Cross-modality fusion of hematology-based digital and molecular biomarkers for intelligent epidemiological screening and surveillance of hepatocellular carcinoma.

The rapid emergence of novel viral pathogens poses a significant threat to global public health, demanding timely detection, effective monitoring, and efficient containment strategies. The NPHA (Novel Public Health Agent) virus represents an emerging viral infection characterized by high transmission potential and limited early diagnostic capabilities. Traditional diagnostic and surveillance methods often face challenges such as delayed detection, limited scalability, and dependency on clinical infrastructure. In recent years, advancements in data analytics, machine learning, and bioinformatics have opened new avenues for virus detection and prediction. This survey paper presents a comprehensive review of existing studies related to the NPHA virus, focusing on its transmission characteristics, diagnostic techniques, and computational approaches employed for early detection and analysis. Furthermore, a conceptual hybrid model integrating machine learning and epidemiological data is proposed to enhance detection accuracy and outbreak prediction. The paper highlights research gaps, summarizes key findings, and outlines future research directions to support effective management of emerging viral threats.

Active surveillance methods to identify adverse events of special interest (AESIs) following vaccination against pandemic diseases: A scoping review.

During the COVID-19 pandemic, wastewater-based epidemiology has progressively taken a central role as a pathogen surveillance tool. Tracking viral loads and variant outbreaks in sewage offers advantages over clinical surveillance methods by providing estimates not biased by testing practices and enabling early detection. However, wastewater-based epidemiology poses new computational research questions that need to be solved in order for this approach to be implemented broadly and successfully. Here, we address the variant deconvolution problem, where we aim to estimate the relative abundances of genomic variants from next-generation sequencing data of a mixed wastewater sample. We introduce LolliPop, a computational method to solve the variant deconvolution problem. LolliPop is tailored to wastewater time series sequencing data and applies temporal regularization in the form of a fused ridge penalty. We show that this regularization is equivalent to kernel smoothing and that it makes abundance estimates robust to very high levels of missing data, which is common for wastewater sequencing. We use the bootstrap to produce confidence intervals, and develop analytical standard errors that can produce similar confidence intervals at a fraction of the computational cost. We demonstrate the application of our method to data from the Swiss wastewater surveillance efforts as well as on simulated data.

Ongoing surveillance after successful endoscopic eradication therapy (EET) for Barrett's esophagus (BE) related neoplasia is essential to detect and manage recurrence. Despite established surveillance interval recommendations after complete eradication of intestinal metaplasia (CE-IM), patient compliance with repeat endoscopy is frequently suboptimal. Understanding patient drivers to adherence is essential to inform interventions that address the high rates of overdue surveillance and loss to follow-up. Patients with BE-related neoplasia who achieved CE-IM were eligible for inclusion and classified as delayed or on-time for endoscopic surveillance. Patients were prospectively enrolled and participated in structured virtual interviews designed to explore barriers and facilitators to on-time care. A rapid qualitative analysis approach was applied, continuing until thematic saturation was reached. Thirty-nine patients were interviewed: 22 (56.4%) were delayed, and 17 (43.6%) were on-time for surveillance. Patients in the delayed group had longer mean BE segment lengths and a higher prevalence of tobacco use. Geographic distance from the treatment center was the most frequently cited barrier to follow-up (n=17; 43.5%). Other common barriers were access limitations, financial concerns, misunderstanding of disease course, and test-related anxiety. Patient related drivers of delay in post-EET surveillance are largely logistical, socioeconomical, and psychological in nature. Solutions to reduce the significant burden on the patient and achieve timely surveillance may include transitioning patients back to their local endoscopists after CE-IM or incorporating non-endoscopic surveillance methods through patient centered approaches.

