COVID-19 Literature Mining and Analysis Research

By 2019 COVID-19, since the epidemic, the number of relevant documents exponentially level rise. Faced with a large amount of literature, this research provides convenience for exploring the connection between research topics and fields and quickly understanding relevant literature information. We pass on the data set after data cleansing using the LDA(Latent Dirichlet allocation) methods, and Berts and K-means modeling method extracting topic keywords. Use knowledge graph tools to output relevant visual graphics and systematically extract adequate information. Through text mining of biomedical research papers related to COVID-19, the improved model is used to analyze and make recommendations to respond to and prevent the COVID-19 pandemic. This research can support the rapid and in-depth analysis of a large number of relevant documents and can be used in future research to support real-time scientific disease research.

Outsourcing or reshoring? A manufacturer?s sourcing strategy in the presence of government subsidy

Multinational firms can outsource to contract manufacturers in low-labor-cost regions. However, in recent years, several developed countries and regions have subsidized their local manufacturers (LM[s], she) to encourage reshoring for external benefit (e.g., creating more domestic jobs or improving industrial struc-ture), especially after the COVID-19 pandemic started. This paper investigates the sourcing problem of an LM with brand premium in the presence of government subsidy and differences in labor costs. An LM faces three options: producing in-house, outsourcing to an original brand manufacturer (OBM, he), which sells competitive substitutes without brand premium, or outsourcing to a non-competing contract manu-facturer (NCM). We find that, first, the LM chooses reshoring if the external benefit or brand premium is sufficiently high. Second, if the LM decides to outsource, she chooses the OBM (NCM) if her brand pre-mium is high (low). Third, the government prefers to subsidize LM reshoring or outsourcing to an NCM. If the government intends to induce LM to reshore, the subsidy should be at a moderate level. Interestingly, when the LM has a low brand premium but chooses outsourcing, the government still subsidizes her to improve her competitiveness.(c) 2022 Elsevier B.V. All rights reserved.

dbSCI: A manually curated database of SARS-CoV-2 inhibitors forCOVID-19 br

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen of the ongoing coronavirusdisease 2019 (COVID-19) global pandemic. Here, by centralizing published cell-based experiments, clinical trials, andvirtual drug screening data from the NCBI PubMed database, we developed a database of SARS-CoV-2 inhibitors forCOVID-19, dbSCI, which includes 234 SARS-CoV-2 inhibitors collected from publications based on cell-basedexperiments, 81 drugs of COVID-19 in clinical trials and 1305 potential SARS-CoV-2 inhibitors from bioinformaticsanalyses. dbSCI provides four major functions: (1) search the drug target or its inhibitor for SARS-CoV-2, (2) browsetarget/inhibitor information collected from cell experiments, clinical trials, and virtual drug screenings, (3) download,and (4) submit data. Each entry in dbSCI contains 18 types of information, including inhibitor/drug name, targetingprotein, mechanism of inhibition, experimental technique, experimental sample type, and reference information. Insummary, dbSCI provides a relatively comprehensive, credible repository for inhibitors/drugs against SARS-CoV-2and their potential targeting mechanisms and it will be valuable for further studies to control COVID-19

Evaluation of patients with history of vaccine allergies prior to mRNA-based Coronavirus Disease 2019 (COVID-19) vaccination

