SARS-CoV-2 transmission in teenagers and young adults in Fútbol Club Barcelona's Multidisciplinary Sports Training Academy.

Most studies, aimed at determining the incidence and transmission of SARS-CoV-2 in children and teenagers, have been developed in school settings. Our study conducted surveillance and inferred attack rates focusing on the practice of sports. Prospective and observational study of those attending the sports facilities of Fútbol Club Barcelona (FCB), in Barcelona, Spain, throughout the 2020-2021 season. Participants were young players (from five different sports) and adult workers, who belonged to stable teams (shared routines and were involved in same quarantine rules). Biweekly health questionnaires and SARS-CoV-2 screening were conducted. From the 234 participants included, 70 (30%) both lived and trained in the FCB facilities (Recruitment Pathway 1;RP1) and 164 (70%) lived at their own household and just came to the facilities to train (RP2). During the study, 38 positive cases were identified; none had severe symptoms or needed hospitalization. The overall weekly incidence in the cohorts did not differ compared to the one expected in the community, except for 2 weeks when an outbreak occurred. The attack rate (AR) was three times higher for the participants from RP1, in comparison to those from RP2 (p < 0.01). A Basketball team showed a significant higher AR.  Conclusion: Physical activities in stable teams are not related to an increased risk of transmission of SARS-CoV-2, since there were the same observed cases than expected in the community. The risk is higher in indoor sports (Basketball vs. Football), and in closed cohort living settings (RP1 vs. RP2). The fulfilment of preventive measures is essential. What is Known: • Despite the low numerical impact caused in paediatric hospitalizations during COVID-19 pandemic, the social impact has been maximum. • The transmission potential in children and teenagers is limited, and it had been widely demonstrated in school settings. What is New: • Group physical activities in children and teenagers are not also related to an increased risk of transmission of SARS-CoV-2, when preventive measures, such as washing hands, and screening protocols are applied. • Routine and semi-professional sports activities seem safe environments to promote during this pandemic.

Automatic Deep Learning-Based Pipeline for Automatic Delineation and Measurement of Fetal Brain Structures in Routine Mid-Trimester Ultrasound Images.

INTRODUCTION: The aim of this study was to develop a pipeline using state-of-the-art deep learning methods to automatically delineate and measure several of the most important brain structures in fetal brain ultrasound (US) images. METHODS: The dataset was composed of 5,331 images of the fetal brain acquired during the routine mid-trimester US scan. Our proposed pipeline automatically performs the following three steps: brain plane classification (transventricular, transthalamic, or transcerebellar plane); brain structures delineation (9 different structures); and automatic measurement (from the structure delineations). The methods were trained on a subset of 4,331 images and each step was evaluated on the remaining 1,000 images. RESULTS: Plane classification reached 98.6% average class accuracy. Brain structure delineation obtained an average pixel accuracy higher than 96% and a Jaccard index higher than 70%. Automatic measurements get an absolute error below 3.5% for the four standard head biometries (head circumference, biparietal diameter, occipitofrontal diameter, and cephalic index), 9% for transcerebellar diameter, 12% for cavum septi pellucidi ratio, and 26% for Sylvian fissure operculization degree. CONCLUSIONS: The proposed pipeline shows the potential of deep learning methods to delineate fetal head and brain structures and obtain automatic measures of each anatomical standard plane acquired during routine fetal US examination.

Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 Infection Among Children in Summer Schools Applying Stringent Control Measures in Barcelona, Spain.