Concrete dams are hydraulic structures whose long-term safety depends on durability, thermal responsiveness, and time-dependent performance of the material, rather than only on initial strength. During their service life, concrete dams are affected by mechanical, thermal, fluid-related, and chemical factors. If these factors are not properly controlled, it may cause the concrete to deteriorate. This paper presents a state-of-practice comparative review based on the analysis of international standards, laboratory testing results, and operational monitoring practices, with a focus on analyzing performance gaps and decision-oriented implications for Turkish dam engineering practice. The mechanical, transport-related, thermal, and aging properties of mass concrete are examined with respect to the main processes that can cause it to undergo degradation. Global norms, lab testing methods, and surveillance methods are considered during the comparison with the ones that are used in Turkey. The evaluation demonstrates that one of the major challenges in Turkey is the complexity of incorporating long-term material monitoring records with construction-phase quality assurance procedures: whereas global strategies rely on synchronized lab profiling, non-destructive evaluation, and structural health monitoring. The main contribution of this study is to join global standards, operational oversight methods, and material-level performance measures into a life cycle-oriented evaluation framework that may be used for building concrete dams. This configuration may enhance engineering decision-making about planning for durability, preventing thermal fissures, and monitoring long-term performance. The results may be applied to improve surveillance methods and design methods that are based on durability in current and future concrete dam projects.

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is one of the most common causes of cancer mortality worldwide, and most patients experience local and/or distant recurrence at some point during follow-up.Aim: This review aims to present the follow-up protocols used in Poland and worldwide for patients undergoing surgical treatment for PDAC.Materials and methods: The current literature focusing on follow-up protocols in Poland and worldwide. Results: Currently, there are no unified international standards for postoperative follow-up for PDAC. Polish criteria for this issue also do not exist – the optimal method of surveillance and its duration remain undetermined. Discussion: The impact of early detection and treatment of recurrence on survival and quality of life is unknown. Early detection of recurrence potentially offers greater treatment options due to systematic improvements in the treatment of local recurrence and distant metastases, but it may also be associated with increased costs for the payer, without clearly translating into benefits resulting from longer survival. Currently, there are no clear recommendations on this issue - it seems necessary to conduct prospective studies to assess whether increased postoperative surveillance can translate into improved survival of patients with PDAC.Conclusions: Multidisciplinary collaboration in developing uniform, nationwide oncological surveillance principles can enable effective supervision of patients with PDAC and bring health benefits.Revelance of the study to the development of the field: This summary of the applicable guidelines and the proposed corrective actions proposed by the authors can translate into progress and improved treatment outcomes in this challenging therapeutic area.

During epidemics, emergency department (ED) syndromic surveillance of patient arrivals provides timely but non-virus-specific assessment of epidemic intensity. Surveillance of severe infection outcomes (intensive care admission or death) is less timely because outcomes can take weeks to occur. Time series models can be used to estimate the frequency of severe infection outcomes due to viruses. We developed and evaluated daily time series modelling applied to linked ED, infection and outcomes data from Australia to better predict population and health system burden during acute respiratory virus epidemics. In retrospective daily surveillance emulation, generalised additive models nowcasted (short-term forecast) the frequency of ED arrivals attributable to each of influenza and COVID-19 that will have a severe infection outcome within 28 days. Daily nowcasts spanned days -29 to -4 from each date for which surveillance was emulated. To validate the method, nowcasts were compared with subsequently observed severe infection outcome frequencies for December 2021 through February 2023. During this period, the mean daily day -4 nowcast error was 2.7 (34.2%), compared with 3.5 (43.8%) if outcomes known at day -1 were used. With increasing real-world data availability, this method could improve rapid, automated epidemic assessment for timely public health action.

