Search Results (469)

Rapid antigen tests targeting SARS-CoV-2 nucleocapsid protein were essential for decentralised testing during the COVID-19 pandemic. Independent performance evaluations are essential to support regulatory approval and inform clinical implementation, particularly in resource-limited settings. This study presents a retrospective analytical and operational evaluation of two instrument-based fluorescent immunoassays (FIAs): the PCL COVID-19 Ag Rapid FIA and LumiraDx SARS-CoV-2 Ag Test. Analytical sensitivity was determined using recombinant nucleocapsid protein and viral cultures. Clinical performance was assessed using residual clinical specimens (n = 110) with RT-PCR as a reference, stratified by cycle threshold (Ct). Operational characteristics were assessed using a structured Likert framework. Overall sensitivity was 63% (51–73) for PCL and 95% (88–99) for LumiraDx. For Ct ≤ 25, sensitivity increased to 93% and 100%. Specificity was ≥97% for both. LumiraDx maintained sensitivity (83–94%) at Ct 25–30, whereas PCL did not detect any positives in this range. The limit of detection was 39 pM (PCL) and 0.6 pM (LumiraDx). Operational usability was high for both (90% PCL, 87% LumiraDx). LumiraDx showed higher analytical sensitivity across a broader viral load range, supporting primary diagnostic use, whereas PCL was limited to high viral loads. This evaluation provides a reproducible framework for rapid diagnostic assessment during emerging outbreaks. Full article

Background/Objectives: The coronavirus disease 2019 (COVID-19) pandemic profoundly disrupted global respiratory virus circulation, with sharp declines during 2020–2021, followed by a resurgence after the relaxation of public health measures. In South America, post-pandemic respiratory virus dynamics remain insufficiently characterized, particularly in ecologically diverse regions. Arequipa, a high-altitude city in southern Peru, has unique environmental conditions, including marked seasonal temperature variability, that may influence viral transmission. Methods: We performed a cross-sectional analysis of 21,784 nasopharyngeal swabs collected from symptomatic patients at four major hospitals between June 2021 and September 2023. All samples were tested for SARS-CoV-2 by RT-qPCR. Because routine screening for other respiratory viruses was implemented only in SARS-CoV-2-negative cases during the study period, a subset of SARS-CoV-2-negative samples was subsequently analyzed for influenza A virus (IAV), influenza B virus (IBV), and respiratory syncytial virus (RSV) using VIASURE assays. Viral circulation patterns were evaluated by year, month, and epidemiological week. Meteorological data were obtained from the SENAMHI–La Pampilla station. Logistic regression models were used to assess epidemiological and climatic predictors of viral detection. Results: SARS-CoV-2 positivity declined from 20.0% in 2021 to 8.8% in 2023. Conversely, detection of other respiratory viruses among SARS-CoV-2-negative samples increased from 0.8% in 2021 to 29.0% in 2023 (p < 0.01). Temporal increases in detection were observed during 2022–2023, particularly for IAV and RSV. In exploratory analyses, calendar year and relative humidity were associated with IAV and RSV detection, while age and temperature variables were associated with IBV. Conclusions: Climatic and demographic variables were associated with changes in viral detection for IAV, IBV, and RSV during the post-pandemic transition period in Arequipa. These findings describe patterns of viral detection within SARS-CoV-2-negative symptomatic patients and should be interpreted as surveillance-based observations rather than population-level estimates. Strengthened integrated epidemiological and genomic surveillance will be essential for vaccine planning and outbreak preparedness in the post-pandemic era. Full article

