Frontiers of COVID-19: Scientific and Clinical Aspects of the Novel Coronavirus 2019

This book aims to serve the critical interests of the global community by supplying the most current knowledge and understanding of Covid-19 epidemiology, treatment, and prognoses. There was much uncertain and contradictory information published in the first year of the novel coronavirus. The dynamics of COVID-19 have now been realized, including the type of antibodies produced in infected patients and their limited lasting endurance. This book will set the record straight on the concept of "herd immunity” and explore the current vaccine trials taking place in different countries. This comprehensive book will illuminate recent advances regarding COVID-19 and offer a possible roadmap on how to move forward. Frontiers of COVID-19: A Pathophysiology and Epidemiology Roadmap of Novel Coronavirus Disease will be a vital and forward-looking guide for infectious disease clinicians, scientists and researchers, and students at the graduate level. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Kawasaki Disease in the Time of COVID-19 and MIS-C - The International Kawasaki Disease Registry.

BACKGROUND: Patients with Multisystem Inflammatory Syndrome in Children (MIS-C) and Kawasaki disease (KD) have overlapping clinical features. We compared demographics/clinical presentation, management, and outcomes of patients by evidence of prior SARS-CoV-2 infection. METHODS: The International KD Registry (IKDR) enrolled KD and MIS-C patients from sites from North, Central and South America, Europe, Asia and Middle East. Evidence of prior infection was defined as: Positive (+ve household contact or positive PCR/serology), Possible (suggestive clinical features of MIS-C and/or KD with negative PCR or serology but not both), Negative (negative PCR and serology and no known exposure), and Unknown (incomplete testing and no known exposure). RESULTS: Of 2345 enrolled patients SARS-CoV-2 status was Positive for 1541 (66%) patients, Possible 89 (4%), Negative 404 (17%) and Unknown for 311 (13%) patients. Clinical outcomes varied significantly between the groups, with more patients in the Positive/Possible groups presenting with shock, having admission to Intensive Care, receiving inotropic support, and having longer hospital stays. Regarding cardiac abnormalities, patients in the Positive/Possible groups had a higher prevalence of left ventricular dysfunction, while patients in the Negative and Unknown groups had more severe coronary artery abnormalities. results CONCLUSION: : There appears to be a spectrum of clinical features from MIS-C to KD with a great deal of heterogeneity, and one primary differentiating factor is evidence for prior acute SARS CoV2 infection/exposure. SARS-CoV-2 Positive/Possible patients had more severe presentations and required more intensive management, with a greater likelihood of ventricular dysfunction but less severe coronary artery adverse outcomes, in keeping with MIS-C.

Genetic Predisposition to a Vascular Catastrophe: Does It Affect Severe COVID-19?

Introduction. Targeted at the hemostatic system and the vascular endothelium, COVID-19 triggers the pathogenetic cascade of disorders in these systems. This cascade leads to the cerebral infarction, significant aggravation of other neurovas-cular diseases and neurological disorders, which requires an in-depth study. Objective: to identify the impact of factors selected among 21 candidate genes and metabolic markers on disease severity and the probability of death from SARS-CoV-2 infection in patients with a history of ischemic stroke (IS) and apparently healthy participants. Materials and Methods. We analyzed genetic, clinical, and laboratory findings in 85 patients with IS occurred at least one year before the study. During the first stage, participants were divided into three groups: Group 1 — 25 patients with a history of IS and COVID-19 at least one year prior to the study;Group 2 — 35 patients with IS history and no clinical manifestations or known COVID-19 history at baseline;and Group 3 — 20 apparently healthy participants as controls who had no clinical manifestations or information about a positive test for COVID-19 at baseline (November 2021). During the second stage, a new Group 4 included 25 patients with a history of IS who were treated for COVID-19 at baseline. Single venous blood tests were used to assess the levels of metabolic markers and identify genetic polymorphisms of hemostasis, immune response, endothelial function, and lipid metabolism in all study participants. Results. We identified the significant factors that determined the irreversible effects (damage) and fatal outcomes in patients with COVID-19 via the throm-bophilia genetic polymorphisms variations as follows: F13 encoding fibrin-stabilizing factor XIII — fibrinase (statistical probability of the factor influence > 90%), and SERPINE1 encoding endothelial plasminogen activator inhibitor-1 (PAI-1;statistical probability of the factor influence > 95%). High admission levels of homocysteine, interleukin-6, and activated partial thromboplastin time in patients with COVID-19 were associated with a severe disease course and fatal outcomes. Conclusion. Information about gene variations that trigger thrombosis and the adequate immune response can improve the effectiveness of specific therapy. Patients should understand their genetic profile, since this knowledge may prevent COVID-19 complications and significantly reduce the risk of a vascular catastrophe. © Dutova T. I., Banin I. N., Sazonov I. E., Peleshenko E. I., 2023.

