Proactive Surveillance Research Articles

Molecular Characterization of Multidrug-Resistant and Hypervirulent New Delhi Metallo-Beta-Lactamase Klebsiella pneumoniae in Lazio, Italy: A Five-Year Retrospective Study

Background/Objectives: Antimicrobial resistance represents a challenge to public health systems because of the array of resistance and virulence mechanisms that lead to treatment failure and increased mortality rates. Although for years the main driver of carbapenem resistance in Italy has been the Klebsiella pneumoniae KPC carbapenemase, recent years have seen an increase in VIM and NDM metallo-beta-lactamases (MBLs). We conducted a five-year survey of New Delhi Metallo-beta-Lactamase (NDM)-producing Klebsiella pneumoniae (NDM-Kpn) clinical isolates from the Lazio region, Italy; the study aimed to elucidate the molecular mechanisms underpinning their resistant and virulent phenotype. Methods: Antimicrobial susceptibility was evaluated by automated systems and broth microdilution. In silico analysis of acquired resistance and virulence genes was performed using whole-genome sequencing (WGS), molecular typing through MLST, and core genome multi-locus sequence typing (cgMLST). Conclusions: A total of 126 clinical NDM-Kpn isolates were collected from 19 distinct hospitals in the Lazio region. Molecular analysis highlighted the existence of NDM-1 (108/126) and NDM-5 (18/126) variants, 18 Sequence Types (STs), and 15 Cluster Types (CTs). Notably, 31/126 isolates displayed a virulence score of 4, carrying ybt, ICEKp, iuc, and rmp genes. This study identified a variety of NDM-Kpn STs, mainly carrying the blaNDM-1 gene, with a significant number linked to high-risk clones. Of these isolates, 24.6% showed high-level resistance and virulence, emphasizing the risk of the spread of strains that combine multi-drug-resistance (MDR) and virulence. Proactive surveillance and international collaborations are needed to prevent the spread of high-risk clones, as well as further research into new antimicrobial agents to fight antibiotic resistance.

Genomics-based timely detection of Dengue Virus type I genotypes I and V in Uruguay

This study details a genomics-based approach for the early detection of mosquito-borne pathogens, marked by Uruguay's first ever complete genomic sequencing of Dengue Virus type I genotypes I and V. This pioneering effort has facilitated the prompt identification of these genotypes within the country, enabling Uruguayan public health authorities to develop timely and effective response strategies. Further integrated into this approach is a climate-driven suitability measure, closely associated with Dengue case reports and indicative of the local climate's role in the virus's transmission in the country within the changing climate context. The detection of multiple DENV-1 genotypes co-circulating in Uruguay underscores the necessity for proactive surveillance, particularly at borders, to prevent the introduction and dissemination of novel viral strains within the country and the region. This approach aids in facilitating prompt public health responses and intervention strategies, which are crucial in mitigating the impact of dengue outbreaks.

Reactive surveillance of deaths involving a fall among the elderly in France, 2015 to March 2023

Abstract In 2022, France launched an elderly anti-fall plan with a goal to reduce fatal falls by 20% within 5 years. In a reactive monitoring approach ensuring comparability over the period, our study aims to develop an algorithm to identify deaths involving a fall using free-text medical causes in death certificates. This will enable proactive surveillance and evaluate plan effectiveness upon completion. We devised an algorithm based on textual search of fall-related expressions in death certificates. Performance metrics were assessed by contrasting algorithm-identified deaths with those flagged by ICD-10 fall-related codes. We compared also temporal dynamics between the algorithms from 2015 to 2021. Analysis was performed by age group, gender and place of death. Additionally, our algorithm enabled estimation of fall-related death trends from 2015 to 2023. The free-text algorithm exhibited robust performance, with a sensitivity and PPV of 95% when compared to deaths coded with an ICD-10 fall-related underlying or associated cause. Temporal trends between both were highly correlated (correlation coefficient=0.99). Instead of the usual 10000 deaths for fall, we revealed about 13000 deaths linked to falls considering both primary and associated causes. Among these, approximately three-quarters were coded as the underlying cause of death in ICD-10 coding. Regarding trends, the results are preliminary and suggested an increase in mortality rates related to falls detected by the algorithm between 2015 and 2022. Our approach distinguishes falls from other competing causes that often relegate them to secondary status in the chain of morbid events leading to death. With free-text medical causes accessible within 3 to 4 months, monitoring deaths involving falls can be done at a detailed geographic level and in a more reactive way. Looking ahead, we must also consider incorporating the impact of epidemics and/or heat waves to accurately evaluate the effectiveness of the anti-fall plan. Key messages • Algorithm using free-text of death certificates identify deaths involving falls. • Our innovative approach isolates falls from other competing causes, elevating their significance in death processes.

