Search Results (87)

Despite growing recognition of the role that social determinants of health (SDOHs) and health-related social needs (HRSNs) play in chronic disease, limited research has examined their associations with Chronic Obstructive Pulmonary Disease (COPD) in population-based studies. This cross-sectional study analyzed 2022 Behavioral Risk Factor Surveillance System (BRFSS) data from 37 U.S. states and territories to determine how financial hardship, food insecurity, employment loss, healthcare access barriers, and psychosocial stressors influence the prevalence of COPD. Weighted logistic regression models were used to assess the associations between COPD and specific SDOHs and HRSNs. Several individual SDOH and HRSN factors were significantly associated with COPD prevalence, with financial strain emerging as a particularly strong predictor. In models examining specific SDOH factors, economic hardships like inability to afford medical care were strongly linked to higher COPD odds. Psychosocial HRSN risks, such as experiencing mental stress, also showed moderate associations with increased COPD prevalence. These findings suggest that addressing both structural and individual-level social risks may be critical for reducing the prevalence of COPD in populations experiencing financial challenges. Full article

This study examines how U.S. immigration policies enact legal violence and multigenerational punishment through the spousal reunification process, particularly in mixed-status, transnational families. Building on the concept of “deportability,” we introduce “importability” to describe a beneficiary’s potential to secure permanent residency, which varies according to social markers such as race, gender, and region of origin. Drawing from a content analysis of threads on the Immigration Pathways (IP) web forum, we analyze discussions among U.S. citizen petitioners navigating marriage-based green card applications, with a focus on experiences involving administrative processing (AP) (i.e., marriage fraud investigations). Our findings show that couples who do not align with the state’s conception of “proper” family—particularly U.S. citizen women petitioning for Black African partners—face intensified scrutiny, long delays, and burdensome requirements, including DNA tests and surveillance. These bureaucratic obstacles produce prolonged family separation, financial strain, and diminished sense of belonging, especially for children in single-parent households. Through the lens of “importability,” we reveal how legal violence and multigenerational punishment of immigration policies on mixed-status families beyond deportation threats, functioning as a gatekeeping mechanism that disproportionately affects marginalized families. This research highlights the understudied consequences of immigration policies on citizen petitioners and contributes to a broader understanding of inequality in U.S. immigration enforcement. Full article

Small ruminant lentiviruses (SRLVs) are widespread and have a long co-evolutionary history with their hosts, namely sheep and goats. These viruses induce insidious pathologies, causing significant financial losses and animal welfare issues for the affected flocks. In Switzerland, in the 1980s, an eradication campaign was launched targeting these viruses, exclusively in goats, eliminating the virulent SRLV-B strains from the goat population, in which SRLV-B-induced arthritis was prevalent. Nevertheless, although they do not seem to induce clinical diseases, SRLV-A strains continue to circulate in Swiss goats. For this study, we contacted farmers who had animals testing positive for these strains during the census from 2011 to 2012 and visited six of these flocks, conducting serological, virological, and clinical analyses of the animals. We confirmed the absence of SRLV-B; however, we have detected SRLV-A in these flocks. Positive and negative animals lived in close contact for ten years and, except for a small flock of 13 animals, 7 of which tested positive, the transmission of these viruses proved inefficient. None of the positive animals showed any pathology attributable to SRLV infection. These encouraging results allowed us to formulate recommendations for the continued surveillance of these viruses in the Swiss goat population. Full article

The agriculture sector is increasingly challenged to maintain productivity and sustainability amidst environmental, marketplace, and geopolitical pressures. While precision agriculture enhances physical production, the financial resilience of agricultural firms has been understudied. In this study, machine learning (ML) methods, including logistic regression (LR), decision trees (DTs), and artificial neural networks (ANNs), are employed to predict the bankruptcy risk for Central and Eastern European (CEE) farming firms. All models consistently showed high performance, with AUC values exceeding 0.95. DTs had the highest overall accuracy (95.72%) and F1 score (0.9768), LR had the highest recall (0.9923), and ANNs had the highest discrimination power (AUC = 0.960). Visegrad, Balkan, Baltic, and Eastern Europe subregional models featured economic and structural heterogeneity, reflecting the need for local financial risk surveillance. The results support the development of AI-based early warning systems for agricultural finance, enabling smarter decision-making, regional adaptation, and enhanced sustainability in the sector. Full article

