Search Results (7,653)

Nepal is currently facing critical water quality challenges due to urbanization, water management and governance issues, as well as natural disasters. This has resulted in the presence of harmful contaminants (e.g., pathogens, nitrates, arsenic) across multiple water sources, subsequently leading to waterborne disease risks (e.g., cholera and typhoid). In response to these environmental and public health concerns, we conducted a scoping review to assess microbial and chemical contaminants in drinking and irrigation water in Nepal, as well as their potential impacts on public health. Following the JBI Manual for Evidence Synthesis and the PRISMA-SCR guidelines, we systematically searched for peer-reviewed literature on Nepal’s water quality in seven databases. Of 3666 unique records screened using predefined inclusion criteria, 140 met our criteria. The studies encompassed a variety of methodological designs, with the majority focusing on water sources in the Bagmati province. Bacteria and arsenic emerged as the most prevalent contaminants. Additionally, diseases such as arsenicosis and typhoid remain widespread and may be linked to contaminated water sources. The review identified key gaps in Nepal’s water quality management, including limited geographic research coverage, inconsistent testing protocols, weak regulatory enforcement, and a lack of integration of water quality with public health planning. Our findings underscore the urgent need for effective surveillance systems and a robust regulatory framework to promptly respond to water contamination events in Nepal. Full article

Bovine Viral Diarrhea Virus (BVDV) is a globally important cattle pathogen causing substantial economic losses. In Kazakhstan, BVDV’s epidemiological status remains poorly characterized due to the absence of systematic surveillance. We carried out a cross-sectional study of cattle herds across Kazakhstan, using ELISA to detect anti-BVDV antibodies and RT-PCR to identify active infections. Positive samples underwent sequencing for phylogenetic analysis of circulating strains. Additionally, a standard reference serum panel was developed to measure virus neutralization titers (ND₅₀) and to evaluate cross-neutralization with Border Disease virus (BDV). Antibodies against BVDV were prevalent, with seropositivity ranging from 28.89% to 96.13% across surveyed regions. Active BVDV infection was confirmed by RT-PCR in 17 animals. Phylogenetic analysis with 2 samples from Mangystau region classified the virus as BVDV2 genotype. The reference serum panel exhibited high neutralizing titers ND₅₀ up to 1:286 against the local BVDV-1 isolate. Notably, these sera also neutralized BDV, albeit at lower titers ND₅₀ 1:45. These findings provide crucial baseline epidemiological data and enhanced diagnostic tools for BVDV in Kazakhstan. They highlight the need for improved surveillance and will inform strategic control measures against this economically significant cattle disease. Full article

Radon exposure is the second leading cause of lung cancer worldwide, yet monitoring strategies remain limited, expensive, and unevenly applied. Recent advances in the Internet of Things (IoT) offer the potential to change radon surveillance through low-cost, real-time, distributed sensing networks. This review consolidates emerging research on IoT-based radon monitoring, drawing from both primary radon studies and analogous applications in environmental IoT. A search across six major databases and relevant grey literature yielded only five radon-specific IoT studies, underscoring how new this research field is rather than reflecting a shortcoming of the review. To enhance the analysis, we delve into sensor physics, embedded system design, wireless protocols, and calibration techniques, incorporating lessons from established IoT sectors like indoor air quality, industrial safety, and volcanic gas monitoring. This interdisciplinary approach reveals that many technical and logistical challenges, such as calibration drift, power autonomy, connectivity, and scalability, have been addressed in related fields and can be adapted for radon monitoring. By uniting pioneering efforts within the broader context of IoT-enabled environmental sensing, this review provides a reference point and a future roadmap. It outlines key research priorities, including large-scale validation, standardized calibration methods, AI-driven analytics integration, and equitable deployment strategies. Although radon-focused IoT research is still at an early stage, current progress suggests it could make continuous exposure assessment more reliable, affordable, and widely accessible with clear public health benefits. Full article