DNA methylation analysis of self-collected samples has shown potential for primary endometrial cancer detection. Here, we aimed to explore DNA methylation testing as a non-invasive alternative for post-treatment surveillance. Endometrial cancer patients (n = 43) without recurrence collected pre- and post-treatment cervicovaginal self-samples and urine at home. Additionally, 17 patients with recurrence provided these samples at the time of recurrence. Healthy controls were used as reference. In total, 207 cervicovaginal self-samples and 203 urine samples were tested for nine markers (ADCYAP1, BHLHE22, CDH13, CDO1, GALR1, GHSR, HAND2, SST and ZIC1) using quantitative methylation-specific PCR. Diagnostic performance was assessed using previously established logistic regression models. In patients without recurrence, most marker levels decreased post-treatment compared to pre-treatment, in both sample types. DNA methylation positivity in cervicovaginal self-samples reduced from 90.7% pre-treatment to 19.5% post-treatment (p < .0001). In urine, a decrease from 80.5% to 20.9% was observed (p < .0001). In patients with recurrence, DNA methylation levels of CDH13, CDO1, GALR1, GHSR and HAND2 in cervicovaginal self-samples, and CDO1, GHSR and HAND2 in urine, were higher than in patients without recurrence. DNA methylation positivity was 62.5% in cervicovaginal self-samples and 58.8% in urine among patients with any recurrence, and 100% in cervicovaginal self-samples and 90.0% in urine of patients with a local recurrence specifically. These findings support methylation-based testing as a promising post-treatment surveillance method for endometrial cancer patients. This non-invasive approach could reduce the follow-up burden on patients and healthcare, alleviating challenges related to resource constraints while improving patient comfort.

Patients with ascending thoracic aortic aneurysms (ATAA) only have a 10-20% chance of survival upon aneurysm rupture. If aneurysm growth is detected, however, surgical repair can mitigate the rupture risk. Current CT- and MRI-based surveillance methods require frequent hospital visits, increasing healthcare costs and reducing patient adherence. Pulse-based measurements, which could eventually be performed at home, are an attractive but poorly explored alternative. In this study, we investigated the feasibility of using frequency analysis of the pulse waveform to determine whether the ATAA radius or wall stiffness has changed. We first determined a correction to the standard 0D model for blood flow through curved vessels, using fluid-structure-interaction (FSI) modeling as ground truth. We then studied idealized ATAA geometries and found that changes in the size of an aneurysm led to consistent changes in the Fast Fourier Transform of the outlet pressure waveform. Furthermore, when the vessel stiffened and grew, these changes were detectable by comparing the low versus high frequency response of the outlet pressure. Similar trends were observed for FSI simulations based on retrospective study of longitudinal scans of a patient over 5 years. This study showed that analyzing the pulse waveform, as clinically measurable by surface tonometry, has potential to form the basis for an at-home method for detecting ATAA growth.

Nasopharyngeal carcinoma (NPC) remains a major challenge due to the high incidence of recurrence, often leading to therapeutic failure. Early detection of recurrence is critical, yet effective surveillance methods are limited. This study aims to evaluate the utility of Epstein-Barr virus (EBV) DNA detection in nasopharyngeal brush samples for identifying recurrent NPC. A total of 187 NPC patients who had undergone radical radiotherapy with or without chemotherapy were included. EBV DNA levels in both nasopharyngeal brush and plasma samples were analyzed using real-time quantitative PCR. Head and neck MRI, sinus endoscopy examination, and biopsy of suspicious lesions were used as the gold standard to confirm recurrence. Patients without recurrence after more than 1 year of follow-up served as controls. Nasopharyngeal brush EBV DNA detection demonstrated significantly higher sensitivity (95.7%) for detecting recurrence compared to plasma EBV DNA testing (61.4%), with comparable specificity (94.0% vs. 96.6%). The positive predictive value was similar between methods, whereas the negative predictive value was markedly higher for the nasopharyngeal brush group (97.3% vs. 80.7%). These findings suggest that EBV DNA detection in nasopharyngeal brush samples is a highly sensitive and minimally invasive supplementary tool for monitoring NPC recurrence. This approach offers superior sensitivity and an improved negative predictive value compared to plasma EBV DNA testing, and may enhance early surveillance and clinical management of NPC recurrence.

