This dataset compiles attacks on energy infrastructure in Nigeria between 2009 and 2025. It integrates geospatially attributed incident-level data with aggregated estimates of physical and economic losses. The dataset covers deliberate disruptions to oil and gas infrastructure and electricity transmission systems across Nigeria's six geopolitical zones. It consists of two complementary components. The first is a geo-referenced incident data (2011-2025) consisting of 161 recorded attacks, with information on date, location, actor type, targeted asset, and attack method. The second is an annual volume-value dataset (2009-2025) reporting crude oil losses and associated revenue estimates resulting from pipeline vandalism, crude theft, and spill events. Data were compiled from verified open sources, including the Nigeria Security Tracker (Council for Foreign Relations), domestic and international media reports, and industry and regulatory publications. These data were processed using reproducible filtering and classification scripts. Together, these datasets enable quantitative assessment of the physical scale and economic implications of crude oil theft in Nigeria. They also support comparative, temporal, and scenario-based analyses across research, policy, and public-interest applications. All data and supporting files are openly available in a Zenodo repository.
A scientometric analysis of 3166 publications in the journals of the peer-reviewed Higher Attestation Commission on forensic medicine over a 20-year period (2005-2024) was performed using pubmed resources, mediasphera.ru, open sources. A search, sorting, and grouping of articles has been carried out that reflect topical issues of forensic medical assessment of defects (deficiencies) in the provision of medical care with a detailed analysis of publications regarding the inadequate provision of medical care in obstetrics and gynecology. Выполнен наукометрический анализ 3166 публикаций в журналах, рецензируемых ВАК, по судебной медицине за 20-летний период (2005—2024 гг.) с ресурсов PubMed, mediasphera.ru, открытых источников. Осуществлен поиск, сортировка, группировка статей, в которых отражены актуальные вопросы судебно-медицинской оценки дефектов (недостатков) оказания медицинской помощи, с подробным анализом публикаций в отношении ненадлежащего оказания медицинской помощи в акушерстве и гинекологии.
In the previous study [1], we showed an increased risk of malignant neoplasms in carriers of the minor allele rs1052133*G of the hOGG1 gene who were affected by chronic radiation exposure at a wide range of doses (up to 3507 mGy to the red bone marrow at the Techa River (Southern Urals). The objective of the present study was to assess the contribution of radiation factor to the risk of malignant neoplasm development in persons chronically exposed at the Techa River. For this purpose, we analyzed the background level of genetically determined risk in the general population of unexposed people on the basis of meta-analysis of the world literature data on the search for the association of rs1052133 of the hOGG1 gene with the risk of malignant neoplasm development. At the final stage, the results of the meta-analysis were compared with data on exposed people. The study found that unexposed and exposed carriers of the rs1052133*G allele had a comparable increased risk of developing malignant neoplasms, odds ratio OR = 1.20; 95% confidence interval [1.06-1.35], p = 0.01 and odds ratio OR = 1.38; 95% confidence interval [1.05-1.83], p = 0.023, respectively.
BACKGROUND: This study examines gender representation across the academic anatomy pipeline in Türkiye, from graduate education and thesis authorship to academic faculty ranks, and aims to identify where gender disparities emerge. METHODS: Data were obtained from three national open-access sources: annual reports on the numbers of master’s and doctoral students in anatomy programs (2015–2025), all anatomy theses published between 1969–2024, and the distribution of academic staff in anatomy departments as of March 2025. Gender was classified using publicly available institutional and academic profiles. These datasets were examined comparatively to map longitudinal patterns from training to senior academic ranks. RESULTS: A total of 1,657 theses were included; women accounted for 57.2% of authors, and their proportion increased from 42.9% in early decades to 64.8% in 2020–2024 (p<0.001). Between 2015–2025, women’s representation rose from 58.2% to 69.7% in master’s programs and from 40.1% to 54.7% in doctoral programs. Despite strong representation of women at trainee levels, only 31% of professors in 2025 were women, while their representation was markedly higher among research assistants (74.4%) and lecturers (69.6%). Academic rank and gender were significantly associated (p<0.001), indicating progressive attrition of women along the academic pathway. CONCLUSIONS: Although women enter the anatomy field in Türkiye in strong numbers and successfully complete graduate training, this increasing representation does not translate into senior academic positions. These findings show that women’s strong early-stage presence fails to reach senior ranks, exposing both clear leakage and suggesting marked delayed advancement in the academic pipeline.