Background: During the initial rollout of COVID-19 vaccination in Singapore, the Ministry of Health (MOH) issued recommendations that patients with a history of any previous vaccine allergy be referred to an allergist for further review on suitability to proceed with mRNA-based COVID-19 vaccines. We review the evaluation of these patients with suspected vaccine allergies prior to receiving mRNA-based COVID-19 vaccines. Method(s): Between 8 April and 22 September 2021, 304 patients were evaluated prior to receiving the COVID-19 vaccinations. Of these, 63 (20.7%) patients with suspected immediate hypersensitivity reactions to non-COVID polysorbate-containing vaccines proceeded to have skin prick test (SPT) and Intradermal test (IDT) to polyethylene glycol (PEG)-3350, polysorbate 80 and polysorbate 20 containing products. Another 62 (20.4%) who reported delayed hypersensitivity reactions to polysorbate-containing vaccines proceeded to have direct inoculation (DI) of the Pfizer BNT162b2 vaccine under the supervision of an allergist. The remaining 242 (76.6%) finally assessed not allergic polysorbate-or tolerated previous non-polysorbate- containing vaccines were recommended to proceed with COVID-19 vaccinations at the community vaccination sites. 99 patients in the SPT/IDT and DI group completed a questionnaire-based survey to report any post vaccination reactions. (Figure 1) Results: Of 63 patients who underwent SPT/IDT, 2 (3.2%) with equivocal IDT tolerated both doses of the BNT162b2 vaccine without major allergic reactions. 61 (6.8%) patients with negative SPT/IDT and 62 (100%) in the DI group completed both doses of BNT162b2 vaccination without major reactions. Among those who completed the questionnaire survey, 13 (13%) reported reactions including non-specific rashes and mild urticaria/angioedema post first dose vaccine. All subsequently completed the second dose of the BNT162b2 vaccine following allergist review;with 8 (61.5%) reporting similar mild skin reactions. Conclusion(s): Majority of those with suspected reactions to polysorbate containing vaccines are able to tolerate the BNT162n2 vaccine which contains PEG-2000. Skin tests prior to mRNA COVID-19 vaccination is unnecessary. Those who report mild potentially allergic reactions after the first dose are able to tolerate the second dose of the BNT162b2 vaccine.

Evolving Perceptions of Mental Health on Social Media and their Medical Impacts

Mental health is an ever-growing issue of concern, especially in light of the COVID pandemic. In this context, we study big data from social media over a 7-year time span to gauge evolving perceptions of mental health, and discuss our research findings, potentially useful for decision support in healthcare. We deploy topic modeling and sentiment analysis to estimate public perceptions of mental health issues, focusing on Twitter as the social media site. We claim that it is important to consider polarity as well as subjectivity in sentiment analysis to comprehend two different aspects of sentiment, i.e. orientation in the emotion, and extent of fact vs. opinion. We assert that ranking via topic modeling is beneficial to fathom the relative importance of issues over the years. We harness tools/techniques from natural language processing and data mining to discover knowledge from big data on social media, related to mental health. Some of our findings reveal that the sentiment around mental health has remained positive overall, but has decreased since the beginning of the COVID pandemic. Major events, such as elections and the pandemic, greatly impact the conversation surrounding mental health. Some topics have remained consistent throughout the years. In other topics, the tone of the public discussions has shifted. The outcomes of our study would be useful to a variety of professionals, ranging from data scientists to epidemiologists and psychologists. This work impacts big healthcare data in general. © 2022 IEEE.

Identification of shared genes and possible therapeutic target between systemic lupus erythematosus and COVID-19

Background/purpose: Coronavirus disease 2019 (COVID-19) has led to a rapid increase in mortality worldwide. Systemic lupus erythematosus (SLE) was a high-risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2) infection, Whereas the molecular mechanisms underlying SLE and CVOID-19 are not well understood. This study aims to discover the common molecular mechanisms and genetic biomarkers of SLE and COVID-19, providing new ideas for the treatment of COVID-19. Method(s): RNA sequencing data of peripheral blood mononuclear cells (PBMC) from 6 SLE datasets and 8 COVID-19 datasets were obtained from the GEO database. Highly related modular genes associated with COVID-19 and SLE were identified by weighted gene co-expression network analysis (WGCNA). The differentially expressed genes (DEGs) between patients and healthy controls (HCs) were identified by the limma package. Common shared DEGs from COVID-19 and SLE were identified. Cytoscape and MCODE plugin were utilized for exploring the protein-protein interaction network (PPI) and identifying shared hub genes. Potential biological functions and pathways were also explored from the common DEGs. For better analysis of detailed biological mechanisms, both xCell algorithm and the cMap in CLUE (https://clue.io/) were utilized for discovering immune cell infiltration and predicting potential drugs that negatively regulate the highly expressed genes. Result(s): With identified 498 up-regulated common DEGs in SLE and COVID-19 related genes, total 11 and 13 gene modules of SLE and COVID-19 were identified espectively After overlapping differential genes, the final intersection gene set contains 218 genes. The PPI, especially the functional subnet module consists of upregulated genes by MCODE showed a great deal IFN related genes involved in the regulation of immunity. GO biological processes also showed possible functions were defense response to virus and mitotic cell cycle. Moreover, changes of most immune cells were strongly consistent between SLE and COVID-19. CDK inhibitors identified may be more likely to inhibit two diseases. Conclusion(s): Our study examined in detail the common molecular mechanisms of SLE and COVID-19, in which cellular response to cytokine stimulus, like regulating IFN, which might be the key target of both diseases. CDK is associated with the progression of SLE and COVID-19, which may be the potential therapeutic drug for SLE patients with COVID-19 infection.