Significance of"Qingfei" and "Paidu" of Qingfei Paidu Decoction in Treatment of COVID-19.

Traditional Chinese medicine(TCM)has played an important role in the prevention and treatment of novel coronavirus disease 2019(COVID-19). Qingfei Paidu decoction, as a general prescription of Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia from the sixth to eighth versions, has been proved effective clinically and is suitable for mild, moderate, severe, and critical patients. It can significantly improve clinical symptoms such as fever, cough, asthma, fatigue, etc. On the basis of the findings of relevant research papers, this paper summarized the TCM understanding of COVID-19, including etiology, pathogenesis, disease location, and treatment, and concluded that the disease is caused by the pestilential Qi, localized in the lungs, and can affect the five organs. It is mainly characterized by coldness, dampness, heat, toxicity, stasis, and deficiency. In response to the etiology and pathogenesis of the disease, the therapeutic principles at all stages are dominated by the elimination of pathogens and removal of toxicity. According to the stages of disease development, the treatment should combine the severity of the disease and the course of the disease with the TCM syndromes. Furthermore, from the clinical application of Qingfei Paidu decoction, this paper discussed the therapeutic intention of "Qingfei(clearing of lungs)" and "Paidu(removal of toxicity)". Qingfei Paidu decoction can clear the pathogenic toxin in the lungs and eliminate external pestilential Qi, which is in line with the therapeutic principles for this pandemic by regulating the triple energizer and protecting healthy Qi using both coldness and warmth to treat both the symptoms and the root cause. Additionally, the experimental research progress on Qingfei Paidu decoction and its modified prescriptions were summarized. As studied, this prescription can inhibit cytokine storm, moderate the overactive immune response, potentiate the immune function and anti-viral ability of the body, and exert its effect on COVID-19 with multiple components, multiple targets, multiple pathways, and multiple biological functions. In conclusion, Qingfei Paidu decoction, as a core prescription for the treatment of COVID-19, can rapidly contain the development of COVID-19, which has been confirmed in terms of TCM theory, clinical efficacy, and experimental research.Copyright © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.

SARS-CoV-2 Vaccine Effectiveness against Omicron Variant in Infection-Naive Population, Australia, 2022.

SARS-CoV-2 transmission in Western Australia, Australia, was negligible until a wave of Omicron variant infections emerged in February 2022, when >90% of adults had been vaccinated. This unique pandemic enabled assessment of SARS-CoV-2 vaccine effectiveness (VE) without potential interference from background immunity from prior infection. We matched 188,950 persons who had a positive PCR test result during February-May 2022 to negative controls by age, week of test, and other possible confounders. Overall, 3-dose VE was 42.0% against infection and 81.7% against hospitalization or death. A primary series of 2 viral-vectored vaccines followed by an mRNA booster provided significantly longer protection against infection >60 days after vaccination than a 3-dose series of mRNA vaccine. In a population free from non-vaccine-derived background immunity, vaccines against the ancestral spike protein were ≈80% effective for preventing serious outcomes from infection with the SARS-CoV-2 Omicron variant.

US National Institutes of Health Prioritization of SARS-CoV-2 Variants.

Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. The group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.

A Case of COVID-19-Induced Immune Thrombocytopenia (ITP) in an Adult Female: An Under-Recognized Emerging Phenomenon.