Sporothrix and Sporotrichosis: A South African Perspective on a Growing Global Health Threat.

Sporotrichosis is a disease that arises from a fungal infection caused by members of the Ascomycete genus Sporothrix. The disease has a unique history in South Africa, due to an association with gold mines, where large numbers of mine workers were infected in the 1930s and 1940s. This was likely driven by hot humid conditions and timber supports used in these mine shafts. Furthermore, the disease is the most common subcutaneous fungal infection amongst the general population in South Africa, and the large number of immunocompromised individuals increases the public health risk in the country. Sporothrix is a genus in the Ophiostomatales, a fungal order primarily associated with environmental habitats. Unsurprisingly, sporotrichosis therefore has a documented history of sapronotic transmission from contaminated plant material. This review provides insights into the understanding of sporotrichosis and Sporothrix species, with a particular emphasis on the South African situation. We highlight knowledge gaps, particularly regarding the ecological factors influencing the occurrence and distribution of these species, which in turn affect the patterns of sporotrichosis. We also emphasise a need for ongoing proactive research and surveillance to prevent future outbreaks of sporotrichosis, an emerging disease with growing health implications worldwide.

WITHDRAWN: Detection of Amblyomma maculatum and Rickettsia parkeri in prairies of Central Missouri

Prairie habitats are complex ecosystems experiencing destruction and decline due to landscape repurposing, thus resulting in significant changes to plant, animal, and insect wildlife diversity. In the Central United States, the reconstruction of prairie habitats from farmland is a widely applied strategy to raise diversity and recreate a healthy, complex ecosystem. In Central Missouri, we are examining the consequences of reconstruction efforts on the prevalence of zoonotic diseases and their associated pathogens and have observed large populations of Dog ticks, Dermacentor variabilis, and Lone Star ticks, Amblyomma americanum, as well as the first recorded instance of the Gulf Coast tick, Amblyomma maculatum, in Callaway County. The Gulf Coast tick is traditionally found mainly along the Atlantic and Gulf Coast regions, but has been undergoing geographic expansion in the last decade. Since detection in 2020, the number of Gulf Coast ticks has increased,. Upon screening 193 Gulf Coast ticks in 105 pools, we found that 6.67 % of ticks were positive for the pathogenic Rickettsia parkeri, which causes spotted fever rickettsiosis in animals and humans, with most ticks coming from the reconstructed prairie site. These observations suggest that reconstruction of prairie habitat has the potential to support the sylvatic cycle of Rickettsia parkeri. Collectively, our observations show that the reconstructed prairie are capable of harboring large tick populations as compared to remnant prairies and demonstrates a potential increase in disease risk as a result. This works highlights the importance of proactive surveillance of ticks, especially with land-use change.

Assessment of real-time PCR test in oral fluid samples for screening the serotypes of Actinobacillus pleuropneumoniae circulating in swine herds

Actinobacillus pleuropneumoniae is the etiological agent of porcine pleuropneumonia, causing remarkable economic losses in the global swine industry. The diversity of A. pleuropneumoniae is generally determined through serotype identification, which is commonly employed for control strategies and surveillance. However, serological methods currently in use still have significant limitations. This study explores the use of real-time polymerase chain reaction (qPCR) to detect circulating serotypes of A. pleuropneumoniae in non-diseased swine herds through testing of oral fluids.The study included three A. pleuropneumoniae-positive and three A. pleuropneumoniae-negative farms located in Quebec, Canada. Tonsil brushings, microbiological growths, and oral fluids were analyzed using qPCR to detect A. pleuropneumoniae and its distinct serotypes. Serological tests were performed using the LPS ELISA available at that time. In negative farms the absence of A. pleuropneumoniae and any serotype confirmed the specificity of the method. Positive farms, on the other hand, confirmed also the sensitivity of the analysis, with oral fluid samples consistently yielding positive results for the serotypes identified by ELISA.The qPCR test conducted on oral fluids offers a noninvasive and cost-effective method for monitoring, complementing traditional serological techniques. It provides qualitative information about serotype distribution, facilitating proactive surveillance and control strategies.