Emerging and re-emerging infectious diseases continue to pose significant threats to lower-middle-income countries (LMICs), particularly in Africa, where health systems are often resource-constrained and prone to disruptions. Drivers such as climate change, antimicrobial resistance, urbanization, civil war, poverty, globalization of travel, and high population mobility exacerbate outbreak risk and severity. This paper outlines how LMICs can strengthen health system resilience and respond more effectively to such threats by adopting practical tools and frameworks offered by the WHO Hub for Emergency Preparedness and Pandemic and Epidemic Intelligence. Key initiatives, including Epidemic Intelligence from Open Sources (EIOS), the International Pathogen Surveillance Network (IPSN), and Public Health Intelligence (PHI) capacity-building, support early detection, genomic surveillance, and data-driven decision-making. We highlight practical strategies for LMICs, including integration of Hub outputs into national policy, sustainable financing, workforce development, institutional strengthening, regional collaboration, and monitoring and evaluation. While challenges such as infrastructure gaps, data governance, and reliance on external funding remain, the WHO Hub provides a structured pathway for LMICs to enhance outbreak preparedness, reduce response times, and mitigate the impact of future epidemics. Not aplicable.
Background/Objectives: Health system socio-economic inequities in dental care are a long-standing problem in Europe. The issue gained increased relevance during the recent pandemic due to service disruption and socio-economic inequities that become even more pronounced under such circumstances. However, while preventive dental programs are considered key elements of public health, little is known about their role in addressing equity in accessing dental care among different countries and over time between them. This research aims at investigating the relationship between preventive dental policy, socio-economic factors, and the inability to get appropriate dental care within EU member states. Methods: A longitudinal panel dataset at the country level, consisting of data collected during 2020 through 2024, was assembled using open sources of statistics from Europe and other international statistical databases. The dependent variable used in the study was the percentage of the population that had unmet dental care need because of cost. Independent variables were the presence or absence of preventive policies related to dentistry, educational attainment, gross domestic product per capita, unemployment rate, number of dentists, and out-of-pocket expenses. Balanced panel datasets and regressions with robust standard errors in random-effects models were estimated. Interaction terms were created to test the moderating effect of education level on the relationship between policies and access to care. Results: Cross-country variations in terms of the prevention policy environment, socio-economic status, and unmet dental care need were found from descriptive analysis. The higher level of out-of-pocket payment was always related to the higher unmet dental care need, while the lower GDP countries displayed poorer access. Using the balanced panel random-effects model, preventive dental policies and the interaction between preventive policies and educational level were insignificant factors predicting the unmet dental care need. On the other hand, higher out-of-pocket payments, education, and dentists per million population had nearly significant positive relationships. In the sensitivity analysis, GDP per capita showed a negative association, whereas dentists per million population remained positively associated with unmet dental care need. Conclusions: The findings suggest that inequalities in access to dental care during and after the COVID-19 period were shaped primarily by financial and structural determinants rather than by the presence of preventive policies alone. While preventive programs remain an important component of long-term oral health strategies, reducing direct household payment burden and strengthening health system capacity may represent more immediate mechanisms for maintaining equitable access to dental services during periods of system disruption.
Background/Objectives: To estimate, against the background of the upcoming German healthcare reform, current access to neurosurgery for patients in Germany, and to derive improvement strategies from geographic information mapping. Methods: We defined access to neurosurgery on a geographical basis as the sum of all points from which one can reach a neurosurgical department within 40 min by car (A2N40). We identified 182 departments of neurosurgery, and we retrieved population numbers and geodetic information from open sources. We processed data and conducted statistical analyses in R. Results: Population density and A2N40 per square kilometer were significantly positively correlated (Spearman's rho = 0.82, p = 0.0001). Population density is significantly lower (Wilcoxon rank sum test, p = 0.009) and A2N40 per square kilometer is significantly worse (Wilcoxon rank sum test, p = 0.005) in the new federal states (without Berlin) as compared to the rest of the country. Geographic information mapping yielded 3 distinct improvement strategies. Conclusions: In Germany, population density and A2N40 per square kilometer are significantly positively correlated, with significantly less A2N40 per square kilometer in the new federal states. Geographic mapping may inform tailored regional improvement policies.