Immune checkpoint inhibitors (ICIs) improve lung cancer prognosis but are associated with immune-related adverse events, most commonly thyroid dysfunction. While prior studies and guidelines have focused on thyroid dysfunction during ICI therapy, data on hypothyroidism and its monitoring after ICI therapy remain limited. We aimed to investigate hypothyroidism incidence and implementation of thyroid function monitoring after ICI therapy completion in patients with lung cancer. We conducted a retrospective observational study using the DeSC claims database of approximately 12 million individuals in Japan. Patients with lung cancer who received ICI therapy between April 2014 and August 2023 were included; those with a history of thyroid hormone replacement or insufficient follow-up were excluded. Among 6883 eligible patients, 277 (4.0%) developed hypothyroidism requiring hormone replacement post-ICI therapy completion (median onset, 67.0 d). Risk factors included ICI plus bevacizumab therapy and a history of myasthenia gravis, while steroid use for ≥28 d during ICI therapy lowered the risk. Post-ICI therapy completion thyroid monitoring was performed in 73.7% of patients, with test date distribution showing a median of 126.0 d and mode of 21.0 d. Hypothyroidism was frequently found to develop within 2 months post-ICI therapy completion, highlighting the need for continued thyroid monitoring and prospective studies to establish optimal surveillance strategies. Full article

Acute respiratory infections (ARIs) continue to pose a major global health threat, particularly among vulnerable populations. These infections often present with similar clinical symptoms, complicating accurate diagnosis and facilitating unmonitored transmissions. Genomic surveillance has emerged as an invaluable tool for pathogen identification and monitoring of such infectious pathogens; however, its implementation is frequently limited by high costs. The widespread use of high-throughput sequencing during the COVID-19 pandemic has created an opportunity to repurpose existing genomic platforms for broader respiratory virus surveillance. In this study, we evaluated the feasibility of adapting the Illumina COVIDSeq assay—initially designed for SARS-CoV-2 whole-genome sequencing—for use with Influenza A/B, Respiratory Syncytial Virus (RSV), and Rhinovirus. Positive control samples were processed using two approaches for library preparation: four virus-specific multiple workflows and a combined rapid workflow. Both workflows incorporated pathogen-specific primers for amplification and followed the Illumina COVIDSeq protocol for library preparation and sequencing. Sequencing quality metrics were analysed, including Phred scores, read length distribution, and coverage depth. The study did not identify significant differences in genome coverage and genetic diversity metrics between workflows. Genome Detective consistently identified the correct species across both methods. The findings of this study demonstrate that the COVIDSeq assay can be effectively adapted for multi-pathogen genomic surveillance and that the combined rapid workflow can offer a cost- and labour-efficient alternative with minimal compromise to data quality. Full article

Bovine leukemia virus (BLV), an oncogenic retrovirus of the genus Deltaretrovirus, causes enzootic bovine leukosis (EBL), the most prevalent neoplastic disease in cattle and a major source of economic loss. While BLV prevalence has been studied in commercial breeds, data on native Latin American cattle remain limited. This study assessed BLV infection and proviral load in 244 animals from six native breeds: Argentine Creole (CrAr), Patagonian Argentine Creole (CrArPat), Pampa Chaqueño Creole (CrPaCh), Bolivian Creole from Cochabamba (CrCoch), Saavedreño Creole (CrSaa), and Siboney (Sib), sampled across Argentina, Bolivia, Paraguay, and Cuba. BLV-CoCoMo-qPCR-2 assay detected BLV provirus in 76 animals (31.1%), with a mean load of 9923 copies per 10⁵ cells (range: 1–79,740). Infection rates varied significantly by breed (9.8% in CrAr to 83.8% in CrPaCh) and country (15.6% in Argentina to 83.8% in Paraguay) (p = 9.999 × 10⁻⁵). Among positives, 57.9% exhibited low proviral load (≤1000 copies), and 13.2% showed moderate levels (1001–9999), suggesting potential resistance to EBL progression. This is the first comprehensive report of BLV proviral load in Creole cattle across Latin America, offering novel epidemiological insights and highlighting the importance of native breeds in BLV surveillance. Full article