BACKGROUND: Understanding the role of children in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is critical to guide decision-making for schools in the pandemic. We aimed to describe the transmission of SARS-CoV-2 among children and adult staff in summer schools. METHODS: During July 2020, we prospectively recruited children and adult staff attending summer schools in Barcelona who had SARS-CoV-2 infection. Primary SARS-CoV-2 infections were identified through (1) a surveillance program in 22 summer schools of 1905 participants, involving weekly saliva sampling for SARS-CoV-2 reverse-transcription polymerase chain reaction (RT-PCR) during 2-5 weeks; and (2) cases identified through the Catalonian Health Surveillance System of children diagnosed with SARS-CoV-2 infection by nasopharyngeal RT-PCR. All centers followed prevention protocols: bubble groups, handwashing, face masks, and conducting activities mostly outdoors. Contacts of a primary case within the same bubble were evaluated by nasopharyngeal RT-PCR. Secondary attack rates and the effective reproduction number in summer schools (Re*) were calculated. RESULTS: Among the >2000 repeatedly screened participants, 30 children and 9 adults were identified as primary cases. A total of 253 close contacts of these primary cases were studied (median, 9 [interquartile range, 5-10] for each primary case), among which 12 new cases (4.7%) were positive for SARS-CoV-2. The Re* was 0.3, whereas the contemporary rate in the general population from the same areas in Barcelona was 1.9. CONCLUSIONS: The transmission rate of SARS-CoV-2 infection among children attending school-like facilities under strict prevention measures was lower than that reported for the general population. This suggests that under preventive measures schools are unlikely amplifiers of SARS-CoV-2 transmission, supporting current recommendations for school opening.

Antibody conversion rates to SARS-CoV-2 in saliva from children attending summer schools in Barcelona, Spain.

BACKGROUND: Surveillance tools to estimate viral transmission dynamics in young populations are essential to guide recommendations for school opening and management during viral epidemics. Ideally, sensitive techniques are required to detect low viral load exposures among asymptomatic children. We aimed to estimate SARS-CoV-2 infection rates in children and adult populations in a school-like environment during the initial COVID-19 pandemic waves using an antibody-based field-deployable and non-invasive approach. METHODS: Saliva antibody conversion defined as ≥ 4-fold increase in IgM, IgA, and/or IgG levels to five SARS-CoV-2 antigens including spike and nucleocapsid constructs was evaluated in 1509 children and 396 adults by high-throughput Luminex assays in samples collected weekly in 22 summer schools and 2 pre-schools in 27 venues in Barcelona, Spain, from June 29th to July 31st, 2020. RESULTS: Saliva antibody conversion between two visits over a 5-week period was 3.22% (49/1518) or 2.36% if accounting for potentially cross-reactive antibodies, six times higher than the cumulative infection rate (0.53%) assessed by weekly saliva RT-PCR screening. IgG conversion was higher in adults (2.94%, 11/374) than children (1.31%, 15/1144) (p=0.035), IgG and IgA levels moderately increased with age, and antibodies were higher in females. Most antibody converters increased both IgG and IgA antibodies but some augmented either IgG or IgA, with a faster decay over time for IgA than IgG. Nucleocapsid rather than spike was the main antigen target. Anti-spike antibodies were significantly higher in individuals not reporting symptoms than symptomatic individuals, suggesting a protective role against COVID-19. CONCLUSION: Saliva antibody profiling including three isotypes and multiplexing antigens is a useful and user-friendlier tool for screening pediatric populations to detect low viral load exposures among children, particularly while they are not vaccinated and vulnerable to highly contagious variants, and to recommend public health policies during pandemics.

Generative Adversarial Networks to Improve Fetal Brain Fine-Grained Plane Classification.

Generative adversarial networks (GANs) have been recently applied to medical imaging on different modalities (MRI, CT, X-ray, etc). However there are not many applications on ultrasound modality as a data augmentation technique applied to downstream classification tasks. This study aims to explore and evaluate the generation of synthetic ultrasound fetal brain images via GANs and apply them to improve fetal brain ultrasound plane classification. State of the art GANs stylegan2-ada were applied to fetal brain image generation and GAN-based data augmentation classifiers were compared with baseline classifiers. Our experimental results show that using data generated by both GANs and classical augmentation strategies allows for increasing the accuracy and area under the curve score.

Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results.

Cross-scanner and cross-protocol variability of diffusion magnetic resonance imaging (dMRI) data are known to be major obstacles in multi-site clinical studies since they limit the ability to aggregate dMRI data and derived measures. Computational algorithms that harmonize the data and minimize such variability are critical to reliably combine datasets acquired from different scanners and/or protocols, thus improving the statistical power and sensitivity of multi-site studies. Different computational approaches have been proposed to harmonize diffusion MRI data or remove scanner-specific differences. To date, these methods have mostly been developed for or evaluated on single b-value diffusion MRI data. In this work, we present the evaluation results of 19 algorithms that are developed to harmonize the cross-scanner and cross-protocol variability of multi-shell diffusion MRI using a benchmark database. The proposed algorithms rely on various signal representation approaches and computational tools, such as rotational invariant spherical harmonics, deep neural networks and hybrid biophysical and statistical approaches. The benchmark database consists of data acquired from the same subjects on two scanners with different maximum gradient strength (80 and 300 â€‹mT/m) and with two protocols. We evaluated the performance of these algorithms for mapping multi-shell diffusion MRI data across scanners and across protocols using several state-of-the-art imaging measures. The results show that data harmonization algorithms can reduce the cross-scanner and cross-protocol variabilities to a similar level as scan-rescan variability using the same scanner and protocol. In particular, the LinearRISH algorithm based on adaptive linear mapping of rotational invariant spherical harmonics features yields the lowest variability for our data in predicting the fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK) and the rotationally invariant spherical harmonic (RISH) features. But other algorithms, such as DIAMOND, SHResNet, DIQT, CMResNet show further improvement in harmonizing the return-to-origin probability (RTOP). The performance of different approaches provides useful guidelines on data harmonization in future multi-site studies.

VERDICT MRI for Prostate Cancer: Intracellular Volume Fraction versus Apparent Diffusion Coefficient.

Background Biologic specificity of diffusion MRI in relation to prostate cancer aggressiveness may improve by examining separate components of the diffusion MRI signal. The Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumors (VERDICT) model estimates three distinct signal components and associates them to (a) intracellular water, (b) water in the extracellular extravascular space, and (c) water in the microvasculature. Purpose To evaluate the repeatability, image quality, and diagnostic utility of intracellular volume fraction (FIC) maps obtained with VERDICT prostate MRI and to compare those maps with apparent diffusion coefficient (ADC) maps for Gleason grade differentiation. Materials and Methods Seventy men (median age, 62.2 years; range, 49.5-82.0 years) suspected of having prostate cancer or undergoing active surveillance were recruited to a prospective study between April 2016 and October 2017. All men underwent multiparametric prostate and VERDICT MRI. Forty-two of the 70 men (median age, 67.7 years; range, 50.0-82.0 years) underwent two VERDICT MRI acquisitions to assess repeatability of FIC measurements obtained with VERDICT MRI. Repeatability was measured with use of intraclass correlation coefficients (ICCs). The image quality of FIC and ADC maps was independently evaluated by two board-certified radiologists. Forty-two men (median age, 64.8 years; range, 49.5-79.6 years) underwent targeted biopsy, which enabled comparison of FIC and ADC metrics in the differentiation between Gleason grades. Results VERDICT MRI FIC demonstrated ICCs of 0.87-0.95. There was no significant difference between image quality of ADC and FIC maps (score, 3.1 vs 3.3, respectively; P = .90). FIC was higher in lesions with a Gleason grade of at least 3+4 compared with benign and/or Gleason grade 3+3 lesions (mean, 0.49 ± 0.17 vs 0.31 ± 0.12, respectively; P = .002). The difference in ADC between these groups did not reach statistical significance (mean, 1.42 vs 1.16 × 10-3 mm2/sec; P = .26). Conclusion Fractional intracellular volume demonstrates high repeatability and image quality and enables better differentiation of a Gleason 4 component cancer from benign and/or Gleason 3+3 histology than apparent diffusion coefficient. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Sigmund and Rosenkrantz in this issue.