Molecular mechanisms underlying regulatory T cell deficiency and potential drugs in COVID-19

Background/Purpose: The 2019 outbreak of coronavirus disease COVID-19 causes immune system disruption. Recent studies reported that the decrease or depletion of regulatory T cell (Treg) may be responsible for overstimulation of the immune system and lung damage in patients with severe COVID-19. This study aims to find the molecular mechanisms and genetic biomarkers associated with Tregs in COVID-19, providing new ideas for the treatment of COVID-19. Method(s): RNA sequencing data of peripheral blood mononuclear cells (PBMC) from 252 COVID-19 infected patients and 69 healthy controls (HC) were obtained from the GEO database. The Tregs composition of COVID-19 samples was quantified using the CIBERSORT deconvolution method. The differential genes (DEGs) were identified by the limma R package. Gene co-expression network analysis (WGCNA) was used to identify the gene. Differentially expressed Tregs-related genes (DETregRGs) were obtained by intersecting DEGs with the highly related modular genes obtained in the previous step. The potential biological functions and pathways of DETregRGs were then explored. Protein-protein interaction (PPI) networks were subsequently constructed to identify hub genes. In addition, the prediction of small molecule drugs for the potential treatment of COVID-19 was made using the CMap database. Result(s): After the weighted gene co-expression network analysis (WGCNA), the turquoise module was highly correlated with Treg expression and a total of 134 DEGs was identified as DETregRGs. These genes were mainly involved in GO biological processes, such as the inflammatory response, and T cell differentiation of thymus. Then, 11 hub genes (including RPS12, RPL21, RPS3A, CD8B, CD3D, TRAT1, RPS6, CD3E, CD28, RPL3, and CD4) were ranked based on Molecular Complex Detection (MCODE) analysis. The TregRG score of COVID-19 patients showed significantly lower than HC, calculated by the 'singscore' algorithms. After the signature query of the CMap database, the KU-0063794, an mTOR inhibitor ranked second in the negative enrichment score, may restore immune system dysregulation caused by increased Th17 differentiation and decreased Treg differentiation during SARS-CoV- 2 infection. Conclusion(s): Our study examined in detail the molecular mechanisms underlying the inadequacy of Tregs in patients with COVID-19 infection. mTOR inhibitors may improve COVID-19 symptoms by expanding Tregs which may be one of the potential therapeutic methods that need further investigation. (Figure Presented).

The rejuvenation of urban community in China under COVID-19

The persistent COVID-19 pandemic has continuously brought the basic level of urban governance to the forefront. Urban community governance in China involves both state-led and civil society-led governance. Whilst previous studies have noted the weak civil society and delocalization in modern China, recent research reveals the re-localization trend shown during the pandemic. In this brief research report, we seek to provide a detailed account of the hyper-local dynamism within civil society in responding to the public health emergency, focusing on the thriving spontaneous groups in Shanghai during the COVID-19 outbreak in March and April 2022. By dissecting the multi-level, multi-actor governance, we reveal the significant roles played by spontaneous groups in complementing state-led governance and in building united urban communities in combatting the worst effects of COVID-19. We outline the types and organizational structure of various spontaneous groups. We also critically reflect on their implications and potential in advancing urban community governance in China. We argue that there is an imperative need to further explore how these spontaneous groups can catalyze transformative changes that can for example empower grassroots actors and motivate wider public participation in community decision-making. Copyright © 2022 Xie and Shao.

[Clinical update in critical care of pulmonary medicine 2022].