Background/Objectives: Outbreaks of highly pathogenic avian influenza virus (AIV) result in significant financial losses and the death or depopulation of millions of domestic birds. Early and rapid detection and surveillance are needed to slow the spread of AIV and prevent its spillover to humans. The volatile metabolome (i.e., the pattern of volatile metabolites emitted by a living subject) represents one such source of health information that can be monitored for disease diagnosis. Indeed, dogs have been successfully trained to recognize patterns of “body odors” associated with many diseases. Because little is known regarding the mechanisms involved in the alteration of the volatile metabolome in response to health perturbation, questions still arise regarding the specificity, or lack thereof, of these alterations. Methods: To address this concern, we experimentally infected twenty mallard ducks with one of two different strains of low-pathogenic AIV (ten ducks per strain) and collected cloacal swabs at various time points before and after infection. Results: Headspace analyses revealed that four volatiles were significantly altered following infection, with distinct profiles associated with each viral strain. The volatiles that differed between strains among post-infection sampling periods included ethylbenzyl ether (p = 0.00006), 2-phenoxyethanol (p = 0.00017), 2-hydroxybenzaldehyde (p = 0.00022), and 6-methyl-5-hepten-2-one (p = 0.00034). Conclusions: These findings underscore that AIV-induced changes to the volatile metabolome are strain-specific, emphasizing the need for disease-specific profiling in diagnostic development. Full article

Street crime is a critical public concern, attracting wide social and research attention. Conventional solutions to reduce street crimes are dispatching more police force in patrol and installing more cameras for street surveillance, which, however, suffer from huge manpower and financial consumption and limited performance. Inspired by the wide application of Unmanned Aerial Vehicles (UAVs) in policing and other related missions such as street surveillance, we investigate the use of UAVs in patrolling along high-risk streets to deter street crimes. UAVs significantly outperform police officers and street cameras in terms of cost reduction and deterring performance improvement. Technically, this paper proposes a data-driven framework to schedule the patrol UAVs, including an online patrol path planning module and an offline UAV station siting module. In the first module, the street-level deterring effect of the UAVs is estimated using a prediction-enhanced method, which guides the UAVs to patrol the high-risk streets more efficiently. Evolved from the path planning algorithm, the second module utilizes a data-driven method to estimate the deterring effect of the candidate UAV stations with different numbers of UAVs. Then both the location of the UAV stations and the UAVs at each station are determined. The proposed framework is comprehensively evaluated using a 6-year crime dataset of the Denver city. The results show that the proposed framework improves the deterring effect by 58.49% on average, and up to 157.32% in extreme cases compared to baselines. Full article

There has been a well-documented increase in the incidence of colorectal cancer in patients under 50 years of age. Additionally, these patients present with later-stage cancer at diagnosis compared to their over-50 counterparts. However, there is limited consensus on how the impact of this evolving epidemiology should impact existing prevention and screening tools. Recently proposed strategies include increased genetic testing, improved young patient awareness through targeted media campaigns, and initiatives to increase clinical suspicion in primary care providers. Prevention is further complicated by nuances of treating colorectal cancer in the younger population, with underexplored concerns regarding fertility, sexual health, financial impact, and extended post-treatment surveillance. This review aims to summarize the changing epidemiology of colorectal cancer in young patients, overview existing screening guidelines, and discuss challenges and opportunities surrounding prevention of early-onset colon cancer. Full article

Background/Objectives: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with the Asia-Pacific (APAC) region bearing a disproportionate burden. This paper examines HCC challenges within seven APAC health systems, identifies key barriers at each stage of the patient journey, and proposes tailored, actionable solutions. To effectively address HCC challenges, a stepwise approach should prioritise high-impact solutions, focusing on prevention, early diagnosis, and expanding surveillance to maximise health outcomes and economic benefits, while tailoring strategies to each health system’s unique resources and constraints. Methods: A mixed-methods approach was used, including expert consultations from the 2024 HCC APAC Policy Forum, a literature review, and a review of Japan’s HCC management model. Data were collected through workshops and stakeholder feedback from healthcare professionals, policymakers, researchers and patient advocates across Australia, India, Malaysia, South Korea, Taiwan, Thailand, and Vietnam. Results: Key findings include significant disparities in HCC awareness, prevention, early detection, diagnosis, and access to treatment. Common challenges across APAC include limited public awareness, suboptimal surveillance infrastructure, and financial barriers to care. The integration of novel biomarkers and advanced surveillance modalities were identified as crucial priorities for improving early detection. Japan’s multi-faceted approach to HCC management serves as a successful model for the region. Conclusions: A customised and targeted approach is essential for reducing the HCC burden across APAC. The proposed recommendations, tailored to each health system’s needs, can significantly improve patient outcomes and reduce healthcare costs. Effective collaboration among stakeholders is necessary to drive these changes. Full article