VERDICT-AMICO: Ultrafast fitting algorithm for non-invasive prostate microstructure characterization.

VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumours) estimates and maps microstructural features of cancerous tissue non-invasively using diffusion MRI. The main purpose of this study is to address the high computational time of microstructural model fitting for prostate diagnosis, while retaining utility in terms of tumour conspicuity and repeatability. In this work, we adapt the accelerated microstructure imaging via convex optimization (AMICO) framework to linearize the estimation of VERDICT parameters for the prostate gland. We compare the original non-linear fitting of VERDICT with the linear fitting, quantifying accuracy with synthetic data, and computational time and reliability (performance and precision) in eight patients. We also assess the repeatability (scan-rescan) of the parameters. Comparison of the original VERDICT fitting versus VERDICT-AMICO showed that the linearized fitting (1) is more accurate in simulation for a signal-to-noise ratio of 20 dB; (2) reduces the processing time by three orders of magnitude, from 6.55 seconds/voxel to 1.78 milliseconds/voxel; (3) estimates parameters more precisely; (4) produces similar parametric maps and (5) produces similar estimated parameters with a high Pearson correlation between implementations, r2  > 0.7. The VERDICT-AMICO estimates also show high levels of repeatability. Finally, we demonstrate that VERDICT-AMICO can estimate an extra diffusivity parameter without losing tumour conspicuity and retains the fitting advantages. VERDICT-AMICO provides microstructural maps for prostate cancer characterization in seconds.

Clinical Feasibility of Quantitative Ultrasound Texture Analysis: A Robustness Study Using Fetal Lung Ultrasound Images.

OBJECTIVES: To compare the robustness of several methods based on quantitative ultrasound (US) texture analysis to evaluate its feasibility for extracting features from US images to use as a clinical diagnostic tool. METHODS: We compared, ranked, and validated the robustness of 5 texture-based methods for extracting textural features from US images acquired under different conditions. For comparison and ranking purposes, we used 13,171 non-US images from widely known available databases (OUTEX [University of Oulu, Oulu, Finland] and PHOTEX [Texture Lab, Heriot-Watt University, Edinburgh, Scotland]), which were specifically acquired under different controlled parameters (illumination, resolution, and rotation) from 103 textures. The robustness of those methods with better results from the non-US images was validated by using 666 fetal lung US images acquired from singleton pregnancies. In this study, 2 similarity measurements (correlation and Chebyshev distances) were used to evaluate the repeatability of the features extracted from the same tissue images. RESULTS: Three of the 5 methods (gray-level co-occurrence matrix, local binary patterns, and rotation-invariant local phase quantization) had favorably robust performance when using the non-US database. In fact, these methods showed similarity values close to 0 for the acquisition variations and delineations. Results from the US database confirmed robustness for all of the evaluated methods (gray-level co-occurrence matrix, local binary patterns, and rotation-invariant local phase quantization) when comparing the same texture obtained from different regions of the image (proximal/distal lungs and US machine brand stratification). CONCLUSIONS: Our results confirmed that texture analysis can be robust (high similarity for different condition acquisitions) with potential to be included as a clinical tool.

Prediction of neonatal respiratory morbidity by quantitative ultrasound lung texture analysis: a multicenter study.