Accurate detection of adverse events (AEs) and patient harm is fundamental for improving patient safety in hospitals. The primary objective of this study is to evaluate the sensitivity of the Institute for Healthcare Improvement (IHI), the Global Trigger Tool (GTT) in detecting adverse events compared with the Assurance of Quality in Surgery (AQC) surgical database and the voluntary Critical Incident Reporting System (CIRS) in a Swiss hospital setting. Specifically, we aim to quantify the detection gap between these 3 systems. A retrospective review was conducted over a 12-month period between January 1st and December 31st, 2024. Analyzing data from 3 distinct surveillance methods: (1) Voluntarily submitted reports via the Critical Incident Reporting System (CIRS) were reviewed for all reported incidents; (2) For the GTT, 20 monthly randomly selected medical records of surgical inpatients (aged 18+, minimum 24-h stay, excluding orthopedics) were reviewed monthly; (3) Assurance of Quality in Surgery (AQC) data was manually entered for all operated surgical inpatients (excluding orthopedics), with rigorous quality checks performed by the authors. The findings from these systems were then compared. An evaluation of CIRS for 2024 revealed only one reported case within the surgical department. Concurrently, AQC statistics indicated 283 completed surgical inpatient procedures, with 17 (6.01%) resulting in complications (surgical and nonsurgical). Furthermore, among 596 stationary patients treated in 2024, the GTT identified 58 patients (9.73%) with at least one AE. Number of overlapping cases between the GTT and the AQC reporting systems was 14. AQC is a particularly valuable tool, especially for operated patients. The Global Trigger Tool (GTT) boasts a wider range of applicability. Its strength lies in its ability to systematically identify potential adverse events through the review of patient records of operated and not operated patients. Sole reliance on voluntary reporting is insufficient for comprehensive adverse event detection. We advise the hospitals to adopt an additional system to complement the voluntary reporting CIRS system.

Enhanced molecular surveillance for gonococcal resistance during doxycycline post-exposure prophylaxis implementation.

Suicidal behaviors present public health challenges worldwide. Surveillance and research aimed at preventing suicidal behaviors often rely on administrative data. Existing systematic reviews examine the validity of methods for identifying suicidal outcomes in administrative datasets but do not include codes based on the International Classification of Diseases, Tenth Revision (ICD-10), despite their widespread use for >2 decades. This rapid review evaluates methods for identifying suicidal behaviors using ICD-10 codes. We searched PubMed and PsycINFO to identify relevant studies worldwide. Studies were included if they measured suicidal behaviors, used ICD-10 codes, validated the behaviors against a gold standard, and provided measures of accuracy (eg, specificity, sensitivity). We extracted data on study populations, data sources, ICD-10 codes used, gold-standard comparators, and accuracy measures from included studies. Of 2246 studies identified, 9 met our inclusion criteria. For methods identifying suicide attempts, sensitivity ranged from 19% to 45%, specificity from 47% to 99%, positive predictive value from 21% to 82%, and negative predictive value from 65% to 92%. For methods identifying self-harm, sensitivity ranged from 12% to 85%, specificity from 98% to 100%, positive predictive value from 64% to 100%, and negative predictive value from 86% to 87%. Only sensitivity was reported for suicide death (range, 78%-97%). Findings indicate that sensitivity and positive predictive value for identifying suicide attempts using ICD-10 codes are low. Studies and surveillance methods relying on these codes might substantially underestimate rates of suicidal behaviors. ICD-10 codes may provide higher accuracy for identifying self-harm and other nonfatal suicidal behaviors than codes from the International Classification of Diseases, Ninth Revision.