Resilience in the Face of Uncertainty: Navigating Supply Chain Challenges Through Proactive Risk Surveillance and Mitigation Strategies among SMEs in ASEAN countries

Background Supply chain risk management is crucial for the consumer products industry due to its vulnerability to uncertainties and risks. This study investigates the relationship between supply chain risks and performance among SMEs in the ASEAN countries. Supply chain performance, defined as meeting end-customer demands, involves ensuring commodity availability, on-time deliveries, and maintaining sufficient inventory and capacity across organizational boundaries from raw materials to the final consumer. Methods The study utilized a sample of 385 entrepreneurs from the consumer products industry in ASEAN countries. The research was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to establish the correlation between supply chain performance and risks. Factors related to the ASEAN Economic Community (AEC) for economic integration and regional trade agreements were incorporated to understand the diverse economic development, infrastructure, and regulatory environments across nations. Results The analysis revealed a strong correlation between supply chain risks and performance. Entrepreneurs in the consumer products industry should collaborate closely with governmental organizations to address the unique challenges posed by regulatory landscapes, cross-border logistics, and geopolitical risks within the ASEAN region. Adapting to cultural nuances and market variations, along with optimizing logistics and infrastructure, are crucial for successful supply chain risk management. Conclusions Effective supply chain risk management significantly enhances the performance of the consumer products industry’s supply chain. Entrepreneurs in this sector should align their strategies with regional and national governments to proactively address issues and mitigate risks. Continuous monitoring and adaptive measures are necessary to handle emerging risks in the dynamic market landscape. The study provides valuable insights for policymakers, suggesting that supportive frameworks and policies are necessary to bolster SME capabilities in risk management. By fostering a collaborative environment between the public and private sectors, ASEAN countries can enhance overall supply chain resilience. Future research could explore sector-specific risk management practices and their impact on supply chain robustness, underscoring the imperative for SMEs to adopt proactive and integrated risk management approaches to thrive in a complex and evolving economic environment.

Prospective Monitoring of New Drugs in Older Adults with and without Frailty: Near-Real-Time Assessment of Effectiveness and Safety of Oral Anticoagulants in Medicare Data.

Prospective sequential analyses after a new drug approval allow proactive surveillance of new drugs. In the current study, we demonstrate feasibility of frailty-specific sequential analyses for dabigatran, rivaroxaban, and apixaban versus warfarin. We partitioned Medicare data from 2011 to 2020 into datasets based on calendar year following the date of drug approval. Each calendar year of data was added sequentially for analysis. We used a new-user, active comparative design by comparing the initiators of dabigatran versus warfarin, rivaroxaban versus warfarin, and apixaban versus warfarin. Patients aged ≥ 65 years with atrial fibrillation without contraindication to the anticoagulants were included. Claims-based frailty index ≥ 0.25 was used to define frailty. The initiators of each direct oral anticoagulant were propensity-score matched to the initiators of warfarin within each frailty status. The effectiveness outcome was ischemic stroke or systemic thromboembolism, and the safety outcome was major bleeding. For each calendar year, we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) from Cox proportional hazards models using all data available up to that year. As an example of the results, in the 2020 dataset, compared with warfarin, apixaban was associated with a reduced risk of ischemic stroke or systemic thromboembolism (frail: HR 0.73, 95% CI 0.63-0.85; non-frail: HR 0.65, 95% CI 0.59-0.72) and major bleeding (frail: HR 0.63, 95% CI 0.57-0.69; non-frail: HR 0.59, 95% CI 0.56-0.63) in both frail and non-frail patients. We found evidence for apixaban's effectiveness and safety within 1-2 years after the drug approval in frail older patients. Our frailty-specific sequential analyses can be applied to future near-real-time monitoring of newly approved drugs.