Coronavirus disease 2019 (COVID-19) follows a mild course in majority of cases, but some patients may develop non-pulmonary yet life-threatening complications. A Pandora's box had been opened when multisystem hyper-inflammatory syndromes and autoimmune diseases that had been described previously in children and young adults, that are associated with COVID-19, have now emerged in adults. They need to be recognized as important sequelae of severe COVID-19 disease. Immune thrombocytopenia (ITP) or thrombocytopenic purpura is an autoantibody and T-cell-mediated autoimmune disorder characterized by isolated thrombocytopenia, which can be triggered by different infections. First-line treatment of severe ITP includes platelet transfusions in life-threatening cases, followed by corticosteroids and intravenous immunoglobulins (IVIG). Since the beginning of the pandemic, more and more cases of COVID-19-associated ITP have been reported. We report a case of acquired ITP in a young woman that could only be attributed to her COVID-19 infection and was refractory to platelet transfusion, requiring further treatments. The aim of this report is to review some of the etiologies and purposed molecular mechanisms of the autoimmune nature of the disease and to focus on diagnosis and treatment. We will review the current literature surrounding this non-pulmonary manifestation of COVID-19 and current treatment options for this uncommon presentation of ITP.

Human-to-Animal Transmission of SARS-CoV-2, South Korea, 2021.

To investigate SARS-CoV-2 transmission from humans to animals in Seoul, South Korea, we submitted samples from companion animals owned by persons with confirmed COVID-19. Real-time PCR indicated higher SARS-CoV-2 viral infection rates for dogs and cats than previously reported from the United States and Europe. Host-specific adaptations could introduce mutant SARS-CoV-2 to humans.

SARS-CoV-2 severity prediction in young adults using artificial intelligence.

Aim: to build, a predictive model for severe COVID-19 prediction in young adults using deep learning methods. Material(s) and Method(s): data from 906 medical records of patients aged. 18 to 44 years with laboratory-confirmed SARS- CoV-2 infection during 2020-2021 period, was analyzed. Evaluation of laboratory and. instrumental data was carried out using the Mann-Whitney U-test. The level of statistical significance was p<0,05. The neural network was trained, using the Pytorch. framework. Result(s): in patients with mild to moderate SARS-CoV-2 infection, peripheral oxygen saturation, erythrocytes, hemoglobin, total protein, albumin, hematocrit, serum, iron, transferrin, and. absolute peripheral blood, eosinophil and. lymphocyte counts were significantly higher than in patients with severe SOVID-19 (p< 0,001). The values of the absolute number of neutrophils, ESR, glucose, ALT, AST, CPK, urea, LDH, ferritin, CRP, fibrinogen, D-dimer, respiration rate, heart rate, blood, pressure in the group of patients with mild and. moderate severity were statistically significantly lower than in the group of severe patients (p < 0.001). Eleven indicators were identified as predictors of severe COVID-19 (peripheral oxygen level, peripheral blood erythrocyte count, hemoglobin level, absolute eosinophil count, absolute lymphocyte count, absolute neutrophil count, LDH, ferritin, C-reactive protein, D-dimer levels) and. their threshold, values. A model intended, to predict COVID-19 severity in young adults was built. Conclusion. The values of laboratory and instrumental indicators obtained in patients with SARS-CoV-2 infection upon admission significantly differ. Among them, eleven indicators were significantly associated with the development of a severe COVID-19. A predictive model based, on artificial intelligence method, with high, accuracy predicts the likelihood, of severe SARS-CoV-2 course development in young adults.Copyright © 2022 Interregional public organization Association of infectious disease specialists of Saint-Petersburg and Leningrad region (IPO AIDSSPbR). All rights reserved.

SARS-CoV-2 severity prediction in young adults using artificial intelligence

Aim: to build, a predictive model for severe COVID-19 prediction in young adults using deep learning methods. Materials and methods: data from 906 medical records of patients aged. 18 to 44 years with laboratory-confirmed SARS- CoV-2 infection during 2020—2021 period, was analyzed. Evaluation of laboratory and. instrumental data was carried out using the Mann-Whitney U-test. The level of statistical significance was p<0,05. The neural network was trained, using the Pytorch. framework. Results: in patients with mild to moderate SARS-CoV-2 infection, peripheral oxygen saturation, erythrocytes, hemoglobin, total protein, albumin, hematocrit, serum, iron, transferrin, and. absolute peripheral blood, eosinophil and. lymphocyte counts were significantly higher than in patients with severe СOVID-19 (p< 0,001). The values of the absolute number of neutrophils, ESR, glucose, ALT, AST, CPK, urea, LDH, ferritin, CRP, fibrinogen, D-dimer, respiration rate, heart rate, blood, pressure in the group of patients with mild and. moderate severity were statistically significantly lower than in the group of severe patients (p < 0.001). Eleven indicators were identified as predictors of severe COVID-19 (peripheral oxygen level, peripheral blood erythrocyte count, hemoglobin level, absolute eosinophil count, absolute lymphocyte count, absolute neutrophil count, LDH, ferritin, C-reactive protein, D-dimer levels) and. their threshold, values. A model intended, to predict COVID-19 severity in young adults was built. Conclusion. The values of laboratory and instrumental indicators obtained in patients with SARS-CoV-2 infection upon admission significantly differ. Among them, eleven indicators were significantly associated with the development of a severe COVID-19. A predictive model based, on artificial intelligence method, with high, accuracy predicts the likelihood, of severe SARS-CoV-2 course development in young adults. © 2022 Interregional public organization Association of infectious disease specialists of Saint-Petersburg and Leningrad region (IPO AIDSSPbR). All rights reserved.