Prostate cancer (PCa) is one of the most common malignancies among men worldwide. While prostate-specific antigen (PSA) screening has improved early detection, it has also led to significant challenges regarding overdiagnosis and overtreatment. Overdiagnosis involves identifying indolent tumors unlikely to affect a patient’s lifespan, while overtreatment refers to unnecessary interventions that can cause adverse effects such as urinary incontinence, erectile dysfunction, and a reduced quality of life. This review highlights contributing factors, including the limitations of PSA testing, advanced imaging techniques like multi-parametric MRI (mpMRI), medical culture, and patient expectations. The analysis emphasizes the need for refining screening protocols, integrating novel biomarkers (e.g., PCA3, TMPRSS2-ERG), and adopting conservative management strategies such as active surveillance to minimize harm. Risk-based screening and shared decision-making are critical to balancing the benefits of early detection with the risks of unnecessary treatment. Additionally, systemic healthcare factors like financial incentives and malpractice concerns exacerbate overuse. This review advocates for updated clinical guidelines and personalized approaches to optimizing patient outcomes while reducing the strain on healthcare resources. Addressing overdiagnosis and overtreatment through targeted interventions will improve the quality of life for PCa patients and enhance the efficiency of healthcare systems. Full article

Maintaining high water quality is essential not only for human survival but also for social and ecological safety. In recent years, due to the influence of human activities and natural factors, water quality has significantly deteriorated, and effective water quality monitoring is urgently needed. Traditional water quality monitoring requires substantial financial investment, whereas the remote sensing and random forest model not only reduces operational costs but also achieves a paradigm shift from discrete sampling points to spatially continuous surveillance. The random forest model was adopted to establish a remote sensing inversion model of three water quality parameters (conductivity, total nitrogen (TN), and total phosphorus (TP)) during the growing period (May to September) from 2020 to 2022 in the Songhua River Basin (SRB), using Landsat 8 imagery and China’s national water quality monitoring section data. Model verification shows that the R² of conductivity is 0.67, followed by that of TN at 0.52 and TP at 0.47. The results revealed that the downstream conductivity of SRB (212.72 μS/cm) was significantly higher than that upstream (161.62 μS/cm), with TN and TP concentrations exhibiting a similar increasing pattern. This study is significant for improving ecological conservation and human health in the SRB. Full article

Following its initial documented emergence in Hunan’s swine facilities in 2017, GETV has inflicted considerable financial damage upon China’s pork production sector. Beyond its impact on swine, GETV also poses a potential risk to other animal species and public health, primarily due to its mosquito-borne transmission. Between September 2020 and May 2021, a GETV outbreak occurred on a commercial swine farm in Sichuan Province, where affected animals exhibited movement disorders, neurological symptoms, and mild diarrhea, with severe cases resulting in mortality. To elucidate the genetic characteristics and transmission dynamics of the virus, a comprehensive investigation of this outbreak was conducted. Clinical samples from diseased or deceased swine were collected and analyzed by PCR, confirming the presence of GETV infection. Additionally, differential diagnostic assays were performed for other common swine pathogens, including porcine reproductive and respiratory syndrome virus (PRRSV), pseudorabies virus (PRV), classical swine fever virus (CSFV), and atypical porcine pestivirus (APPV). All tests yielded negative results, confirming GETV as the sole etiological agent of the outbreak. The GETV-positive samples were inoculated into BHK-21 cells, leading to the isolation of a GETV strain (SC202009). Whole-genome sequence analysis revealed that SC202009 belongs to the GIII genotype of GETV, with a nucleotide sequence identity ranging from 95.1% to 99.8% compared to reference sequences in GenBank. This high level of sequence identity suggests that SC202009 is closely related to other circulating strains in the region, indicating potential local transmission networks and endemic viral circulation. The nucleotide sequence identity of the E2 gene ranged from 94.2% to 99.6%, while the E2 protein amino acid sequence identity ranged from 97.2% to 99.5%. Phylogenetic analysis further indicated that SC202009 is genetically distant from the original Malaysian prototype strain (MM2021) but shares high sequence identity with several strains isolated in Sichuan Province, including SC266, SC201807, and SC483. Notably, NMJA_F2_18-8L-NH-Cxp-Y-1-1 was isolated from Culex pipiens, suggesting a mosquito-borne transmission route. These findings provide novel insights into the regional dissemination patterns and genetic diversity of GETV in China. These results also highlight the importance of the continuous surveillance of viral genetic variations and the elucidation of transmission dynamics to develop effective control strategies and mitigate potential public health risks. Future studies should focus on the ecological and environmental factors influencing GETV transmission, particularly the role of mosquito vectors in cross-species viral spread, to enhance targeted prevention and control measures for this emerging arboviral threat. Full article