Aim: To investigate approaches to the criminal legal qualification of collaborationism in the field of healthcare, taking into account the norms of international humanitarian law. Materials and Methods: The research methodology involves an analysis of current legislative documents on the qualification of criminal liability for collaborative activities, as well as regulatory legal acts in the healthcare field, and documents of international humanitarian law. The data analysis was conducted using open sources, mainly for the period 2013-2025, with an emphasis on the period of the active phase of the war in Ukraine. The main search keywords were "human rights", "collaborationism", "criminal liability", "crimes against the foundations of national security", "medical immunity in international humanitarian law", and "healthcare". The initial database consisted of 70 sources, of which 34 were included in the final analysis. The materials of the publication form the basis for the systematization of criminal legislation on the problems of protecting the rights of persons accused of collaborative activities in the field of healthcare, the key ones being the Constitution of Ukraine, the Criminal Code of Ukraine, and the European Convention on Human Rights. Conclusions: The study emphasizes the need to improve the approach to the criminal legal qualification of collaborationism in the health sector, which covers both legal and organizational components, as well as mandatory compliance with the norms of international humanitarian law. The social danger of this phenomenon lies not only in the fact that it encroaches on the defense capability and foundations of national security, but also in the fact that it poses a threat to other objects of criminal law protection.
The reliable and continuous acquisition of seismic data from multiple open sources is essential for real-time monitoring, hazard assessment, and early-warning systems. However, the heterogeneity among existing data providers such as the United States Geological Survey, the European-Mediterranean Seismological Centre, and the Spanish National Geographic Institute creates significant challenges due to differences in formats, update frequencies, and access methods. To overcome these limitations, this paper presents a modular and automated framework for the scheduled near-real-time ingestion of global seismic data using open APIs and semi-structured web data. The system, implemented using a Docker-based architecture, automatically retrieves, harmonizes, and stores seismic information from heterogeneous sources at regular intervals using a cron-based scheduler. Data are standardized into a unified schema, validated to remove duplicates, and persisted in a relational database for downstream analytics and visualization. The proposed framework adheres to the FAIR data principles by ensuring that all seismic events are uniquely identifiable, source-traceable, and stored in interoperable formats. Its lightweight and containerized design enables deployment as a microservice within emerging data spaces and open environmental data infrastructures. Experimental validation was conducted using a two-phase evaluation. This evaluation consisted of a high-frequency 24 h stress test and a subsequent seven-day continuous deployment under steady-state conditions. The system maintained stable operation with 100% availability across all sources, successfully integrating 4533 newly published seismic events during the seven-day period and identifying 595 duplicated detections across providers. These results demonstrate that the framework provides a robust foundation for the automated integration of multi-source seismic catalogs. This integration supports the construction of more comprehensive and globally accessible earthquake datasets for research and near-real-time applications. By enabling automated and interoperable integration of seismic information from diverse providers, this approach supports the construction of more comprehensive and globally accessible earthquake catalogs, strengthening data-driven research and situational awareness across regions and institutions worldwide.