BACKGROUND: Prediction of neonatal respiratory morbidity may be useful to plan delivery in complicated pregnancies. The limited predictive performance of the current diagnostic tests together with the risks of an invasive procedure restricts the use of fetal lung maturity assessment. OBJECTIVE: The objective of the study was to evaluate the performance of quantitative ultrasound texture analysis of the fetal lung (quantusFLM) to predict neonatal respiratory morbidity in preterm and early-term (<39.0 weeks) deliveries. STUDY DESIGN: This was a prospective multicenter study conducted in 20 centers worldwide. Fetal lung ultrasound images were obtained at 25.0-38.6 weeks of gestation within 48 hours of delivery, stored in Digital Imaging and Communication in Medicine format, and analyzed with quantusFLM. Physicians were blinded to the analysis. At delivery, perinatal outcomes and the occurrence of neonatal respiratory morbidity, defined as either respiratory distress syndrome or transient tachypnea of the newborn, were registered. The performance of the ultrasound texture analysis test to predict neonatal respiratory morbidity was evaluated. RESULTS: A total of 883 images were collected, but 17.3% were discarded because of poor image quality or exclusion criteria, leaving 730 observations for the final analysis. The prevalence of neonatal respiratory morbidity was 13.8% (101 of 730). The quantusFLM predicted neonatal respiratory morbidity with a sensitivity, specificity, positive and negative predictive values of 74.3% (75 of 101), 88.6% (557 of 629), 51.0% (75 of 147), and 95.5% (557 of 583), respectively. Accuracy was 86.5% (632 of 730) and positive and negative likelihood ratios were 6.5 and 0.3, respectively. CONCLUSION: The quantusFLM predicted neonatal respiratory morbidity with an accuracy similar to that previously reported for other tests with the advantage of being a noninvasive technique.

Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

OBJECTIVES: Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. METHODS: This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. RESULTS: Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). DISCUSSION: This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant.

INNOVATE: A prospective cohort study combining serum and urinary biomarkers with novel diffusion-weighted magnetic resonance imaging for the prediction and characterization of prostate cancer.

BACKGROUND: Whilst multi-parametric magnetic resonance imaging (mp-MRI) has been a significant advance in the diagnosis of prostate cancer, scanning all patients with elevated prostate specific antigen (PSA) levels is considered too costly for widespread National Health Service (NHS) use, as the predictive value of PSA levels for significant disease is poor. Despite the fact that novel blood and urine tests are available which may predict aggressive disease better than PSA, they are not routinely employed due to a lack of clinical validity studies. Furthermore approximately 40 % of mp-MRI studies are reported as indeterminate, which can lead to repeat examinations or unnecessary biopsy with associated patient anxiety, discomfort, risk and additional costs. METHODS/DESIGN: We aim to clinically validate a panel of minimally invasive promising blood and urine biomarkers, to better select patients that will benefit from a multiparametric prostate MRI. We will then test whether the performance of the mp-MRI can be improved by the addition of an advanced diffusion-weighted MRI technique, which uses a biophysical model to characterise tissue microstructure called VERDICT; Vascular and Extracellular Restricted Diffusion for Cytometry in Tumours. INNOVATE is a prospective single centre cohort study in 365 patients. mp-MRI will act as the reference standard for the biomarker panel. A clinical outcome based reference standard based on biopsy, mp-MRI and follow-up will be used for VERDICT MRI. DISCUSSION: We expect the combined effect of biomarkers and VERDICT MRI will improve care by better detecting aggressive prostate cancer early and make mp-MRI before biopsy economically viable for universal NHS adoption. TRIAL REGISTRATION: INNOVATE is registered on ClinicalTrials.gov, with reference NCT02689271 .

An Artificial Placenta Experimental System in Sheep: Critical Issues for Successful Transition and Survival up to One Week.