Mortality and Serious Adverse Events Associated With Glucagon-Like Peptide-1 Receptor Agonists: A Pharmacovigilance Study Using the FDA Adverse Event Reporting System.

Purpose Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are an increasingly prevalent class of drugs for managing overweight/obesity and type 2 diabetes mellitus. Postmarket surveillance is essential for characterizing their risk profiles in real-world patient populations as clinical use increases. This study investigated the association of GLP-1RAs with mortality and serious adverse events (AEs) reported to the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Methods A disproportionality analysis was conducted utilizing FAERS data from Q2 2005 to Q1 2024 to identify AEs listing an approved GLP-1RA as the primary suspect drug. The reporting odds ratio (ROR) was calculated for mortality and serious AEs associated with each GLP-1RA compared to the combined group of all other GLP-1RAs. A signal of disproportionate reporting indicating a potential safety concern was defined as a lower bound of the 95% CI for the ROR exceeding 1.0. Results The analysis identified 287,201 AEs associated with GLP-1RAs during the study period. Disproportionality analyses revealed statistically significant elevated signals for mortality with the earliest approved GLP-1RAs: Byetta (ROR = 2.20, 95% CI: 2.06-2.34) and Victoza (ROR = 2.12, 95% CI: 1.98-2.28). Significant elevated signals for serious AEs were identified with the semaglutide products Ozempic (ROR = 2.77, 95% CI: 2.69-2.85), Rybelsus (ROR = 2.42, 95% CI: 2.26-2.60), and Wegovy (ROR = 1.30, 95% CI: 1.22-1.39); the liraglutide products Victoza (ROR = 2.10, 95% CI: 2.04-2.15) and Saxenda (ROR = 2.21, 95% CI: 2.09-2.33); and Byetta (ROR = 1.11, 95% CI: 1.08-1.14) compared to other GLP-1RAs. The newer GLP-1RAs were associated with a higher proportion of serious AEs reported in younger patients (p < 0.001) and females (p < 0.001). Conclusion This pharmacovigilance study utilizing the FAERS database identified potential safety signals of increased mortality and serious AE reporting associated with certain GLP-1RAs, particularly the earlier approved liraglutide agents Byetta and Victoza. These findings highlight the importance of proactive postmarket surveillance to characterize the real-world safety profiles of individual GLP-1RA drugs.

Pathogen characteristics of respiratory infections in the season after the COVID-19 pandemic between August and December 2023: evidence from direct-to-consumer testing-based surveillance in Guangzhou and Beijing, China

ObjectivesIn the fall-winter of 2023, China experienced its first epidemic season of respiratory diseases since the COVID-19 pandemic. Gathering timely data about pathogenetic characteristics of respiratory infections is crucial to complement current respiratory surveillance mechanisms in China. Data from direct-to-consumer (DTC) multi-respiratory pathogen (MRP) testing could serve as a novel source of multi-pathogen data for community-based surveillance. MethodsA pioneering initiative was launched to detect multiple respiratory pathogens in Beijing and Guangzhou, China. DTC MRP tests were used to provide proactive surveillance ahead of medical services. ResultsA total of 28,018 participants were enrolled between 22 August and 10 December 2023. Positive findings for at least one respiratory pathogen were observed in 26,202 (93.5%) participants. Influenza virus A, respiratory syncytial virus (RSV), and human adenovirus are the three leading viral pathogens detected with proportions of 18.0%, 10.6%, and 8.8%. Viral-bacterial pathogens were co-detected in 9736 (34.7%) of participants, which reduced to 22.2% for bacterial-bacterial co-detection, and 22.0% for bacterial mono-detection. The epidemiological ecology of respiratory pathogens within both viral clusters and specific pathogens varied among cities. The peak of RSV epidemics in Guangzhou occurred in the fall of 2023, earlier than in Beijing. ConclusionThe innovative program offered enhanced surveillance capabilities beyond traditional methods, enabling prompt feedback about test results and mitigating the risk of cross-infection caused by waits in healthcare facilities.

A large-scale surveillance revealed that KPC variants mediated ceftazidime-avibactam resistance in clinically isolated Klebsiella pneumoniae.