In this review, we outlined the clinical studies in critical care field of pulmonary medicine from October 1, 2021 to September 30, 2022. For critically ill patients, frailty before disease onset was a predictor of mortality with increasing ICU length of stay, and the complaints of dyspnea in intubated phase was independently associated with posttraumatic stress disorder. Compared with transbronchial lung biopsy (TBLB) for patients with acute hypoxemic respiratory failure, transbronchial lung cryobiopsy (TBLC) had a positive significance to in leading to an increased chance of establishing a more accurate diagnosis, which could significantly improve the patients' prognosis. M-ROSE (microbiological rapid on-site evaluation) had high diagnostic value for lower respiratory tract pathogens, and the application of M-ROSE in the ICU could contribute to promoting a decrease in patients' inflammation levels and reducing the mortality of patients with invasive mechanical ventilation. EIT (electrical impedance tomography), DPL (transpulmonary driving pressure) and DPaw (airway driving pressure) had excellent positive values on dynamic assessment, guiding individualized respiratory support and prognostic evaluation. In critically ill hospitalized patients with COVID-19 who had received invasive mechanical ventilation or extracorporeal membrane oxygenation, treatment with baricitinib compared with placebo (in combination with standard of care, including corticosteroids) might reduce mortality. Delayed antimicrobial treatment significantly increased the incidence of severe infection and the mortality of shock patients, however, timing of antimicrobial therapy and control of the source of infection was critical. NIV (non-invasive ventilation) alternating with high-flow nasal oxygen immediately after extubation significantly decreased the risk of reintubation and death compared with high-flow nasal oxygen alone in obese or overweight patients at high risk of extubation failure. The effect of Pes-guided positive end-expiratory pressure (PEEP), compared with empirical high PEEP, was associated with lower mortality for more severe acute respiratory distress syndrome (ARDS) ventilated patients (APACHE Ⅱ>27.5). Prone-positioning during veno-venous extracorporeal membrane oxygenation was safe and effective and was associated with a higher probability of surviving and being weaned-off extracorporeal membrane oxygenation at 90 days. Therefore, individualized respiratory support strategies based on dynamic monitoring and assessment were essential for critically ill patients.

Analyzing Extreme Events in Power Systems: An Open, Cross-Domain Data-Driven Approach

Over the past several years the electric power sector has been challenged by a number of extreme events around the globe. Significant societal and economic shocks were due to the rapid spread of COVID-19 around the world. In addition to the pandemic, there have been several extreme weather and societal disruptions to the electricity sector, such as the February 2021 Texas power outage and the 9 p.m. nine-minute blackout event in India. © 2003-2012 IEEE.

IMPACT OF PERSISTENT COVID-19 SYMPTOMS ON PHYSICAL ACTIVITY AND CARDIORESPIRATORY PERFORMANCE IN VULNERABLE CHILDREN AND ADOLESCENTS