OBJECTIVE: To describe the development of an artificial placenta (AP) system in sheep with learning curve and main bottlenecks to allow survival up to one week. METHODS: A total of 28 fetal sheep were transferred to an AP system at 110-115 days of gestation. The survival goal in the AP system was increased progressively in three consecutive study groups: 1-3 h (n = 8), 4-24 h (n = 10) and 48-168 h (n = 10). Duration of cannulation procedure, technical complications, pH, lactate, extracorporeal circulation (EC) circuit flows, fetal heart rate, and outcomes across experiments were compared. RESULTS: There was a progressive reduction in cannulation complications (75%, 50% and 0%, p = 0.004), improvement in initial pH (7.20 ± 0.06, 7.31 ± 0.04 and 7.33 ± 0.02, p = 0.161), and increment in the rate of experiments reaching survival goal (25%, 70% and 80%, p = 0.045). In the first two groups, cannulation accidents, air bubbles in the extracorporeal circuit, and thrombotic complications were the most common cause of AP system failure. CONCLUSIONS: Achieving a reproducible experimental setting for an AP system is extremely challenging, time- and effort-consuming, and requires a highly multidisciplinary team. As a result of the learning curve, we achieved reproducible transition and survival up to 7 days. Extended survival requires improving instrumentation with custom-designed devices.

Performance of an automatic quantitative ultrasound analysis of the fetal lung to predict fetal lung maturity.

OBJECTIVE: The objective of the study was to evaluate the performance of automatic quantitative ultrasound analysis (AQUA) texture extractor to predict fetal lung maturity tests in amniotic fluid. STUDY DESIGN: Singleton pregnancies (24.0-41.0 weeks) undergoing amniocentesis to assess fetal lung maturity (TDx fetal lung maturity assay [FLM]) were included. A manual-delineated box was placed in the lung area of a 4-chamber view of the fetal thorax. AQUA transformed the information into a set of descriptors. Genetic algorithms extracted the most relevant descriptors and then created and validated a model that could distinguish between mature or immature fetal lungs using TDx-FLM as a reference. RESULTS: Gestational age at enrollment was (mean [SD]) 32.2 (4.5) weeks. According to the TDx-FLM results, 41 samples were mature and 62 were not. The imaging biomarker based on AQUA presented a sensitivity 95.1%, specificity 85.7%, and an accuracy 90.3% to predict a mature or immature lung. CONCLUSION: Fetal lung ultrasound textures extracted by AQUA provided robust features to predict TDx-FLM results.

Feasibility and reproducibility of fetal lung texture analysis by Automatic Quantitative Ultrasound Analysis and correlation with gestational age.

OBJECTIVE: To evaluate the feasibility and reproducibility of fetal lung texture analysis using a novel automatic quantitative ultrasound analysis and to assess its correlation with gestational age. METHODS: Prospective cross-sectional observational study. To evaluate texture features, 957 left and right lung images in a 2D four-cardiac-chamber view plane were previously delineated from fetuses between 20 and 41 weeks of gestation. Quantification of lung texture was performed by the Automatic Quantitative Ultrasound Analysis (AQUA) software to extract image features. A standard learning approach composed of feature transformation and a regression model was used to evaluate the association between texture features and gestational age. RESULTS: The association between weeks of gestation and fetal lung texture quantified by the AQUA software presented a Pearson correlation of 0.97. The association was not influenced by delineation parameters such as region of interest (ROI) localization, ROI size, right/left lung selected or sonographic parameters such as ultrasound equipment or transducer used. CONCLUSIONS: Fetal lung texture analysis measured by the AQUA software demonstrated a strong correlation with gestational age. This supports further research to explore the use of this technology to the noninvasive prediction of fetal lung maturity.

Low levels of CIITA and high levels of SOCS1 predict COVID-19 disease severity in children and adults.

It is unclear why COVID-19 ranges from asymptomatic to severe. When SARS-CoV-2 is detected, interferon (IFN) response is activated. When it is insufficient or delayed, it might lead to overproduction of cytokines and severe COVID-19. The aim was to compare cytokine and IFN patterns in children and adults with differing severity with SARS-CoV-2.It was a prospective, observational study, including 84 patients. Patients with moderate/severe disease had higher cytokines' values than patients with mild disease (p< 0.001).Two IFN genes were selected to build a decision tree for severity classification: SOCS1 (representative of the rest of the IFN genes) and CIITA (inverse correlation). Low values of CIITA and high values of SOCS1 indicated severe disease. This method correctly classified 33/38(86.8%) of children and 27/34 (79.4%) of adults. To conclude, patients with severe disease had an elevated cytokine pattern, which correlated with the IFN response, with low CIITA and high SOCS1 values.