To monitor the resistance rate and gain a deeper understanding of the resistance mechanisms, we conducted over a 2-year surveillance focusing on the Klebsiella pneumoniae associated with the clinical usage of ceftazidime-avibactam (CZA) in a teaching hospital. A total of 4,641 K. pneumoniae isolates were screened to identify the CZA resistance through antimicrobial susceptibility testing. Comprehensive analyses, including homology analysis, conjugation experiments, clone assays, and whole genome sequencing, were furtherly performed on the CZA-resistant strains. In total, four CZA-resistant K. pneumoniae (CZA-R-Kp) strains were separated from four patients, in which three of them received CZA treatment during the hospitalization, accounting for a 4% (3/75) resistance development rate of K. pneumoniae under CZA stress. All CZA-R-Kp isolates were found to possess variants of blaKPC-2. The identified mutations included blaKPC-33, blaKPC-86, and a novel variant designated as blaKPC-129, all of which were located in the Ω loop of the KPC enzyme. These mutations were found to impact the amino acid sequence and spatial structure of the enzyme's active center, consequently affecting KPC carbapenemase activity. This study underscores the importance of active surveillance to monitor the emergence of resistance to CZA, highlighting the need for ongoing research to develop effective strategies for combating antimicrobial resistance. Understanding the mechanisms behind resistance is crucial in maintaining the efficacy of CZA, a vital tool in the battle against multidrug-resistant infections.IMPORTANCEAs an effective drug for the treatment of carbapenem-resistant Klebsiella pneumoniae, ceftazidime-avibactam (CZA) began to develop resistance in recent years and showed an increasing trend. In order to effectively monitor the resistance rate of CZA and understand its resistance mechanism, we monitored K. pneumoniae for more than 2 years to find CZA-resistant strains. Through comprehensive analysis of the selected CZA-resistant strains, it was found that all the CZA-resistant strains had mutation, which could affect the activity of KPC carbapenemase. This study highlights the importance of proactive surveillance to monitor the emergence of CZA resistance, which highlights the need for ongoing research to develop effective strategies to combat antimicrobial resistance. Understanding the mechanisms behind resistance is critical to maintaining the effectiveness of CZA, an important tool in the fight against multidrug-resistant infections.

Central lymph node ratio is an important recurrence prognostic factor for pediatric differentiated thyroid cancer.

The current risk stratification methods for Pediatric Differentiated Thyroid Carcinoma (DTC) are deemed inadequate due to the high recurrence rates observed in this demographic. This study investigates alternative clinicopathological factors, specifically the Central Lymph Node Ratio (CLNR), for improved risk stratification in pediatric DTC. A retrospective review of 100 pediatric DTC patients, aged 19 or younger, treated between December 2012 and January 2021 at the First Affiliated Hospital of Guangxi Medical University was conducted. Clinicopathological variables were extracted, and univariate logistic regression identified factors correlated with recurrence. Kaplan-Meier (KM) survival analysis and subsequent statistical tests were used to assess the significance of these factors. The CLNR, with a cutoff value of 77.78%, emerged as a significant predictor of recurrence. Patients with a CLNR above this threshold had a 5.467 times higher risk of recurrence. The high CLNR group showed a higher proportion of male patients, clinically lymph node positivity (cN1), and extrathyroidal extension (ETE) compared to the low-risk group (p<0.05). CLNR is a valuable predictor for recurrence in pediatric DTC and aids in stratifying patients based on Recurrence-Free Survival (RFS). For patients with a high CLNR, aggressive iodine-131 therapy, stringent TSH suppression, and proactive postoperative surveillance are recommended to mitigate recurrence risk and facilitate timely detection of recurrent lesions.