Opioid-related adverse events (AEs) resulting in or following an ED visit are well described. Less is known about AEs due to opioid administration in the ED, whose detection is limited by the high frequency of administration and poorly specific surveillance methods. We studied the use of the ED Trigger Tool (EDTT) for detection of AEs from high-risk opioid administration in the ED. This is a secondary analysis of a multicenter retrospective study of the EDTT for two selected triggers: M2- ≥ 3 doses of hydromorphone administered and M18- opioid + benzodiazepine administration. We applied the EDTT to an 18-month extract of data from three sites and reviewed a balanced sample of ~3000 records/site using a two-tiered approach, characterizing opioid-related AEs by occurrence, type, and severity. Analysis is descriptive. A total of 13,601/450,852 visits (3.0%) across three sites included one of these triggers: M2 (6447; 1.4%); M18 (6201; 1.4%); or both (853; 0.2%). In our sample of 8719 records, 458 (5.3%) included at least one of these triggers (78 with M2, 347 with M18, and 33 with both). Reviewer agreement was high (Kappa = 0.94). We identified 124 opioid-related ED AEs among 120 triggered visits (26.2%): M2 (37/78 visits; 47.4%); M18 (76/347 visits; 21.9%), and both (7/33 visits; 21.2%). There were no site differences in opioid-related ED AE detection. Common AEs included hypotension, hypoxia, allergic reactions, and delirium, mostly resulting in temporary harm but 30% requiring urgent intervention. In our sample, 5% of visits included high-risk opioid administration, of which 26% included an opioid-related AE. AE rates were similar across sites, with expected variability in type and severity across triggers and sites. The EDTT is a useful approach for AE detection. Triggers focusing on high-risk opioid administration may have a more favorable yield as a surveillance strategy.

Rural United States (U.S.) residents typically have lower access to health resources and greater chronic disease risk than urban counterparts. Policy, systems, and environmental (PSE) change strategies can facilitate equitable access to health-promoting resources and improve health-promoting behaviors such as breastfeeding (BF), healthy eating (HE), and physical activity (PA). This qualitative study grounded in the Social Ecological Model examined how PSE strategies promoting BF, HE, and PA are tracked in rural communities. Nine practitioners, representing eight states, were interviewed in August 2020. Participants' organizations included Cooperative Extension (n = 4), non-Extension SNAP-Ed (n = 1), county health department (n = 1), and other community organizations/coalitions (n = 3). A 31-item interview guide based on a PSE framework was developed to assess PSE changes, evaluation strategies, and challenges pertaining to BF, HE, and PA in rural communities. Synthesis coding was completed using a content analysis framework to summarize reported surveillance-specific information, systems, tools, methods, and needs. We identified three themes around rural community needs: (1) localized, accurate, and feasible surveillance methods to assess PSE changes; (2) systems assistance with data collection and monitoring; and (3) easier access to their own and comparison communities' data to inform decisions. Robust systems are required for data collection, monitoring, and analysis to evaluate the effectiveness of PSE change strategies. Greater surveillance/evaluation infrastructure and capacity in rural communities will help ensure these communities have access to data to inform PSE change strategies. Surveillance methods are also needed that extend beyond individual-level behaviors to track the impact of PSE factors on population health.

This study examines the effectiveness of utilizing Unmanned Aerial Vehicle (UAV) technology in supporting land border security operations along the Indonesia–Malaysia border. The research addresses the increasing complexity of transnational threats that challenge conventional surveillance methods and require adaptive defense strategies. The objective of this study is to analyze the contribution of UAVs to border security operations, identify implementation constraints, and formulate optimization strategies for sustainable utilization. A qualitative descriptive-analytical method was employed, with data collected through in-depth interviews, field observations, and document analysis involving military operational units, border security task forces, and local stakeholders in the Kalimantan border area. The findings indicate that UAVs significantly enhance early detection, real-time aerial surveillance, and tactical decision-making. However, their effectiveness remains constrained by limited operator capability, inadequate infrastructure, and restricted logistical and budgetary support. The study concludes that integrating UAV systems into command and control structures, improving operator competence, and strengthening intersectoral cooperation are essential to establishing a modern and adaptive border security system.