Highly pathogenic avian influenza (HPAI) H5N1 has been traditionally linked to poultry and wild birds, which has recently become a serious concern for dairy cattle, causing outbreaks all over the United States. The need for improved surveillance, biosecurity protocols, and interagency collaboration is highlighted by the discovery of H5N1 in dairy herds in several states and its human transmission. The epidemiology, transmission dynamics, and wide-ranging effects of H5N1 in cattle are reviewed in this paper, with particular attention paid to the disease’s effects on agricultural systems, public health, and animal health. Nonspecific clinical symptoms, such as decreased milk production and irregular milk consistency, are indicative of infection in dairy cows. Alarmingly, significant virus loads have been discovered in raw milk, raising worries about potential zoonotic transmission. The dangers of viral spillover between species are further highlighted by cases of domestic cats experiencing severe neurological symptoms after ingesting raw colostrum and milk from infected cows. Even though human cases remain rare, and they are mostly related to occupational exposure, constant attention is required due to the possibility of viral adaptability. The necessity of a One Health approach that integrates environmental, animal, and human health efforts is further supported by the broad occurrence of H5N1 across multiple species. For early detection, containment, and mitigation, cooperation between veterinary clinics, public health organizations, and agricultural stakeholders is crucial. Controlling the outbreak requires stringent movement restrictions, regular testing of dairy cows in reference labs, and adherence to biosecurity procedures. This review highlights the importance of thorough and coordinated efforts to manage H5N1 in dairy cattle by combining existing knowledge and pointing out gaps in surveillance and response strategies. Additionally, it sheds light on the potential risk of consumption of cow’s milk contaminated with H5N1 virus by humans and other companion animals like cats. In the face of this changing threat, proactive monitoring, strict biosecurity protocols, and cross-sector cooperation are crucial for reducing financial losses and protecting human and animal health. Full article

Early-onset sepsis (EOS) remains a major cause of neonatal morbidity and mortality worldwide, with significant differences in the incidence and outcome of the disease in Europe. Eastern European countries face particular challenges due to differences in access to healthcare, diagnostic facilities, and prevention strategies. This review summarizes the results of recent research to provide insights into maternal risk factors, regional inequalities in access to healthcare, diagnostic biomarkers, pathogen patterns, and treatment protocols for EOS. This review also examines how healthcare infrastructure and socioeconomic factors influence EOS outcomes in Eastern Europe. Introduction: Early-onset sepsis (EOS) presents a significant health challenge for newborns, characterized by sepsis occurring within the first 72 h of life, primarily caused by the vertical transmission of pathogens from mother to child. Despite advancements in medical care, EOS remains particularly burdensome in resource-poor settings, especially in Eastern Europe, where disparities in healthcare access and maternal health are pronounced. This systematic review aims to provide insights into maternal risk factors, regional inequalities in healthcare access, diagnostic biomarkers, pathogen patterns, and treatment protocols for EOS. Background/Objectives: EOS is increasingly recognized as a public health issue, with outcomes significantly influenced by maternal health, socioeconomic status, and healthcare infrastructure. The review seeks to summarize the existing literature on EOS, particularly focusing on differences between high-income Western and low-resource Eastern European countries. The influence of maternal access to antenatal care, pathogen prevalence, and antibiotic resistance on EOS outcomes across regions will also be examined. Methods: To achieve the review’s objectives, a comprehensive search was conducted across multiple databases including PubMed, Google Scholar, ScienceDirect, and Scopus, adhering to PRISMA guidelines for systematic reviews. The inclusion criteria encompassed studies published within the last 20 years (January 2004–August 2024) that addressed EOS in late preterm or term infants, emphasizing maternal health, risk factors, diagnostic approaches, and treatment protocols pertinent to European populations. Exclusion criteria included non-English publications and studies lacking a focus on maternal and neonatal health. A total of 29 peer-reviewed articles meeting the specified criteria were ultimately included in the analysis. Results: The findings highlight significant regional disparities in EOS management between Western and Eastern Europe. Key issues include maternal risk factors, socioeconomic barriers to healthcare, diagnostic biomarkers, and pathogen resistance trends. Limited access to prenatal screenings and healthcare infrastructure in Eastern European countries, especially in rural regions in Romania, exacerbate the challenges faced by expectant mothers. Financial burdens, such as high out-of-pocket expenses, were shown to further restrict access to necessary maternal care. Conclusions: This systematic review emphasizes the urgent need for targeted investments in maternal healthcare infrastructure in Eastern Europe to mitigate the impacts of EOS. Enhanced screening programs, standardized surveillance systems, and ensuring equitable health policies are essential to improving neonatal outcomes. Additionally, tailored education and awareness campaigns for disadvantaged groups and comprehensive health policy reforms, including universal antenatal care and Group B Streptococcus (GBS), are essential to bridging healthcare gaps. Full article