SARS-CoV-2 severity prediction in young adults using artificial intelligence.

Aim: to build, a predictive model for severe COVID-19 prediction in young adults using deep learning methods. Material(s) and Method(s): data from 906 medical records of patients aged. 18 to 44 years with laboratory-confirmed SARS- CoV-2 infection during 2020-2021 period, was analyzed. Evaluation of laboratory and. instrumental data was carried out using the Mann-Whitney U-test. The level of statistical significance was p<0,05. The neural network was trained, using the Pytorch. framework. Result(s): in patients with mild to moderate SARS-CoV-2 infection, peripheral oxygen saturation, erythrocytes, hemoglobin, total protein, albumin, hematocrit, serum, iron, transferrin, and. absolute peripheral blood, eosinophil and. lymphocyte counts were significantly higher than in patients with severe SOVID-19 (p< 0,001). The values of the absolute number of neutrophils, ESR, glucose, ALT, AST, CPK, urea, LDH, ferritin, CRP, fibrinogen, D-dimer, respiration rate, heart rate, blood, pressure in the group of patients with mild and. moderate severity were statistically significantly lower than in the group of severe patients (p < 0.001). Eleven indicators were identified as predictors of severe COVID-19 (peripheral oxygen level, peripheral blood erythrocyte count, hemoglobin level, absolute eosinophil count, absolute lymphocyte count, absolute neutrophil count, LDH, ferritin, C-reactive protein, D-dimer levels) and. their threshold, values. A model intended, to predict COVID-19 severity in young adults was built. Conclusion. The values of laboratory and instrumental indicators obtained in patients with SARS-CoV-2 infection upon admission significantly differ. Among them, eleven indicators were significantly associated with the development of a severe COVID-19. A predictive model based, on artificial intelligence method, with high, accuracy predicts the likelihood, of severe SARS-CoV-2 course development in young adults.Copyright © 2022 Interregional public organization Association of infectious disease specialists of Saint-Petersburg and Leningrad region (IPO AIDSSPbR). All rights reserved.

Infectious disorders: HIV, hepatitis C, and COVID-19 pandemics

This chapter instead focuses on the neuropsychological manifestations and neuropathological underpinnings of three prominent pandemic infectious diseases: human immunodeficiency virus (HIV), hepatitis C virus (HCV), and the novel coronavirus disease of 2019 (COVID-19), given their substantial global prevalence. It shows how these pandemics highlight the complexities of characterizing neurocognition across varying dimensions of clinical disease. Through a predominantly neuropsychological lens, the chapter discusses how variations in disease duration, severity, degree of recovery, and treatment can affect brain health and related outcomes. Toward this end, it discusses how these mechanisms intersect and diverge in HIV and HCV, two historically severe infectious diseases that now have undergone significant advances in treatment. In turn, the chapter draws upon insights gained from researching the neuropsychological complications of these diseases in order to inform the assessment and diagnosis of neurocognitive impairment in the context of COVID-19. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Digital twins to fight against COVID-19 pandemic