Individual prevention and containment measures in schools in Catalonia, Spain, and community transmission of SARS-CoV-2 after school re-opening.

BACKGROUND: Despite their clear lesser vulnerability to COVID-19, the extent by which children are susceptible to getting infected by SARS-CoV-2 and their capacity to transmit the infection to other people remains inadequately characterized. We aimed to evaluate the role of school reopening and the preventive strategies in place at schools in terms of overall risk for children and community transmission, by comparing transmission rates in children as detected by a COVID-19 surveillance platform in place in Catalonian Schools to the incidence at the community level. METHODS AND FINDINGS: Infections detected in Catalan schools during the entire first trimester of classes (September-December 2020) were analysed and compared with the ongoing community transmission and with the modelled predicted number of infections. There were 30.486 infections (2.12%) documented among the circa 1.5M pupils, with cases detected in 54.0% and 97.5% of the primary and secondary centres, respectively. During the entire first term, the proportion of "bubble groups" (stable groups of children doing activities together) that were forced to undergo confinement ranged between 1 and 5%, with scarce evidence of substantial intraschool transmission in the form of chains of infections, and with ~75% of all detected infections not leading to secondary cases. Mathematical models were also used to evaluate the effect of different parameters related to the defined preventive strategies (size of the bubble group, number of days of confinement required by contacts of an index case). The effective reproduction number inside the bubble groups in schools (R*), defined as the average number of schoolmates infected by each primary case within the bubble, was calculated, yielding a value of 0.35 for primary schools and 0.55 for secondary schools, and compared with the outcomes of the mathematical model, implying decreased transmissibility for children in the context of the applied measures. Relative homogenized monthly cumulative incidence ([Formula: see text]) was assessed to compare the epidemiological dynamics among different age groups and this analysis suggested the limited impact of infections in school-aged children in the context of the overall community incidence. CONCLUSIONS: During the fall of 2020, SARS-CoV-2 infections and COVID-19 cases detected in Catalan schools closely mirrored the underlying community transmission from the neighbourhoods where they were set and maintaining schools open appeared to be safe irrespective of underlying community transmission. Preventive measures in place in those schools appeared to be working for the early detection and rapid containment of transmission and should be maintained for the adequate and safe functioning of normal academic and face-to-face school activities.

Multiplex Antibody Analysis of IgM, IgA and IgG to SARS-CoV-2 in Saliva and Serum From Infected Children and Their Close Contacts.

COVID-19 affects children to a lesser extent than adults but they can still get infected and transmit SARS-CoV-2 to their contacts. Field deployable non-invasive sensitive diagnostic techniques are needed to evaluate the infectivity dynamics of SARS-CoV-2 in pediatric populations and guide public health interventions, particularly if this population is not fully vaccinated. We evaluated the utility of high-throughput Luminex assays to quantify saliva IgM, IgA and IgG antibodies against five SARS-CoV-2 spike (S) and nucleocapsid (N) antigens in a contacts and infectivity longitudinal study in 122 individuals (52 children and 70 adults). We compared saliva versus serum/plasma samples in infected children and adults diagnosed by weekly RT-PCR over 35 days (n=62), and those who consistently tested negative over the same follow up period (n=60), in the Summer of 2020 in Barcelona, Spain. Saliva antibody levels in SARS-CoV-2 RT-PCR positive individuals were significantly higher than in negative individuals and correlated with those measured in sera/plasmas. Asymptomatic infected individuals had higher levels of anti-S IgG than symptomatic individuals, suggesting a protective anti-disease role for antibodies. Higher anti-S IgG and IgM levels in serum/plasma and saliva, respectively, in infected children compared to infected adults could also be related to stronger clinical immunity in them. Among infected children, males had higher levels of saliva IgG to N and RBD than females. Despite overall correlation, individual clustering analysis suggested that responses that may not be detected in blood could be patent in saliva, and vice versa. In conclusion, measurement of SARS-CoV-2-specific saliva antibodies should be considered as a complementary non-invasive assay to serum/plasma to determine COVID-19 prevalence and transmission in pediatric populations before and after vaccination campaigns.