Climate change has a significant impact on the population’s health and negatively affects the functioning of healthcare systems. Health systems must be operationally prepared to handle the challenges posed by environmental change. Resilience is required to adapt quickly to critical environmental conditions and reduce carbon emissions. In this systematic review strategies, for health system preparedness and resilience are examined to address the impacts of climate change, and the barriers and challenges faced when implementing them. To identify studies, the Scopus, PubMed and Google Scholar databases were searched three times (from April to October 2024, 21 April, 15 June, and 9 September) for the years 2018 to 2024, using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. Specifically, the search identified 471 articles, of which the specified inclusion and exclusion criteria (secondary studies with inclusion criteria, being in English, etc.) were met by sixteen (16) studies. According to the findings of the studies reviewed, adaptation strategies focus on structural changes, the development of training programs, the development of surveillance systems, and appropriate operational plans. The leader’s ability to motivate employees to achieve defined goals, continuous evaluation of goals and interventions, and learning from previous disasters play an important role in their implementation. Similarly, key policies and strategies for mitigation include the adoption of sustainable practices, such as recycling and cultural change. However, lack of resources (human, material, financial) and increased demand for health services make it difficult to implement adaptation and mitigation strategies. The findings of the review are mainly theoretical in nature and are confirmed by other studies. It is suggested that further research on resilience and preparedness of health systems should be pursued, leading to their sustainability and the formulation of appropriate policies. Full article

Background: Healthcare-associated infections are infections that patients acquire during hospitalization or while receiving healthcare in other facilities. They represent the most frequent negative outcome in healthcare, can be entirely prevented, and pose a burden in terms of financial and human costs. With the development of new AI and ML algorithms, hospitals could develop new and automated surveillance and prevention models for HAIs, leading to improved patient safety. The aim of this review is to systematically retrieve, collect, and summarize all available information on the application and impact of AI in HAI surveillance and/or prevention. Methods: We conducted a systematic review of the literature using PubMed and Scopus to find articles related to the implementation of artificial intelligence in the surveillance and/or prevention of HAIs. Results: We identified a total of 218 articles, of which only 35 were included in the review. Most studies were conducted in the US (n = 10, 28.6%) and China (n = 5; 14.3%) and were published between 2021 and 2023 (26 articles, 74.3%) with an increasing trend over time. Most focused on the development of ML algorithms for the identification/prevention of surgical site infections (n = 18; 51%), followed by HAIs in general (n = 9; 26%), hospital-acquired urinary tract infections (n = 5; 9%), and healthcare-associated pneumonia (n = 3; 9%). Only one study focused on the proper use of personal protective equipment (PPE) and included healthcare workers as the study population. Overall, the trend indicates that several AI/ML models can effectively assist clinicians in everyday decisions, by identifying HAIs early or preventing them through personalized risk factors with good performance. However, only a few studies have reported an actual implementation of these models, which proved highly successful. In one case, manual workload was reduced by nearly 85%, while another study observed a decrease in the local hospital’s HAI incidence from 1.31% to 0.58%. Conclusions: AI has significant potential to improve the prevention, diagnosis, and management of healthcare-associated infections, offering benefits such as increased accuracy, reduced workloads, and cost savings. Although some AI applications have already been tested and validated, adoption in healthcare is hindered by barriers such as high implementation costs, technological limitations, and resistance from healthcare workers. Overcoming these challenges could allow AI to be more widely and cost-effectively integrated, ultimately improving patient care and infection management. Full article