Aim: To investigate the negative and positive obligations of the state in ensuring the right of an individual to respect for human dignity in medical and legal relations, taking into account the practice of the European Court of Human Rights, and to reveal the protection of this right among drug addicts. Materials and Methods: The research methodology involves the analysis of national regulatory provisions, international treaties, legislative acts of Ukraine, and legal positions of the ECHR on the problems of implementing the right to respect for human dignity in medical and legal relations, as well as the case law of the European Court of Human Rights. Data analysis was conducted using open sources, mainly for the period 2010-2025. The main search keywords were "ECHR", "protection of rights", "health care", "legal regulation", "the right of an individual to respect for human dignity". The search criteria focused on modern scientific approaches and practical experience in ensuring the right of individuals to respect for human dignity in medical and legal relations. Sources that do not focus on medical-legal relations, that do not take into account the current practice of the ECHR, that do not comply with international human rights standards, legal acts or regulatory documents that contradict the practice of the ECHR were excluded from consideration. Conclusions: The study highlights cases of failure to fulfill negative obligations of a material nature of the studied right of individuals, among which the following are identified: improper performance by officials of their duties due to inaction (failure to provide medical services, which led to serious consequences); improper performance of official duties by officials of state bodies, as well as unlawful actions of law enforcement agencies of a deliberate nature (physical and psychological violence against persons in custody). An approach is proposed in which adherence to the principle of the supremacy of the law under study, taking into account the practice of the European Court of Human Rights, is the basis for respecting human rights and freedoms.
BACKGROUNDPublic Health Intelligence (PHI) aims to detect health threats early for a timely and effective response. The PHI team at the Robert Koch Institute (RKI) uses the Epidemic Intelligence from Open Sources (EIOS) system in combination with other sources for detecting signals of international public health threats relevant to Germany. However, while EIOS is increasingly used for PHI worldwide, it is rarely evaluated.AIMWe designed and conducted an attribute-based evaluation to assess EIOS's performance for international PHI in 2023 and to identify areas for improvement.METHODSWe adapted surveillance system attributes and designed attribute-specific data collection methods. We conducted a mixed-method evaluation combining prospective and retrospective operational data collection with feedback from PHI officers.RESULTSDuring 2 weeks in July 2023, the PHI team reported 20 signals: 16 detected using EIOS and four from other sources. Increasing the number of EIOS sources increased timeliness and sensitivity slightly but caused a 35-fold increase in articles to screen (35,546 vs 1,138). The team found EIOS flexible and simple for signal detection but identified challenges in simplicity of signal documenting and reporting and in completeness of EIOS sources screened by the team.CONCLUSIONThe current use of EIOS proved sensitive and timely. However, PHI must balance sensitivity, timeliness and resource requirements. To maintain this balance, we strongly recommend regular evaluations of the use of EIOS for PHI. Our evaluation offers practical guidance for other PHI teams. We recommend integrating EIOS with an event management system to facilitate signal documentation and reporting.
BACKGROUND: Leptospirosis remains a major public health concern in Sri Lanka, a country with a tropical climate conducive to transmission. Despite ongoing surveillance, there is limited evidence on the spatial and climatic determinants driving long-term disease dynamics. This study aimed to investigate the spatiotemporal distribution and climatic sensitivity of leptospirosis from 2009 to 2024 using advanced statistical modelling. METHODS: District-level monthly leptospirosis case data for the period 2009–2024 were obtained from the Epidemiology Unit of the Ministry of Health, Sri Lanka. Corresponding monthly district-level climatic variables, including total rainfall, mean temperature, minimum temperature, maximum temperature, and mean relative humidity, were retrieved from the NASA POWER satellite dataset. Associations between climatic variables and leptospirosis incidence, as well as spatial heterogeneity in case distribution, were assessed using a Generalized Additive Model for Location, Scale, and Shape with a Zero-Adjusted Gamma distribution, while spatial clustering and autocorrelation were examined using Moran’s I. RESULTS: A total of 81,629 confirmed cases of leptospirosis were recorded during the study period. The ZAGA-GAMLSS model identified several climatic, spatial, and temporal predictors that were significantly associated with district-level incidence. Relative humidity and maximum temperature showed immediate negative associations with incidence, while humidity, mean temperature, and rainfall demonstrated positive lag-dependent effects at 1–3 months. In contrast, maximum and minimum temperatures exhibited predominantly negative association at 3-month lag. Spatial heterogeneity was evident in both incidence rates and zero-inflation, and temporal dependence was detected at 1 and 12-month lags. Higher relative humidity three months earlier was linked to more stable leptospirosis incidence rates across districts. Spatial analysis further revealed significant clustering, with hotspots identified in the districts of Ratnapura, Galle, Matara, and Hambantota, while Colombo was identified as a spatial outlier. CONCLUSIONS: Leptospirosis in Sri Lanka exhibits distinct spatiotemporal patterns influenced by climatic variability, with elevated risk following monsoon rains in the south‑western part of the country. Climate‑sensitive modelling, as demonstrated in this study, supports the integration of meteorological surveillance into early warning and response systems to enhance leptospirosis control, particularly in identified hotspot regions.
