of factors, several models were acceptable, but a two-factor solution, comprising psychological discomfort and physical discomfort was the most satisfactory in all three samples although a one-factor solution, oral discomfort was also acceptable. Instead of using a large number of dimensions with few items each, as often is done, it is most adequate and feasible to use no more than two scales, i.e., psychological discomfort and physical discomfort, comprising 11 items in total. These subscales of 6 and respectively, 5 items are not only statistically, but also theoretically the most adequate. Additionally, all items together, i.e., oral discomfort as a one-dimensional scale are useful and easy to apply for practical use.

Abstract: This paper introduces a novel Dynamic Access Decision Scoring (ADS) framework that integrates cognitive computing and big data to address emerging challenges in controlling access to healthcare data systems. Traditional rule-based access control mechanisms lack the cognitive capabilities to process dynamic security requirements, creating vulnerabilities when managing large-scale electronic health records (EHRs). Our framework leverages cognitive computing by combining machine learning algorithms, behavioral pattern analysis, and real-time data analytics to create an intelligent security system that safeguards sensitive medical data while maintaining computational efficiency. The core innovation lies in developing a cognitive mathematical template that data scientists and researchers can adapt through deep learning and analytical processing. The framework introduces a modular formula as an adaptive cognitive pattern, incorporating four computational elements: machine learning predictions, historical pattern recognition, risk analytics, and temporal context processing. Each element employs cognitive algorithms that security architects can calibrate within their specific data ecosystems. The framework’s primary contribution demonstrates how cognitive probabilistic approaches can dynamically adapt to complex healthcare environments. This research advances big data security by establishing a cognitive computing foundation for making access control decisions, effectively bridging theoretical data models with practical machine intelligence implementation in healthcare information systems.

Abstract:

In this case study, we describe and document how Baltimore City Public Schools (BCPS), an urban K–12 public school system, implemented COVID-19 mitigation measures guided by a Public Health Advisory Committee, as well federal and state guidance. BCPS comprises more than 160 public schools, and offers education and social safety services to a population of almost 76,000 students. Throughout the 2020–2023 academic years, BCPS worked with a Public Health Advisory Committee to establish comprehensive COVID-19 transmission mitigation measures, using federal and state pandemic-related funding meant to reduce COVID-19 prevalence among students, faculty, and staff. The school system’s processes of determining and establishing these mitigation measures over the three academic years provides valuable information and lessons for preparing schools in the event of future health emergencies or pandemics, particularly related to decision-making processes, and student/parent communications.

Abstract: Background: Geographic Information Systems, or GIS, play a pivotal role in the study of Per- and Polyfluoroalkyl Substances, or PFAS. By focusing on their environmental distribution and pathways, GIS significantly contributes to understanding the sources of PFAS exposure. This method is instrumental in environmental risk assessment and developing effective management strategies.Objective: To geolocate PFAS sites in a map and perform proximity analysis around these sites. Methods: This was a cross-sectional study. Each PFAS site address was geocoded. We measured proximity using the Kriging interpolation method with each census tract centroid. Additionally, each site had a 1-mile buffer (exposure risk). Results: We geocoded nineteen industrial sites, twenty-nine military sites, and one wastewater management site. By empirical Bayesian kriging, a smoothed map showing proximity ranges from 200 to 2000 meters around the PFAS sites. A one-mile proximity buffer map covered the entire study area. Conclusion: This study’s findings underscore the urgent need for action. Using GIS in decision-making, we can allocate resources and prioritize interventions based on risk and vulnerability. The study highlights potential contamination in residential areas, public water supplies, public parks, and high-density population areas.

Abstract:

Virtual reality (VR) demonstrates significant potential to improve rehabilitation outcomes for musculoskeletal conditions and chronic pain. However, the field faces notable challenges, including inconsistent terminology, a lack of specialized/comprehensive software solutions, and an overwhelming variety of hardware options, which can make it difficult for healthcare professionals without technical expertise to identify the most suitable tools for clinical use. This article explores the current state of VR in the rehabilitation of musculoskeletal conditions and chronic pain, focusing on terminology discrepancies, available hardware and software solutions, and key professional associations shaping the field. A review of the current state of terminology is essential to address inconsistencies that risk perpetuating misuse and limiting the applicability of research findings. Building on this review, we propose a conceptual framework for understanding VR that aligns more closely with the capabilities of current VR technology. A comprehensive overview of VR hardware and software can assist healthcare professionals in selecting appropriate technologies for clinical practice, guide researchers in designing interventions, and inform developers on unmet needs in the field. Furthermore, understanding key professional associations provides valuable direction for those engaged in virtual rehabilitation, enabling them to access resources, foster collaboration, and stay informed about the latest advancements in the domain.

Abstract:

Background/Objectives: The uneven distribution of nurses in Albania is a major problem that compromises equitable access to health services. Rural and less developed regions suffer from a chronic shortage of nursing staff, while urban areas attract the health professionals. This study aims to quantify the inequalities in the distribution of nurses in Albania, analyzing the nurse-to-population ratio and its impact on the quality of health care. The main objective of this study is to examine the distribution of the nursing workforce in Albania and assess regional disparities, using the Gini coefficient and the Human Development Index (HDI) to measure and compare inequalities between regions. Methods: This descriptive-analytical study was conducted in 2024. The data was collected from official sources, including the Albanian Ministry of Health and the World Health Organization (WHO). The Gini coefficient and the Lorenz curve were used to analyze the distribution of nurses in relation to the population and HDI of the different regions. The analysis included data on the number of nurses, population and regional socioeconomic conditions. Results: The average nurse-to-population ratio in Albania is 28 nurses per 10,000 inhabitants, with significant variations between regions. Tirana has the highest ratio (60 nurses per 10,000 inhabitants), while Kukës and Dibër have the lowest values (10 per 10,000 inhabitants). The calculated Gini coefficient is 0.0228, indicating a very low level of inequality in the distribution of the nursing workforce. Conclusions: Inequalities in the distribution of nurses in Albania require targeted policy interventions. Policies are needed that incentivize health workers to work in less developed regions, through economic incentives, infrastructure improvements and lifelong learning programs. These interventions are essential to reduce disparities and ensure equitable access to health services across the country.