SESSION TITLE: Late Breaking Chest Infections Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: 10/18/2022 01:30 pm - 02:30 pm PURPOSE: The science continues to develop in terms of the epidemiology of persistent, or long COVID, especially in the pediatric population. The impact of persistent COVID-19 on cardiorespiratory fitness in the form of physical activity and athletic performance among children/adolescents is not well described, especially among vulnerable populations. METHODS: A retrospective electronic health record review identified children/adolescents with previously diagnosed COVID (N=312, 52.9% male, mean age at diagnosis 6.6 [SD 5.9] years, 20.5% non-Hispanic White [NHW], 19.2% non-Hispanic Black [NHB], and 54.5% Hispanic, 85.26% hospitalized due to COVID-19 illness) from one pediatric healthcare system that serves predominantly Medicaid-dependent families. Patients or caregivers completed a follow-up telephone survey from March 2021- February 2022 to estimate the prevalence of persistent COVID symptoms, defined as the presence of symptoms lasting ≥ 30 days. Multiple logistic regression models explored the association between physical activity and the presence of long COVID. RESULTS: 71 (22.8%) patients reported long COVID and the most prevalent symptoms included tiredness (21 [6.7%]), shortness of breath (18 [5.8%]), cough (16 [5.1%]), headache (14 [4.5%]), difficulty with thinking/concentration (14 [4.5%]), disrupted sleep (14 [4.5%]), other symptoms (12 [3.8%]), anxiety (11 [3.5%]), body aches (11 [3.5%]), joint pain (10 [3.2%]) chest pain (9 [2.9%]), intermittent fever (6 [1.9%]), and loss taste/smell (5 [1.6%]). Almost a third (32%, N = 24) of patients who participated in any athletics or physical activity in or outside of school reported a negative impact on physical or athletic performance, and 66.7% reported it was directly related to COVID-19 illness. Specific complaints when returning to physical activity post-COVID illness included tiredness (7 [36.8%]) and shortness of breath (2 [10.5%]). The odds of a decline in physical activity performance was over twice that (OR 2.17, 95% CI 0.54-8.71, p = 0.28) among children with long COVID versus those reporting no long COVID after adjusting for demographics. There was no difference by age (mean 9.8 vs. 9.7 years, p = 0.93), sex (50% girls vs. 50% boys, p =0.71), or race/ethnicity (25% NHW vs. 25% NHB vs. 37.5% Hispanic, p = 0.25) in terms of decline in physical activity performance. Two children were recommended to delay re-entry into physical activity. CONCLUSIONS: A substantial proportion of ethnically diverse children from low resource backgrounds who had severe COVID illness are reporting long-term impacts on physical activity and cardiorespiratory fitness. Findings can inform pediatricians about this vulnerable population in post-COVID-19 recovery efforts. CLINICAL IMPLICATIONS: Pediatric pulmonologists and other sub-specialists should screen and monitor patients who have had previous severe COVID-19 illness for persistent cardiorespiratory impacts. DISCLOSURES: No relevant relationships by Kubra Melike Bozkanat No relevant relationships by Jackson Francis No relevant relationships by Weiheng He No relevant relationships by Alejandra Lozano No relevant relationships by Matthew Mathew No relevant relationships by Sarah Messiah No relevant relationships by Angela Rabl No relevant relationships by Sumbul shaikH No relevant relationships by Nimisha Srikanth No relevant relationships by Apurva Veeraswamy No relevant relationships by Sitara Weerakoon No relevant relationships by Luyu Xie

Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data

Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to local health departments to limit the spread of the disease. Understanding the spatio-temporal dynamics of hotspot events is of great importance to support policy decisions and prevent large-scale outbreaks. This paper presents a spatio-temporal Bayesian framework for early detection of COVID-19 hotspots (at the county level) in the United States. We assume both the observed number of cases and hotspots depend on a class of latent random variables, which encode the underlying spatio-temporal dynamics of the transmission of COVID-19. Such latent variables follow a zero-mean Gaussian process, whose covariance is specified by a non-stationary kernel function. The most salient feature of our kernel function is that deep neural networks are introduced to enhance the model's representative power while still enjoying the interpretability of the kernel. We derive a sparse model and fit the model using a variational learning strategy to circumvent the computational intractability for large data sets. Our model demonstrates better interpretability and superior hotspot-detection performance compared to other baseline methods. IEEE

High-Resolution Spatio-Temporal Model for County-Level COVID-19 Activity in the U.S

We present an interpretable high-resolution spatio-temporal model to estimate COVID-19 deaths together with confirmed cases 1 week ahead of the current time, at the county level and weekly aggregated, in the United States. A notable feature of our spatio-temporal model is that it considers the (1) temporal auto- and pairwise correlation of the two local time series (confirmed cases and deaths from the COVID-19), (2) correlation between locations (propagation between counties), and (3) covariates such as local within-community mobility and social demographic factors. The within-community mobility and demographic factors, such as total population and the proportion of the elderly, are included as important predictors since they are hypothesized to be important in determining the dynamics of COVID-19. To reduce the model's high dimensionality, we impose sparsity structures as constraints and emphasize the impact of the top 10 metropolitan areas in the nation, which we refer to (and treat within our models) as hubs in spreading the disease. Our retrospective out-of-sample county-level predictions were able to forecast the subsequently observed COVID-19 activity accurately. The proposed multivariate predictive models were designed to be highly interpretable, with clear identification and quantification of the most important factors that determine the dynamics of COVID-19. Ongoing work involves incorporating more covariates, such as education and income, to improve prediction accuracy and model interpretability.