Diverse tree communities can bolster urban ecosystem resilience and provide vital ecosystem services. However, existing urban tree species datasets have limited geographic coverage and contain inadequate attributes. To address those gaps, we developed the Global Urban Tree Species (GUTS) dataset by integrating data from literature, biodiversity databases, and other open sources. The new dataset encompasses 159,845 occurrence records of 10,094 tree species in 8,349 cities and 139 countries. Among them, 109,879 records were confirmed from urban areas, representing 11.18% of global tree species diversity. The dataset has been validated using multiple methods. GUTS fills critical data gaps and provides a foundation for future research and management of global urban biodiversity.
Agricultural greenhouse gas emissions on the planet threaten both food security and climate change. The United Nations is calling for food security and sustainable agriculture to end hunger by 2030. Sustainable Development Goal 2.4 addresses resilient agricultural practices to combat climate change and produce sustainable food. Resilient agricultural practices are only possible with agricultural technologies (AgriTech) that will create a digital transformation in agriculture. AgriTech can meet the increasing food demand by increasing production efficiency while increasing resource efficiency by combating problems such as climate change and water scarcity. The aim of this study is to examine the impacts of AgriTech usage on sustainable agriculture in Sub-Saharan African (SSA) countries. The analyses were conducted using panel data from 20 SSA countries between 2000 and 2022. In this study, MMQR (Method of Moments Quantile Regression) provided consistent results across quantiles in variable interactions, while GMM (Generalized Method of Moments) and KRLS (Kernel Regularized Least Squares Method) approaches were used to ensure consistency of results. The findings confirm that AgriTech (ATECH) and agricultural value added (AGRW) contribute significantly to sustainable agriculture in SSA countries. The coefficients of ATECH and AGRW variables are negative and statistically significant in all quantiles. This shows that when AgriTech use and agricultural value added increase in SSA, emissions from agriculture decrease and the environment improves. However, agricultural credits (ACRD) are insufficient to reduce agricultural emissions. Furthermore, agricultural workers (AEMP) and internet use (INT) help reduce agricultural emissions up to the 60th and 50th quantiles, while this effect disappears at higher quantile levels. These results emphasize the importance of integrating green procurement and green production technologies supported by green credits into agricultural production in order to achieve sustainable agricultural development goals in SSA. Policies that facilitate farmers' access to agricultural green credits should be adopted in SSA societies. Infrastructure works that will increase farmers' access to the internet should be increased. Awareness of agricultural workers on green production and sustainability should be provided to agricultural workers.Highlights. The results show that agricultural technologies, agricultural growth, agricultural labor, and internet use reduce agricultural emissions in SSAcountries, while credit use increases agricultural emissions. AgriTech use (ATECH) and agricultural value-added (AGRW) have statistically significant negative coefficients in all quantiles, indicating that increasing AgriTech and value-added reduce agricultural greenhouse gas emissions. The potential of AgriTech to reduce emissions is higher in low-emission quantiles (10-30%), while the effect is relatively weaker in high-emission quantiles. Agricultural credits (ACRD) only provide environmental improvements in the low-emission quantile (25%) and are insufficient to reduce emissions in high quantiles. Agricultural labor (AEMP) and internet use (INT) significantly reduced emissions at 10-50% quantiles, while this effect disappeared at higher quantiles. Farmers' success in reducing emissions is directly dependent on their internet access. Panel instantaneous momentum quantile regression (MMQR) was preferred to capture heterogeneous interactions, and the robustness of the results was confirmed with the GMM and KRLS approaches.