In Ecuador, the transmission of dengue has steadily increased in recent decades, particularly in coastal cities like Manta, where the conditions are favorable for the proliferation of the Aedes aegypti mosquito. The objective of this study was to model the spatial distribution of dengue transmission risk in Manta, a coastal city in Ecuador with consistently high incidence rates. A total of 148 georeferenced dengue cases from 2018 to 2021 were collected, and environmental and socioeconomic variables were incorporated into a maximum entropy model (MaxEnt). Additionally, climate and social zoning were performed using a multi-criteria model in TerrSet. The MaxEnt model demonstrated excellent predictive ability (training AUC = 0.916; test AUC = 0.876) and identified population density, sewer system access, and distance to rivers as the primary predictors. Three high-risk clusters were identified in the southern, northwestern, and northeastern parts of the city, while the coastal strip showed lower suitability due to low rainfall and vegetation. These findings reveal the strong spatial heterogeneity of dengue risk at the neighborhood level and provide operational information for targeted interventions. This approach can support more efficient surveillance, resource allocation, and community action in coastal urban areas affected by vector-borne diseases. Full article

We investigated respiratory virus epidemiology in older adults across pre-pandemic (2007–2019), pandemic (2020–2022), and post-pandemic (2023–2024) periods, focusing on how public health interventions shaped surveillance, prevalence, and sex-specific trends. We conducted a retrospective cross-sectional study at a 1000-bed tertiary hospital in the Republic of Korea during 2007–2024, analyzing 4692 nasopharyngeal swab specimens collected from adults aged ≥ 65 years with suspected respiratory infections during 2007–2024. The specimens were tested for 15 respiratory viruses using multiplex real-time polymerase chain reaction. The outcomes included virus-specific detection rates and seasonal, sex-based and temporal trends before and after the COVID-19 pandemic. During the pre-pandemic period, older adults accounted for 13.2% of the tested individuals, which significantly increased to 52.0% in the later periods. Influenza A was the most frequently detected virus, followed by rhinovirus and human metapneumovirus. Influenza, RSV A/B, and coronaviruses 229E and OC43 showed peak positivity in winter, parainfluenza virus type 3 peaked in summer, and rhinovirus circulated year-round. Virus circulation was markedly suppressed during 2020–2022 and partially rebounded during 2023–2024. This study highlights the shift in diagnostic access and epidemiologic patterns of respiratory virus infections in older adults following the COVID-19 pandemic. Full article

Immunocompromised outpatients, including people living with HIV/AIDS (PLWH), diabetes, cancer, and organ transplant recipients, are at high risk of antimicrobial resistance (AMR) due to their weakened immune systems and use of immunosuppressive therapies. The high prevalence of prophylactic and therapeutic antibiotic use in this vulnerable population, coupled with frequent contact with healthcare facilities and limited outpatient antimicrobial resistance surveillance systems, contributes to the increase in antimicrobial resistance. The majority of available data pertains to inpatients, and there is a lack of comprehensive outpatient information on pathogen distribution, resistance patterns, and diagnostic challenges. Moreover, nonspecific clinical presentations, diminished inflammatory responses, and limitations of traditional diagnostic methods complicate infection diagnosis in this population. Increasing resistance surveillance, developing rapid diagnostic tools, and implementing accurate and personalized approaches are key strategies to reduce the burden of disease, mortality, and healthcare costs in the immunocompromised outpatient population. This study was designed as a narrative review based on a comprehensive search of major databases and guidelines. It aims to examine the available evidence and address the challenges associated with AMR in immunocompromised outpatients. Full article

Objective: To evaluate the predictive value of umbilical artery half peak systolic velocity deceleration time (UA hPSV-DT) for composite adverse perinatal outcomes (CAPO) in pregnancies complicated by gestational diabetes mellitus (GDM). Methods: In this prospective observational study, 120 singleton pregnancies in the third trimester were enrolled: 30 insulin-regulated GDM (IRGDM), 30 diet-regulated GDM (DRGDM), and 60 healthy controls. UA hPSV-DT and standard Doppler indices were measured using a standardized protocol by a single perinatologist. An abnormal UA hPSV-DT was defined as <5th percentile for gestational age. Maternal metabolic parameters, fetal biometry, and neonatal outcomes were recorded. The primary outcome was CAPO, defined as the presence of one or more adverse perinatal events. Results: Median UA hPSV-DT values were significantly lower in IRGDM (171 ms) and DRGDM (184 ms) compared with controls (227 ms) (p = 0.006). Abnormal UA hPSV-DT occurred in 43.3% of GDM cases and was associated with higher estimated fetal weight and abdominal circumference percentiles, increased amniotic fluid, elevated OGTT values, higher HbA1c, and more frequent insulin therapy (p < 0.01 for all). In GDM pregnancies, CAPO occurred in 73.1% of the abnormal UA hPSV-DT group versus 11.8% of the normal group (p < 0.001). ROC analysis identified a cut-off of < 181 ms for predicting CAPO (AUC 0.741, 70.3% sensitivity, 66.7% specificity). Conclusions: UA hPSV-DT is a novel, reproducible Doppler parameter that independently predicts adverse perinatal outcomes in GDM pregnancies, even when conventional UA Doppler indices are normal. Incorporating UA hPSV-DT into routine surveillance may improve risk stratification and guide management to optimize perinatal outcomes. Full article