Borax (sodium tetraborate decahydrate; Na₂B₄O₇·10H₂O) is prohibited for use in processed foods in Indonesia, necessitating analytically defensible surveillance methods for routine monitoring. This study aimed to validate a curcumin-based UV–Vis spectrophotometric assay and to apply rapid qualitative screening to nugget products marketed in Gorontalo, Indonesia. Qualitative screening was performed using the flame test and turmeric paper test on six samples (A1–C2) collected in October 2025. For the UV–Vis method, wavelength optimisation using a 500 µg/mL borax standard identified 427 nm as the operational measurement wavelength. Calibration standards (1–9 µg/mL) were analysed in triplicate, and validation was conducted for linearity, LOD, LOQ, repeatability precision, and spike-recovery accuracy (80%, 100%, and 120% levels). The method exhibited excellent linearity (y = 0.1082x + 0.0147; R² = 0.9995), with LOD and LOQ of 0.25849 µg/mL and 0.86165 µg/mL, respectively. Repeatability showed 1.40% RSD, while spike-recovery testing demonstrated high trueness (mean recovery 99.403%) with low dispersion (%RSD 0.201–0.252%). All nugget samples were negative by both qualitative screening assays. However, UV–Vis quantitative values for the nugget extracts were not available in the recorded dataset; therefore, borax-equivalent concentrations in mg/kg could not be reported for the marketed samples. Overall, the validated curcumin UV–Vis procedure demonstrates strong analytical performance and is suitable for confirmatory monitoring, provided that future surveillance applies the method directly to each sample extract to enable defensible classification as ND (LOD), LOQ, or quantified (≥LOQ).

Endoscope reprocessing is a time-consuming, multi-step process, and ongoing microbial surveillance is necessary to ensure effective reprocessing and safe storage. Despite this, traditional surveillance methods, such as cultures, are not often carried out due to time and cost constraints, providing only delayed end point results from specific locations, with no insight into biofilm formation, disinfection efficacy, or any variability related to device design. Within this study, the efficacy of plasma activated water (PAW) disinfection (and subsequent regrowth) within endoscopic test pieces was investigated using bacterial bioluminescence enabling real time and in situ monitoring of biofilm formation and treatment efficacy. Real time imaging of bioluminescent Pseudomonas aeruginosa PAO1 SEI MCS5-lite was used to track biofilm growth within translucent PVC endoscopic test pieces across regions of interest using analysis of bioluminescent intensity. Results demonstrated that biofilm accumulation was more prominent around connectors compared to other regions of the test pieces. Disinfection with PAW achieved a significant 96.45% reduction in biofilm density (determined by culture) and a 93.08% reduction in bioluminescence (relative light units). However, percentage reduction in bioluminescence ranged from 77% to 95% across regions indicating lack of uniformity of treatment. Subsequent testing with plasma activated disinfectant (PAD) showed consistent biofilm reduction across all regions, with no variability between connectors and other regions as observed with PAW and other treatments. In conclusion, bioluminescence can be used to assess efficacy of disinfectants and effect of endoscope design by tracking biofilm density in real time and in situ.

The demand for advanced, autonomous technologies in aerial mapping and surveillance has grown exponentially across industries such as environmental monitoring, urban planning, and security. This work introduces the development of an autonomous drone system designed to perform real-time mapping and surveillance with high efficiency. The proposed system integrates advanced navigation algorithms, precision sensors, and robust data processing capabilities, enabling it to operate with minimal human intervention. Notable features include GPS-based autonomous flight planning, real-time obstacle detection and avoidance, and high-resolution data capture through integrated LiDAR and RGB cameras. Additionally, 3D mapping via photogrammetry generates precise terrain models from captured video footage, enhancing the system’s mapping accuracy. The drone’s onboard processing unit allows for real-time data processing and live streaming to a ground station, enabling remote monitoring without any latency. Field trials and initial tests have confirmed the drone’s ability to navigate diverse terrains, autonomously adjust flight paths, and provide high-accuracy, real-time mapping updates. This system offers a scalable, cost-effective alternative to traditional, laborintensive aerial surveillance methods, providing enhanced efficiency and precision. This work aims to advance the research in autonomous aerial systems by tackling significant challenges, including real-time obstacle avoidance, data processing efficiency, and system reliability in varying environments. Future improvements may focus on enhancing battery life, increasing flight endurance, and enabling multi-drone coordination to extend the scope and capabilities of the system across a wider range of applications.