The United Nations considers children a crucial national asset and makes their welfare a top priority. However, infant mortality remains a persistent challenge, notably in Arab nations. Bahrain, Kuwait, and Oman, despite sharing similar income brackets and health care systems, differ in health policies, demographics, and maternal-child resource allocation. These countries also faced sharp fiscal deficits during the 2020 COVID-19 crisis. Compared to wealthier nearby nations like the United Arab Emirates, their lower gross domestic product further complicates efforts to reduce the Infant Mortality Rate (IMR) and sustain effective, equitable child health strategies. This study aimed to identify factors contributing to the IMR in Bahrain, Kuwait, and Oman by establishing an interpretative framework to examine the influence of sociodemographic, macroeconomic, health status and resource, and environmental factors. A longitudinal study collected annual time-series data (1990-2022) for Bahrain, Kuwait, and Oman from international open sources. To counterbalance the time-series effects on both IMR and explanatory factors, a generalized least squares model based on the Cochrane-Orcutt procedure with a first-order autoregressive model was used. Generalized least squares shows that the total fertility rate has a strong effect on IMR among the 3 countries (Oman: β=1.138, P<.001; Kuwait: β=.429, P=.006; Bahrain: β=.610, P=.03). Health status and resources, such as female life expectancy at birth, had an inconsistent impact on the IMR, with a positive effect (β=.103, P=.002) for Oman and a negative effect (β=-4.0697, P<.001) for Kuwait. Macroeconomic factors, such as female unemployment, were significant in decreasing the IMR only for Kuwait (β=-.076, P=.008). Gross domestic product per capita is significant only for Bahrain (β=-.398, P<.001). Environmental factors included CO2 emissions, which negatively impacted Oman's IMR (β=-.077, P=.03), and N2O had a positive effect on Bahrain's IMR (β=.420, P=.04). This study indicated the substantial effects of sociodemographics, health status and resources, macroeconomics, and environment on the IMR in 3 Arab countries. Sociodemographic and health-related factors like female life expectancy, fertility regulation, and female unemployment level were identified as key determinants of infant mortality.
The Electromagnetic Field (EMF) effect is considered an alarming human health issue, dependent on the use of mobile phones. Several nationwide awareness programs on EMF Emissions & Telecom Towers were initiated by the Department of Telecom (DoT) to build a direct bridge between the number of investors and the information gap with scientific evidence. EMF interaction with humans has caused oxidative stress for brain physiological and pathological degeneration. This study aimed to investigate the EMF's influence on oxidative stress and disorders of neurodegenerative. This analytical study is conducted on a generalized linear model, a supervised learning approach in machine learning, to understand mobile tower radiation. The data is obtained from open sources from two different states in India. Confidential Interval (CI) was obtained for measured value radiation for Andhra Pradesh in 2018-2019 as 95% CI [0.0045 to 0.0111] and for 2019-2020 as 95% CI [0.0016 to 0.0028]. Telangana -CI for Measured Value (MV) in 2018-2019 was found to be 95% CI [0.0500 to 0.0763] and 2019-2020 is 95% CI [0.0189 to 0.4345]. Generalized Linear Models (GLM) are the best statistical model to analyze the mobile tower radiation.
Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate among all major cancers due to a lack of symptoms in early stages, early detection tools, and optimal therapies for late-stage patients. Thus, effective and non-invasive diagnostic tests are greatly needed. Recently, circulating miRNAs have been reported to be altered in PDAC. They are promising biomarkers because of stability in the blood, ease of non-invasive detection, and convenient screening methods. This study aimed to use blood-based miRNA biomarkers and various analysis methods in the development of a machine-learning (ML) model for PDAC. Blood-based miRNAs associated with PDAC were collected from open sources. miRNA sequences, targeted genes, and involved pathways were used to construct a set of descriptors for an ML model. Bioinformatics analysis revealed that most genes in pancreatic cancer and insulin signaling pathways were targeted by the PDAC-related miRNAs. The best-performing ML model with the Random Forest classifier was able to achieve an accuracy of 88.4%. Model evaluations of an independent PDAC-associated miRNAs test set had 100% accuracy while non-cancer miRNAs had 52.4% accuracy, indicating specificity to PDAC. Our results suggest an ML model developed using blood-based miRNA biomarkers' target gene, pathway, and sequence features could be potentially implicated in PDAC diagnostics.