Low transmission of SARS-CoV-2 derived from children in family clusters: An observational study of family households in the Barcelona Metropolitan Area, Spain.

BACKGROUND: Family clusters offer a good opportunity to study viral transmission in a stable setting. We aimed to analyze the specific role of children in transmission of SARS-CoV-2 within households. METHODS: A prospective, longitudinal, observational study, including children with documented acute SARS-CoV-2 infection attending 22 summer-schools in Barcelona, Spain, was performed. Moreover, other patients and families coming from other school-like environments that voluntarily accessed the study were also studied. A longitudinal follow-up (5 weeks) of the family clusters was conducted to determine whether the children considered to be primary cases were able to transmit the virus to other family members. The household reproduction number (Re*) and the secondary attack rate (SAR) were calculated. RESULTS: 1905 children from the summer schools were screened for SARS-CoV-2 infection and 22 (1.15%) tested positive. Moreover, 32 additional children accessed the study voluntarily. Of these, 37 children and their 26 households were studied completely. In half of the cases (13/26), the primary case was considered to be a child and secondary transmission to other members of the household was observed in 3/13, with a SAR of 14.2% and a Re* of 0.46. Conversely, the SAR of adult primary cases was 72.2% including the kids that gave rise to the contact tracing study, and 61.5% without them, and the estimated Re* was 2.6. In 4/13 of the paediatric primary cases (30.0%), nasopharyngeal PCR was persistently positive > 1 week after diagnosis, and 3/4 of these children infected another family member (p<0.01). CONCLUSIONS: Children may not be the main drivers of the infection in household transmission clusters in the study population. A prolonged positive PCR could be associated with higher transmissibility.

Correlation between a semiautomated method based on ultrasound texture analysis and standard ultrasound diagnosis using white matter damage in preterm neonates as a model.

OBJECTIVES: Diagnosis of white matter damage by cranial ultrasound imaging is still subject to interobserver variability and has limited sensitivity for predicting abnormal neurodevelopment later in life. In this study, we evaluated the ability of a semiautomated method based on ultrasound texture analysis to identify patterns that correlate with the ultrasound diagnosis of white matter damage. METHODS: The study included 44 very preterm neonates born at a median gestational age of 29 weeks 3 days (range, 26 weeks-31 weeks 6 days). Patients underwent cranial ultrasound scans within 1 week of birth and between 14 and 31 days of life. Periventricular leukomalacia was diagnosed by experienced clinicians on the 14- to 31-day scan according to standard criteria. To perform the texture analysis, 4 regions of interest were delineated in stored images: left and right periventricular areas and choroid plexuses. A classification algorithm was developed on the basis of the best combination of texture coefficients to correlate with the clinical diagnosis, and the ability of this algorithm to predict a later diagnosis of periventricular leukomalacia on the first scan was evaluated using a leave-one-out cross-validation. RESULTS: Periventricular leukomalacia was diagnosed by the standard procedure in 14 of 44 neonates. The texture classification algorithm performed on the first scan could identify cases with a later diagnosis of periventricular leukomalacia with sensitivity of 100% and accuracy of 97.7%. CONCLUSIONS: These data support the notion that semiautomated quantitative ultrasound analysis achieves early identification of changes in subclinical stages and warrant further investigation of the role of ultrasound texture analysis methods to improve early detection of neonatal brain damage.