Photoaging Characteristics of Disposable Masks under UV Irradiation

The global outbreak of Corona Virus Disease 2019 (COVID-19) has led to an extreme increase in the use of disposable masks. If the used disposable masks are not appropriately disposed of, they will enter the natural environment and lead to environmental pollution. In order to understand the impacts of disposable masks after being disposed of into the natural environment, aging experiments with simulated natural conditions were performed on the outer, inner, and middle layers of the masks to verify the aging characteristics of disposable masks. We analyzed the mechanical behavior, surface morphology, and Fourier Transform Infrared Spectroscopy (FT-IR) spectra of disposable masks treated with different levels of UV irradiation to understand the possible changes in the masks under UV. Results showed that the elongation at break, tensile strength, and maximum force of all three polypropylene (PP) mask layers decreased after UV irradiation, indicating chemical bond breakage. In the process of photoaging, each layer of the disposable masks showed a different degree of microscopic surface changes after UV irradiation, and these changes gradually intensified with the extension of UV exposure time. FT-IR results showed that functional groups, such as hydroxyl and carbonyl groups increased in each layer after UV irradiation. The results of this study support that, although the different layers of the disposable masks are all made of PP, they age differently in the environment. With the ever-increasing number of disposable masks in the environment, we need to further study the aging and degradation of disposable masks to better understand their potential impacts on the environment in the future. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Bioinformatics analysis of high-throughput sequencing to identify key genes and signaling pathways in vero E6 cells infected by SARS-CoV-2

Background: In 2020, the coronavirus disease 2019 began spreading widely across the world. We aim to study the biological changes of SARS-CoV-2 infected Vero cells using high-throughput sequencing data, which will be helpful for vaccine development and drug screening. Methods: The data GSE153940 was obtained from the Gene Expression Omnibus database. R software was used to screen out differentially expressed genes and perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein-protein interaction network was built by STRING. Cytoscape 3.7.2 was applied for the visualization of the protein-protein interaction network and the identification of the hub genes. GraphPad Prism 8.4.3 was used to perform the statistical analysis to verify the obtained central genes. Results: A total of 3640 differentially expressed genes were obtained. The most significant enrichment items of Gene Ontology in the biological process, cellular component, and molecular function were the regulation of mRNA metabolic process, organelle inner membrane, and cadherin binding respectively. Ten enrichment pathways were identified by the Kyoto Encyclopedia of Genes and Genomes analyses. A protein-protein interaction network with 328 nodes and 498 edges was established. Six hub genes were screened out, among which four genes (MRPS7, DAP3, CHCHD1 and MRPL3) were confirmed to be statistically significant. Conclusions: Our results suggest that mitochondrial activity has a significant role in the process of SARS-CoV-2 infecting Vero E6 cells. Further experimental studies are needed to obtain abundant data to verify the predicted results of the bioinformatics analysis.

Kawasaki disease is not linked to COVID-19 in Chinese pediatric population

Increasing cases of children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presenting with severe Kawasaki-like disease have recently been reported in some Western countries, raising the possibility of SARS-CoV-2 being a trigger of Kawasaki disease (KD). We aimed to investigate whether KD is linked to coronavirus disease 2019 (COVID-19) in Chinese pediatric population. Methods: Patients were enrolled if diagnosed with KD in the 40 hospitals of China Kawasaki Disease Research Collaborative Group from January to April 2020, the COVID-19 epidemic period in China. Information of demographic data, KD shock syndrome, macrophage activation syndrome (MAS), evidence of SARS-CoV-2 infection and the number of KD cases were retrospectively analyzed. Results: The completed response was received from 29/40 hospitals (72.5%) across 19 provinces. Of 2,108 KD patients enrolled, the median age was 1.9 years and 63.8% were male. KD shock syndrome and MAS were diagnosed in 8 (0.4%) and 2 (0.1%) patients, respectively, none of whom had contact history with COVID-19 patients. A greater number of KD cases from January to April 2020 than the upper limit of 95% confidence interval (95% CI) of estimated numbers of cases of the past 3 years were observed in only 2 out of 29 (6.9%) hospitals. Reverse transcription-polymerase chain reaction (RT-PCR) tests in 434 patients and antibody tests in 64 patients for SARS-CoV-2 were all negative, including nine with exposure history. Conclusions: There is no evidence of the link of KD with COVID-19 in Chinese children in terms of its prevalence and severity. © Pediatric Medicine. All rights reserved.