Knowing the health opportunity costs of funding decisions is crucial to assess whether the health gains associated with new interventions are larger than the health losses imposed by the displacement of resources. Empirical estimates based on the effect of health spending on health outcomes have been proposed in several countries, including Spain, as a proxy to capture these opportunity costs. However, there is a need to regularly update existing health opportunity cost estimates and to explore the role of omitted variable bias in these estimations. The aim of this paper is to provide an updated and refined estimate of the causal impact of health spending on health in Spain that can be translated into an estimate of the incremental cost per quality-adjusted life-year produced by the Spanish national health system. We applied fixed-effect models using data for 17 Spanish regions from 2002 until 2022 to estimate the impact of public health spending on health outcomes and explored the extent of omitted variable bias. Changes in these estimates over time were assessed and alternative specifications were tested. Based on fixed-effect models with control variables, the estimated spending elasticity was 0.061, which translated into an incremental cost per quality-adjusted life-year of approximately €34,000. The bias-corrected elasticity was 0.075, with a corresponding incremental cost per quality-adjusted life-year of €27,000. We found that the estimated impact of spending on health decreases when recent years of data are added, and that the extent of omitted variable bias appears to increase, particularly when adding the COVID-19 pandemic period. This study provides an updated estimation of the incremental cost per quality-adjusted life-year produced by the Spanish national health system. The estimates provided can be easily updatable as new data become accessible, and the methods applied might be transferable to other settings with similar available data.
An accurate thermal measurement of low-frequency stimulation (LFS) pads for thermotherapy was investigated using background subtraction (BGS) methods. The safety of LFS thermal pads must be investigated to prevent low-temperature burns (LTBs), because they frequently contact the sensitive skin in neck, shoulder and abdominal regions. The thermal measurement was based on thermal imaging using the active region-of-interest (ROI) from a foreground. The shape of the LFS thermal pad consists of complicated curves, thus it is difficult to extract the foreground using conventional shapes of ROIs. We proposed the foreground extraction using background subtraction (BGS) and digital and morphological filters to time-variant thermal images. The foreground extraction was implemented using open sources and experimented for abdominal, cervical and patellar pads. The results showed that the foreground can be separated from background regardless of the size, position, orientation and shape of the pad. The thermal characteristics of the LFS thermal pads were evaluated from the complicated shapes of the foreground with high accuracy. This study demonstrated that standard deviation of pixel history (SDPH) is a simple method for the BGS, but the SDPH is useful to find the safety risk of LTBs and prevent them in advance. The results also showed that the proposed SDPH was simple but had remarkable accuracy compared with the conventional BGS methods. These BGS methods are expected to increase the reliability of products used on the human body. Further, the BGS methods can be used to inspect the temperatures of static products in industrial processes.
Open-source intelligence is the collection, analysis, and use of information legally obtained from public sources for a specific purpose. Although information obtained from open sources is not validated, it is useful in evidence-based medicine due to its rapid accessibility. In order to contain the spread of epidemics and respond to them, it is essential to obtain information as quickly as possible. The tools and sources of open-source intelligence procedures are therefore used by several institutions established for this purpose, as well as by the World Health Organization. Orv Hetil. 2025; 166(32): 1250–1255. A nyílt forrású hírszerzés nyilvános forrásokból legálisan megszerzett információk gyűjtése, elemzése és felhasználása egy bizonyos cél érdekében. Annak ellenére, hogy a nyílt forrásokból nyert információ nem validált, a gyors hozzáférése révén válik az ’evidence-based’ (bizonyítékon alapuló) orvostudomány hasznára. A járványok terjedésének megfékezéséhez és az arra való reagáláshoz alapvető, hogy a lehető leggyorsabban hozzájussunk az információhoz. A nyílt forrású hírszerzési eljárás eszközeit, forrásait ezért számos, erre a célra létrejött intézmény és az Egészségügyi Világszervezet is használja. Orv Hetil. 2025; 166(32): 1250–1255.