Infectious disease outbreaks continue to pose a significant threat to global health, underscoring the importance of timely detection and reliable reporting for effective interventions. Traditional reporting systems often rely on hierarchical data flows, which introduce delays, inconsistencies, and vulnerabilities, as highlighted during the COVID-19 pandemic. Blockchain, a disruptive technology, offers a promising solution. This study proposes a blockchain-based infectious disease reporting system built on Hyperledger Fabric that supports multi-level reporting and governance across national health systems. The architecture preserves hierarchical structures while enabling real-time reporting across authorized health stakeholders. It separates public test results from sensitive patient information, with private data secured via Private Data Collections and anchored using cryptographic hashes. Smart contracts enforce role-based access and validation, ensuring data integrity and controlled oversight. The system prototype was deployed within Docker containers and evaluated using illustrative COVID-19 case data. Network performance was benchmarked using Hyperledger Caliper, measuring throughput, latency, and resource utilization. The results demonstrate proper system functioning and stable transaction processing under the tested experimental conditions, supporting the feasibility of the proposed architecture for privacy-preserving multi-level infectious disease reporting systems. Full article

Background/Objectives: Nosocomial outbreaks of viral respiratory infections strain healthcare systems and endanger patients and healthcare workers (HCWs). We describe two large nosocomial outbreaks with the SARS-CoV-2 Alpha variant, during its initial emergence in Germany, to assess transmission dynamics, effectiveness of control measures, and challenges in managing highly transmissible respiratory viruses. Methods: Confirmed cases were inpatients, HCWs, or their contacts testing SARS-CoV-2-positive since 1 January 2021 (Hospital A [HA])) or 21 January 2021 (Hospital B [HB])) with N501Y and delH69/V70 spike gene mutations. We conducted case interviews, reviewed medical records and shift schedules, and performed sequencing, genome reconstruction, and phylogenetic analysis. We describe cases, transmission chains, and control measures. Results: HA reported 18 patient cases, 20 HCW cases, and 33 community cases (N = 71). HB reported 48 patient cases, 43 HCW cases (13 in a COVID-19 ward), and 27 community cases (N = 118). In-hospital transmission occurred patient-to-patient, HCW-to-patient, patient-to-HCW, and HCW-to-HCW. HA halted admissions immediately after the initial cases; HB implemented measures gradually. Regular testing detected pre-symptomatic (HA = 6; HB = 18) and asymptomatic cases (HA = 3; HB = 13). Testing of agency staff was incomplete. The suspected primary case was an HCW in HA and a patient in HB who required resuscitation shortly after admission. Conclusions: Early COVID-19 outbreaks offer valuable lessons for managing emerging nosocomial outbreaks of highly transmissible respiratory viruses. Our findings provide empirical evidence for effective interventions, including rapid response, testing, HCW protection, and rigorous contact tracing in high-risk emergency situations. Managing agency staff remains a major challenge. Full article

Background/Objectives: Influenza A (IAV) and influenza B (IBV) viruses pose significant public health threats, with varying epidemiology and immune responses. Limited subtype-specific cytokine data exist for influenza in Saudi Arabia. This study conducted molecular surveillance on 380 NPAs from patients at King Khalid University Hospital (KKUH) in Riyadh, Saudi Arabia, during winter seasons (2020–2023). Methods: NPA samples were collected from hospitalized patients presenting with fever (>38 °C) and respiratory symptoms. RNA was extracted using the QIAamp Viral RNA Kit, followed by RT-PCR for IAV (H1N1, A/H3N2) and IBV detection. Quantitative real-time PCR profiled mRNA expression of 17 cytokines/chemokines in IAV-positive (n = 65) and IBV-positive (n = 20) samples, normalized to GAPDH using the 2^−ΔΔCq method. Appropriate statistical tests were applied (p < 0.05 significant). Results: Results showed 17.11% IAV positivity (7.89% A/H1N1, 9.21% A/H3N2) and 5.26% IBV. A/H3N2 predominated, increasing from 6.67% (2020/21) to 12.30% (2022/23). Males had higher IAV rates (25.88% vs. 10.00% females, p < 0.05), while IBV was higher in females (6.67% vs. 3.53%). Age-wise, 0–4 years had peak IAV (28.42%, p < 0.05); IBV peaked at 5–14 years (10.91%). IAV elicited higher mRNA expression IFN-α, IL-10, IL-13, and CCL-2 (p < 0.05); IBV showed elevated IL-1α, IL-6, and IL-33 (p < 0.05). Within IAV, A/H1N1 had higher IL-4, IL-10, IL-13, and IL-17; A/H3N2 elevated TNF-α, IL-6, IL-22, CCL-3, and CCL-4 (p < 0.05). Conclusions: These findings highlight subtype-specific inflammatory profiles and demographic disparities in Saudi Arabia, informing targeted interventions. Post-COVID resurgence underscores surveillance needs amid travel and gatherings. Insights into cytokine dynamics aid prognosis and therapeutics, emphasizing regional molecular monitoring for vaccine optimization and outbreak prevention. Full article