Background/Objectives: Fetal growth restriction (FGR) is a leading cause of perinatal morbidity and mortality. Accurate surveillance and timely delivery are critical to improving outcomes. This narrative review examines the role of computerized cardiotocography (cCTG) and short-term variation (STV) interpretation in the monitoring of FGR and its integration with Doppler velocimetry and the biophysical profile (BPP). Methods: A comprehensive literature search of PubMed, Scopus, and Web of Science was performed for studies published up to 2021 using combinations of terms related to FGR, CTG, STV, and Doppler surveillance. Eligible sources included original studies, systematic reviews, and international guidelines. Case reports, intrapartum-only monitoring, and studies involving major anomalies were excluded. Results: Reduced STV consistently correlates with fetal compromise, abnormal Doppler findings, and adverse perinatal outcomes. In early-onset FGR (<32 weeks), ductus venosus abnormalities often coincide with or precede STV reduction; combined use supports optimal timing of delivery. In late-onset FGR (≥32 weeks), STV changes are less pronounced and require integration with cerebroplacental ratio, variability indices, and trend-based interpretation. Longitudinal evaluation offers greater prognostic value than isolated measurements. However, heterogeneity in thresholds, fragmented outcome data, and system-specific definitions limit standardization and comparability across studies. Conclusions: cCTG provides an objective and adjunct to Doppler and BPP in the surveillance of FGR, a tool for obstetrician needs. Its greatest utility lies in serial, integrated assessment, supported by gestational age-specific reference ranges. Future advances should include standardized STV thresholds, large outcome-linked databases, and artificial intelligence-driven tools to refine decision-making and optimize delivery timing. Full article

Brucellosis remains an underreported zoonotic disease in Ecuador. Its control program in cattle integrates diagnostic testing, vaccination, and eradication incentives, although participation is largely voluntary. Since 2025, vaccination has become compulsory nationwide. Human surveillance remains largely passive, and strain-level data are very limited. This study applied an integrated approach, combining serology (Rose Bengal and SAT-EDTA), microbiological culture, and molecular diagnostics, to assess the presence and diversity of Brucella spp. in cattle and pigs from six slaughterhouses in the northern Andean highlands. A total of 2054 cattle and 1050 pigs from Carchi, Imbabura, and Pichincha were sampled. Among cattle, 133 (6.5%; 95% CI: 5.5–7.6) were seropositive, and viable B. abortus strains were isolated from 17 (12.8%). Genus identification was confirmed by IS711-PCR, while species- and biovar-level differentiation was achieved with AMOS-PCR; additional assays targeting the ery gene and RB51 marker were used to distinguish field from vaccine strains. Biotyping and molecular analysis revealed a predominance of B. abortus biovar 4 (13/17 isolates) over biovar 1, all confirmed as field strains. In pigs, 10 animals (0.95%) tested seropositive, but no isolates were recovered, highlighting limitations of serology in swine. Most livestock, including the positives, originated locally, reinforcing the representativeness of our findings. The successful isolation and molecular characterization of B. abortus demonstrates the value of combining diagnostic strategies beyond serology. These results underscore the utility of active surveillance when supported by traceability systems; this approach may also contribute to guide interventions to reduce infection risk in livestock and humans. Full article