Insights into tick dynamics and anaplasmosis in ruminants: A microscopic and molecular perspective

AbstractTicks are blood‐sucking parasite and transmit pathogens to humans, domestic and wild animals. Ticks are seriously damage the production of sheep and goats, resulting in heavy economic loss to farmers. The present study investigated microscopic and molecular identification of ticks and tick‐borne anaplasmosis infesting sheep and goats in three agro‐ecological zones of Pakistan. The collected ticks were identified at species level based on their morphological features through microscopy by using taxonomic keys. Four Rhipicephalus (R.) species namely: R. guilhoni Rh. geigyi, R. annulatus, R. pulchellus, two Haemaphysalis (Hae) spp. Hae. sulcate, Hae. punctate, one Ixodes ricinus and Hyalomma anatolicum were identified. The morphological variations in their body sizes, scutal pattern, female genital opening, spiracular plate length and male adanal plate were recorded. Furthermore, we assessed the effectiveness of utilizing the 16S rRNA gene sequence to differentiate Anaplasma samples at the species level. Microscopically suspected positive blood samples for Anaplasma were subjected to DNA extraction. Anaplasma was observed in the blood of 14 animals. The sequence similarity between Anaplasma marginale and the reference genome were 99.25%, while below this value indicating a distinct species. Phylogenetic analysis revealed close similarity with A. marginale isolates from Iran, Vietnam and Pakistan This study contributes to the epidemiology of ticks and TBPs in the KP province and highlights the importance of proactive TBP surveillance in livestock.

Smart city fire surveillance: A deep state‐space model with intelligent agents

AbstractIn the realm of smart city development, the integration of intelligent agents has emerged as a pivotal strategy to enhance the efficacy of search methodologies. This study introduces a novel state‐space navigational model employing intelligent agents tailored specifically for fire surveillance in urban environments. Central to this model is the fusion of a convolutional neural network and multilayer perceptron, enabling accurate fire detection and localisation. Leveraging this capability, the intelligent agent proactively navigates through the search space, guided by the shortest path to the identified fire location. The utilisation of the A* algorithm as the search mechanism underscores the efficiency and efficacy of our proposed approach. Implemented in Python and Gephi, our method surpasses traditional search algorithms, both informed and uninformed, demonstrating its effectiveness in navigating urban landscapes for fire surveillance. This research study contributes significantly to the field by offering a robust solution for proactive fire detection and surveillance in smart city environments, thereby enhancing public safety and urban resilience.

Pilot study to evaluate the use of remote patient monitoring to guide the timing of valve intervention in patients with severe asymptomatic aortic stenosis (APRAISE-AS): study protocol for a randomised controlled trial delivered in two tertiary cardiac centres in the UK

IntroductionAortic stenosis (AS) is common affecting >13% of adults over the age of 75 years. In people who develop symptoms, without valve replacement, prognosis is dismal with mortality as high...

ITS 94 - Employing Proactive Surveillance Using an Electronic Health Record-based Screening Technology for Clostridioides difficile to Mitigate Healthcare-associated Infections

ITS 94 - Employing Proactive Surveillance Using an Electronic Health Record-based Screening Technology for Clostridioides difficile to Mitigate Healthcare-associated Infections

Risk factors for the recurrence of left atrioventricular valvular regurgitation after surgical repair of partial and transitional atrioventricular septal defect.

Left atrioventricular valvular regurgitation (LAVVR) recurrence after partial and transitional atrioventricular septal defect (AVSD) repair is the main risk factor associated with reoperation or mortality. The purpose of this study was to identify risk factors associated with the recurrence of LAVVR after surgical repair of transitional and partial AVSD at a single institution. A hundred and fifty-seven patients who underwent anatomical repair for partial and transitional AVSD from January 2013 to December 2021 were included in our institutional database. Demographic characteristics, operative information, comorbidities, complications, and outcomes were retrieved from electronic medical records. Echocardiographic evaluations included cardiac dimensions, the degree of LAVVR, and the anatomy of the atrioventricular valve. After a median follow-up period of 5.8 years, 40 patients had recurrent moderate or even more severe LAVVR. Compared with patients without recurrent LAVVR, those experiencing LAVVR recurrence were more likely to have larger preoperative left atrial (LA) size and larger left ventricular (LV) size after standardization, larger left atrioventricular valve (LAVV) cleft width, higher proportions of preoperative moderate or even more severe LAVVR, and immediately postoperative mild to moderate or even more severe LAVVR. Univariate Cox regression analysis showed that age at first repair, height, LA size after standardization, LV size after standardization, the severity of preoperative LAVVR, immediately postoperative LAVVR, and the LAVV cleft width more than 1cm were risk factors for recurrent LAVVR (P<0.05 for all). Multivariable Cox regression analysis showed that mild to moderate or even more severe LAVVR postoperatively [hazard ratio (HR) 9.53, 95% confidence interval (CI): 3.78-24.01; P<0.001], the width of LAVV cleft more than 1 cm (HR: 3.90, 95% CI: 1.80-8.48; P<0.001) and age at first repair (HR: 0.45, 95% CI: 0.31-0.66; P<0.001) were independently associated with the recurrence of LAVVR. The width of LAVV cleft, mild to moderate or even more severe LAVVR immediately after surgery, and age at initial surgery are risk factors for recurrent LAVVR. The presence of recurrent LAVVR necessitates proactive surveillance to facilitate timely reintervention.