Several researchers have documented the occurrence of the unfamiliar severe acute respiratory syndrome coronavirus 2 ribonucleic acid (also known as SARS-CoV-2 RNA) in various raw wastewater (WW) samples analyzed globally. The efficiency of strategic WW-based epidemiology (WBE) approach as a timely cautioning tool for human coronavirus disease-2019 (COVID) and other similar outbreaks is highly promising. This strategy offers a cost-effective, population-wide surveillance tool that can detect rising case trends, from days to weeks before clinical reports, thus enabling proactive public health interventions. This study aimed to detect the occurrence of the viral genome in WW over four seasons, which contributes to the database for multi-plant surveillance research in South Africa. About 480 WW influent samples were amassed from ten sampling points situated in nine wastewater treatment facilities (WWTFs) in Amathole District Municipality (ADM) located in the Province of Eastern Cape (EC), South Africa (SA). The study was carried out for a period of one year. Quantitative real-time polymerase chain reaction (i.e., RT-PCR) was operated to identify the viral genomes in the respective total RNA samples. Of the 480 extracted RNA samples, 210 (44%) were positive with viral genome copies (gc) that ranged from 700 to 40,000 GC/mL. Our results were contrasted with existing COVID-19-positive cases throughout the COVID omicron wave in the ECP. Variations in gc were observed across different seasons, with the highest GC observed in winter. In contrast, there were significant inconsistencies in the existing data of COVID-19 clinical cases, thus indicating no connection between both data. However, with more similar studies, advanced innovative WBE strategies could possibly act as prompt warning tools to signal public health officials about potential future outbreaks. Full article

Following the COVID-19 pandemic, researchers have increasingly focused on monitoring the spread of the virus and improving methods to detect changes in the SARS-CoV-2 genome. Although clinical surveillance provides direct and reliable results, it has limited applicability. Wastewater-based epidemiology (WBE) has therefore emerged as a valuable, non-invasive complementary tool for disease surveillance. It provides a comprehensive picture of virus circulation in a population, including asymptomatic individuals and those who do not seek healthcare. In addition, it facilitates early detection of outbreaks and the collection of epidemiologic data at the community level. However, WBE also presents technical challenges, including variations in sampling and testing protocols, the presence of inhibitors that affect viral RNA extraction, and the need for standardised procedures between studies. These challenges should be addressed for possible future infectious disease outbreaks. One of the challenges facing researchers was to develop efficient methods that could overcome the extraction and detection problems related to inhibitors present in wastewater. To this aim, this systematic review highlights the potential use of WBE, the variety of techniques, and the most effective methods for the detection and quantification of SARS-CoV-2 in wastewater samples. A reproducible electronic search of the literature was conducted in the Web of Science (WoS) and PubMed databases for articles published between 2020 and 2024. Our search revealed that the majority of observed WBE applications emphasised a correlation between SARS-CoV-2 RNA concentration trends in wastewater and epidemiological data. Another relevant issue that the articles often discussed and compared was the techniques used in different steps of sample processing, such as sample collection, concentration and detection, hence the lack of standardised procedures. This paper provides a framework regarding previous research on WBE to gain a better understanding that will lead to functional solutions. Full article