This comprehensive review explores the distribution, diversity, and epidemiology of tick-borne borrelioses across Eurasia, focusing on Lyme borreliosis (LB) and other Borrelia-related infections. The genus Borrelia is categorized into three major groups, the Lyme Group (LG), the Relapsing Fever Group (RFG), and the Echidna–Reptile Group (REPG), each with distinct vectors, reservoirs, and pathogenic profiles. LB, caused by Borrelia burgdorferi sensu lato, is highly endemic in Europe and is increasingly reported in Asia, although it is underdiagnosed in Southeast Asia due to limited surveillance. This review details the ecological dynamics of tick vectors—primarily Ixodes spp.—and their vertebrate hosts, emphasizing the role of migratory birds and climate change in disease spread. It also highlights the presence of relapsing fever Borrelia species transmitted by soft ticks (Ornithodoros spp.) and the emergence of novel species such as Borrelia miyamotoi (RFG) and Borrelia turcica (REPG). This study underscores the need for harmonized surveillance systems, improved diagnostic tools, and integrated public health strategies to address the growing threat of borreliosis in Eurasia. Full article

The increasing use of AI systems for face, object, action, scene, and emotion recognition raises significant privacy risks, particularly when processing Personally Identifiable Information (PII). Current privacy-preserving methods lack adaptability to users’ preferences and contextual requirements, and obfuscate user faces uniformly. This research proposes a user-centric, context-aware, and ontology-driven privacy protection framework that dynamically adjusts privacy decisions based on user-defined preferences, entity sensitivity, and contextual information. The framework integrates state-of-the-art recognition models for recognising faces, objects, scenes, actions, and emotions in real time on data acquired from vision sensors (e.g., cameras). Privacy decisions are directed by a contextual ontology based in Contextual Integrity theory, which classifies entities into private, semi-private, or public categories. Adaptive privacy levels are enforced through obfuscation techniques and a multi-level privacy model that supports user-defined red lines (e.g., “always hide logos”). The framework also proposes a Re-Identifiability Index (RII) using soft biometric features such as gait, hairstyle, clothing, skin tone, age, and gender, to mitigate identity leakage and to support fallback protection when face recognition fails. The experimental evaluation relied on sensor-captured datasets, which replicate real-world image sensors such as surveillance cameras. User studies confirmed that the framework was effective, with over 85.2% of participants rating the obfuscation operations as highly effective, and the other 14.8% stating that obfuscation was adequately effective. Amongst these, 71.4% considered the balance between privacy protection and usability very satisfactory and 28% found it satisfactory. GPU acceleration was deployed to enable real-time performance of these models by reducing frame processing time from 1200 ms (CPU) to 198 ms. This ontology-driven framework employs user-defined red lines, contextual reasoning, and dual metrics (RII/IVI) to dynamically balance privacy protection with scene intelligibility. Unlike current anonymisation methods, the framework provides a real-time, user-centric, and GDPR-compliant method that operationalises privacy-by-design while preserving scene intelligibility. These features make the framework appropriate to a variety of real-world applications including healthcare, surveillance, and social media. Full article

Despite the well-established link between animal abuse and interpersonal violence, animal mistreatment remains a global issue. Challenges such as inconsistent legislation, limited training of specialized pathologists, and lack of regional data persist and must be addressed. In Spain, the real incidence of animal abuse is unknown, and the literature on the topic remains scarce. This study aims to assess the evolution of feline abuse cases in the Community of Madrid, Spain, since the publication of a previous study in the same region. Over a five-year period (2020–2024), 53 cats with suspected abuse were diagnosed at the Pathology and Forensic Veterinary Unit of the VISAVET Health Surveillance Center. Thirty-one cats (58.49%) died from non-natural causes: 17 (32.07%) due to blunt force trauma, eight (15.09%) due to poisoning, and six (11.32%) due to projectile injuries. Natural causes accounted for 21 cases (39.62%). Compared to the previous study, data suggest a possible upward trend in the number of cats referred with suspected animal abuse, including eight new cases of ethylene glycol poisoning. The correlation between the type of suspected abuse and final diagnosis was very low. This article examines current challenges related to animal violence, with particular emphasis on feline colonies, and promotes awareness among both veterinary and non-veterinary professionals. Full article