Persistence of SARS-CoV-2 infection and viral intra- and inter-host evolution in COVID-19 hospitalized patients.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) persistence in COVID-19 patients could play a key role in the emergence of variants of concern. The rapid intra-host evolution of SARS-CoV-2 may result in an increased transmissibility, immune and therapeutic escape which could be a direct consequence of COVID-19 epidemic currents. In this context, a longitudinal retrospective study on eight consecutive COVID-19 patients with persistent SARS-CoV-2 infection, from January 2022 to March 2023, was conducted. To characterize the intra- and inter-host viral evolution, whole genome sequencing and phylogenetic analysis were performed on nasopharyngeal samples collected at different time points. Phylogenetic reconstruction revealed an accelerated SARS-CoV-2 intra-host evolution and emergence of antigenically divergent variants. The Bayesian inference and principal coordinate analysis analysis showed a host-based genomic structuring among antigenically divergent variants, that might reflect the positive effect of containment practices, within the critical hospital area. All longitudinal antigenically divergent isolates shared a wide range of amino acidic (aa) changes, particularly in the Spike (S) glycoprotein, that increased viral transmissibility (K417N, S477N, N501Y and Q498R), enhanced infectivity (R346T, S373P, R408S, T478K, Q498R, Y505H, D614G, H655Y, N679K and P681H), caused host immune escape (S371L, S375F, T376A, K417N, and K444T/R) and displayed partial or complete resistance to treatments (G339D, R346K/T, S371F/L, S375F, T376A, D405N, N440K, G446S, N460K, E484A, F486V, Q493R, G496S and Q498R). These results suggest that multiple novel variants which emerge in the patient during persistent infection, might spread to another individual and continue to evolve. A pro-active genomic surveillance of persistent SARS-CoV-2 infected patients is recommended to identify genetically divergent lineages before their diffusion.

Adaptive SARIMA modelling for continuous chamber temperature tracking in ultra-low temperature freezers

Ultra-low temperature (ULT) freezers are vital for storing perishable biological materials, requiring continuous monitoring of chamber thermal conditions to ensure sample integrity. A reliable dynamic data-driven model is key for smart proactive surveillance of the ULT freezers through real-time status tracking. However, the dynamic nature of ULT freezers, influenced by external disturbances, demands adaptive models to sustain performance. Complex models thus face challenges due to time-consuming parameter updates. To ensure model prediction performance while minimising model updating time, this study proposes a Seasonal Autoregressive Integrated Moving Average (SARIMA) model-based approach for short-term ULT freezer chamber temperature prediction. This method solely relies on historical chamber temperature data, eliminating the need for additional measurements. Moreover, two adaptive duty cycle length (DCL) selection strategies and a one-step ahead DCL estimation method are developed to address auto-correlation issues caused by recurring duty cycles. Comparative analyses with reference models demonstrate that the SARIMA model, incorporating future DCL effects, excels in one-step prediction and multi-step forecast under stable and variant DCL periods. Moreover, it outperforms the reference models in auto-correlation representation, affirming its reliability in predicting future states. The proposed modelling approach promises an effective method for freezing chamber temperature prediction, enabling continuous status tracking and early fault detection. Moreover, it holds great potential for modelling other critical temperatures in refrigeration systems and facilitating flexible energy operations.

Proactive surveillance for avian influenza H5N1 and other priority pathogens at mass gathering events

Proactive surveillance for avian influenza H5N1 and other priority pathogens at mass gathering events