The COVID-19 pandemic underscored the urgent need for rapid, reliable, and safe laboratory workflows that ensure both diagnostic accuracy and biosafety for laboratory personnel. We developed a comprehensive approach for SARS-CoV-2 detection using saliva-based RT-qPCR that spans the entire process from sample transfer to final disposal. This workflow integrates biosafety principles with efficient diagnostic procedures, ensuring safe handling, minimized exposure risks, and reliable molecular testing. Critical components included biosecurity, standardized protocols for sample receipt, secure transfer, safe processing, and environmentally responsible disposal. By applying a holistic safety framework, we not only protected laboratory staff during the pandemic but also established a model that can inform preparedness for future emerging infectious disease threats. This approach demonstrates how laboratory safety and diagnostic efficiency can be simultaneously achieved, offering a reference for institutions seeking to balance biosafety and public health needs in outbreak situations. Full article

The exceptional olfactory capabilities of trained detection dogs demonstrate high potential for identifying infectious diseases. However, safe and standardized canine training requires specific chemical targets rather than infectious biological samples. This study presents an analytical proof-of-concept combining untargeted metabolomics and machine learning (ML) to decode the specific odor profile of SARS-CoV-2 infection. Using headspace solid-phase microextraction gas chromatography coupled with time-of-flight mass spectrometry (HS-SPME-GC/MS-ToF), axillary sweat samples from 76 individuals (SARS-CoV-2 positive and negative) were analyzed. Data preprocessing and dimensionality reduction were performed to feed a Partial Least Squares-Discriminant Analysis (PLS-DA) model. The optimized model achieved an overall accuracy of 79%, with a specificity of 89% and sensitivity of 70% in external validation, identifying a specific panel of Volatile Organic Compounds (VOCs) as discriminant biomarkers. The optimized model achieved robust classification performance, effectively distinguishing infected individuals from healthy controls based solely on their volatilome. Six VOCs were found to be consistently presented in COVID-19-positive individuals. These compounds were proposed as candidate odor signatures for constructing artificial training aids to standardize and accelerate the training of detection dogs. This study establishes a framework where machine learning-driven metabolomic profiling directly informs biological sensor training, offering a novel synergy between ML and biological intelligence in disease detection. This study establishes a scalable computational framework to translate biological samples into chemical data, providing the scientific basis for designing safe, synthetic K9 training aids for future infectious disease outbreaks without the biosafety risks associated with handling live pathogens. Full article

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had major social and economic consequences worldwide. Whole genome sequencing (WGS) is essential for genomic monitoring, enabling tracking of viral evolution, detection of emerging variants, and identification of introductions and transmission chains to inform timely public health responses. Here, we compile and harmonize SARS-CoV-2 genomic data generated by multiple laboratories across Kazakhstan together with publicly available sequences to provide a national overview of genomic dynamics across successive epidemic waves from 2020 to 2022. We analyzed 4462 genomes deposited in GISAID (including 340 generated in this study), of which 3299 passed Nextclade quality filters, and summarized lineage turnover across major phases (pre-VOC, Alpha, Delta, Omicron BA.1/BA.2, Omicron BA.4/BA.5, and a later recombinant-dominant period). Sequencing intensity varied markedly over time (0.60‰ of confirmed cases during Delta vs. 11.57‰ during the Omicron BA.5 wave), suggesting that lineage diversity and persistence may be underestimated. Pre-VOC circulation included ≥12 Pango lineages with evidence of multiple introductions and sustained local transmission, including a Kazakhstan-restricted B.4.1 lineage that emerged in Nur-Sultan/Astana and disappeared after April 2020. The Tengizchevroil oilfield outbreak comprised B.1.1 viruses with phylogenetic support for ≥three independent introductions. Alpha and Omicron waves were characterized by repeated introductions and heterogeneous origins, whereas Delta was dominated by AY.122 with an additional distinct AY.122 cluster; a notable BF.7 local transmission event was observed during BA.5. We also highlight locally enriched non-lineage-defining mutations. Overall, recurrent importations and variable local amplification shaped SARS-CoV-2 dynamics in Kazakhstan, while interpretation is constrained by strongly time-skewed sequencing. Full article

Following the normalization of the COVID-19 pandemic, the focus of wastewater-based epidemiology (WBE) must be broadened from SARS-CoV-2 to encompass surveillance of other major infectious diseases, particularly for pathogens where conventional clinical monitoring systems exhibit inherent surveillance gaps. In this study, we conducted a continuous two-year WBE study (January 2023 to December 2024) across three high-population-density cities in Guangdong, China to establish epidemiological baselines for enteric diarrheal viruses. We analyzed monthly raw wastewater samples from major treatment plants using advanced molecular methods, including digital PCR (ddPCR) for viral load quantification and targeted high-throughput sequencing (tNGS) for genotypic analysis. Our findings revealed diverse circulation patterns among the monitored enteric viruses. Astrovirus (AstV) had the highest detection rate (100%), reflecting its broad endemic distribution, while Norovirus genogroup II (NoV GII) exhibited relatively high viral loads (median 4 × 10⁴ copies/mL) and presented explosive seasonal peaks (significant upward trend in spring.), highlighting its epidemic potential. Furthermore, distinct spatiotemporal patterns were observed, with Sapovirus showing a significant summer peak in Foshan city, contrasting with the winter/spring peaks in the other cities. The tNGS results demonstrated similar sensitivity to RT-PCR in virus detection, and sequencing analyses uncovered the co-circulation and periodic shifts in dominant viral genotypes, such as the emergence of multiple NoV and AstV lineages. This longitudinal WBE surveillance successfully established critical baseline data and demonstrated significant regional heterogeneity in viral circulation, providing essential, complementary data to inform public health strategies for preventing diarrheal outbreaks in urban settings. Full article

Human adenovirus type 3 (HAdV-3) in the species Mastadenovirus blackbeardi is a frequent cause of hundreds of respiratory infections in Japan, with outbreaks varying in clinical severity. Such a high frequency of cases could be due to regular migration of novel variants or persistent circulation of endemic strains. Either scenario would require different measures to ameliorate the burden on public health. We designed a new cost-effective whole-genome sequencing protocol based on tiled amplicons and nanopore sequencing to clarify the circumstances behind the frequent outbreaks. This protocol was used with clinical samples collected between 2011 and 2020 from Japanese patients with acute respiratory illness (n = 110), resulting in near whole-genome sequences (~99% length) for 105 samples with high read coverage (~262.6 ± 192 reads). Phylogenetic analysis indicated sustained circulation of endemic strains in Japan during the analyzed decade and their relation to other strains worldwide with publicly available genome sequences. However, a comparison with other Japanese HAdV-3 strains circulating since 2023 suggested the public health measures introduced during the COVID-19 pandemic (2020–2022) indirectly affected the prevalence of circulating HAdV-3 variants. Additionally, our approach enabled the detection and partial sequencing (~71% completion) of co-infecting strains from the species Mastadenovirus caesari (n = 4) in the examined samples. The detection of adenoviruses belonging to different species in the same sample highlights how our protocol enhances the distinction of circulating viruses. In conclusion, these results and the introduced protocol will enable timely characterization and clinical interventions to mitigate this virus. Full article

Emerging and re-emerging viruses continue to pose major threats to public health. Their ability to adapt, cross species barriers, and spread rapidly can trigger severe outbreaks or even pandemics. Strengthening preparedness with comprehensive and efficient strategies is therefore essential. Here, we explore the key components of viral outbreak preparedness, including surveillance systems, diagnostic capacity, prevention and control measures, non-pharmaceutical interventions, antiviral therapeutics, and research and development. We emphasize the increasing importance of genomic surveillance, wastewater-based surveillance, real-time data sharing, and the One Health approach to better anticipate zoonotic spillovers. Current challenges and future directions are also discussed. Effective preparedness requires transparent risk communication and equitable access to diagnostics, vaccines, and therapeutics. The COVID-19 pandemic highlighted both the promise of next-generation vaccine platforms and the necessity of maintaining diagnostic capacity, as early testing delays hindered containment efforts. Countries adopted various non-pharmaceutical interventions: risk communication and social distancing proved to be the most effective, while combined workplace infection-prevention measures outperformed single strategies. These experiences highlight the importance of early detection, rapid response, and multisectoral collaboration in mitigating the impact of viral outbreaks. By applying best practices and lessons learned from recent events, global health systems can strengthen resilience and improve readiness for future viral threats. Full article

Background: Hospital-acquired influenza remains a persistent threat that amplifies morbidity, mortality, length of stay, and operational strain, particularly among older and immunocompromised inpatients. The COVID-19 era reshaped control norms—normalizing N95 use during surges, ventilation improvements, and routine multiplex PCR—creating an opportunity to strengthen hospital outbreak management. Methods: We conducted a targeted narrative review of WHO/CDC/Infectious Diseases Society of America (IDSA) guidance and peer-reviewed studies (January 2015–August 2025), emphasizing adult inpatient care. This narrative review synthesizes recent evidence and discusses theoretical implications for practice, rather than establishing formal guidelines. Evidence was synthesized into pragmatic practice statements on detection, diagnostics, isolation/cohorting, antivirals, chemoprophylaxis, vaccination, surveillance, and communication. Results: Early recognition and test-based confirmation are pivotal. For inpatients, nucleic-acid amplification tests are preferred; negative antigen tests warrant PCR confirmation, and lower-respiratory specimens improve yield in severe disease. A practical outbreak threshold is ≥2 epidemiologically linked, laboratory-confirmed cases within 72 h on the same ward. Effective control may require immediate isolation or cohorting with dedicated staff, strict droplet/respiratory protection, and daily active surveillance. Early oseltamivir (≤48 h from onset or on admission) reduces mortality and length of stay; short-course post-exposure prophylaxis for exposed patients or staff lowers secondary attack rates. Integrated vaccination efforts for healthcare personnel and high-risk patients reinforce workforce resilience and reduce transmission. Conclusions: A standardized, clinician-led bundle—early molecular testing, do-not-delay antivirals, decisive cohorting and Personal protective equipment (PPE), targeted chemoprophylaxis, vaccination, and disciplined communication— could help curb transmission, protect vulnerable patients and staff, and preserve capacity. Hospitals should codify COVID-era layered controls for seasonal influenza and rehearse unit-level outbreak playbooks to accelerate response and recovery. These recommendations target clinicians and infection-prevention leaders in acute-care hospitals. Full article

Background/Objectives: The purpose of this study was to identify shared and differing characteristics of individuals testing for both SARS-CoV-2 and MPXV in 2022 in the greater Houston metro area. Methods: Data from the Houston Electronic Disease Surveillance System (HEDSS) identified 7,754,198 SARS-CoV-2 PCR lab results and 1246 MPXVV PCR lab results in 2022. Three cohorts for analysis were created where tests were performed, as follows: those positive for both viruses, those negative for COVID-19 but positive for MPXV, and those positive for COVID-19 but negative for MPXV. Results: We identified 88 individuals positive for both viral infections, those negative for COVID-19 but positive for MPXV (n = 38), and those positive for COVID-19 but negative for MPXV (n = 96). While groups were generally similar in regard to demographics (age, sex, and race) and risk factors reported, key differences in timing of testing and risk factors were reported. Notably, there was statistically significant difference in the time between t-tests for dual-infected individuals (99 days) compared to MPXV-positive only (58 days, p < 0.01) or COVID-19 positive only (63 days, p < 0.01). Conclusions: In the setting of multiple disease outbreaks, the characteristics of infected patients may be largely similar. Some people with dual infection may show unusual test results or symptom patterns compared with those with only one infection. Large public health studies with robust reporting systems and laboratory screening are vital for early detection of dual infections. Public health strategies to educate providers and outreach teams enhance response during concurrent outbreaks. Further research is needed on behavior and risk factors in communities with simultaneous outbreaks. Full article