This study is aimed to explore the anti-epidemic effect of artificial intelligence (AI) algorithms such as digital twins on the COVID-2019 (novel coronavirus disease 2019), so that the information security and prediction accuracy of epidemic prevention and control (P & C) in smart cities can be further improved. It addresses the problems in the current public affairs governance strategy for the outbreak of the COVID-2019 epidemic, and uses digital twins technology to map the epidemic P & C situation in the real space to the virtual space. Then, the blockchain technology and deep learning algorithms are introduced to construct a digital twins model of the COVID-2019 epidemic (the COVID-DT model) based on blockchain combined with BiLSTM (Bi-directional Long Short-Term Memory). In addition, performance of the constructed COVID-DT model is analyzed through simulation. Analysis of network data security transmission performance reveals that the constructed COVID-DT model shows a lower average delay, its data message delivery rate (DMDR) is basically stable at 80%, and the data message disclosure rate (DMDCR) is basically stable at about 10%. The analysis on network communication cost suggests that the cost of this study does not exceed 700 bytes, and the prediction error does not exceed 10%. Therefore, the COVID-DT model constructed shows high network security performance while ensuring low latency performance, enabling more efficient and accurate interaction of information, which can provide experimental basis for information security and development trends of epidemic P & C in smart cities. © 2022

Can Some Viral Respiratory Infections Observed Before the Pandemic Announcement Be Related to SARS-CoV-2?

OBJECTIVE: There have been doubts that SARS-CoV-2 has been circulating before the first case was announced. The aim of this study was to evaluate the possibility of COVID-19 in some cases diagnosed to be viral respiratory tract infection in the pre-pandemic period in our center. MATERIAL AND METHODS: Patients who were admitted to our hospital's pulmonary diseases, infectious diseases, and intensive care clinics with the diagnosis of viral respiratory system infection within a 6-month period between October 2019 and March 12, 2020, were screened. Around 248 archived respiratory samples from these patients were analyzed for SARS-CoV-2 ribonucleic acid by real-time-quantitative polymerase chain reaction. The clinical, laboratory, and radiological data of the patients were evaluated. RESULT(S): The mean age of the study group was 47.5 (18-89 years);103 (41.5%) were female and 145 (58.4%) were male. The most common presenting symptoms were cough in 51.6% (n = 128), fever in 42.7% (n = 106), and sputum in 27.0% (n = 67). Sixty-nine percent (n = 172) of the patients were pre-diagnosed to have upper respiratory tract infection and 22.0% (n = 55) had pneumonia, one-third of the patients (n = 84, 33.8%) were followed in the service. Respiratory viruses other than SARS-CoV-2 were detected in 123 (49.6%) patients. Influenza virus (31.9%), rhinovirus (10.5%), and human metapneumovirus (6.5%) were the most common pathogens, while none of the samples were positive for SARS-CoV-2 RNA. Findings that could be significant for COVID-19 pneumonia were detected in the thorax computed tomography of 7 cases. CONCLUSION(S): The negative SARS-CoV-2 real-time-quantitative polymerase chain reaction results in the respiratory samples of the cases followed up in our hospital for viral pneumonia during the pre-pandemic period support that there was no COVID-19 among our cases during the period in question. However, if clinical suspicion arises, both SARS and non-SARS respiratory viral pathogens should be considered for differential diagnosis.Copyright © Author(s).

Hydroxychloroquine: New Perspectives for an Indispensable Old Drug

Hydroxychloroquine (HCQ) is a multi-functional drug owing to its lysosomotropic, immunomodulatory, anti-inflammatory, anti-infective, antithrombotic, antitumoral (pronounced effects on autophagy and apoptosis processes) and beneficial metabolic properties (improved lipid profiles, decreased insulin resistance). We know that chronic low-dose HCQ therapy has been successfully used in a variety of chronic diseases such as rheumatological and dermatological disorders. Additionally, with all these effects mentioned above and showing synergism, HCQ can also be useful mostly as an adjuvant in the management of many chronic metabolic disorders, serious life-threatening conditions such as cardiovascular, neurological, oncological and infectious diseases, as well as their accompanying morbidities. More recently, this former drug, whose effectiveness has been shown in the global coronavirus disease 2019 (COVID-19) pandemic, has entered the spotlight again. Ongoing clinical trials testing HCQ in new indications and challenging diseases are still receiving great attention. In this article, the mechanisms of action, current clinical uses and new indications of HCQ therapy have been overviewed with a comprehensive literature review.Copyright © Necati Ozpinar. All rights reserved.

Perceived Stress and Psychological Impact Among Healthcare Workers at a Tertiaty Hospital in China During the COVID-19 Outbreak: The Moderating Role of Resilience and Social Support.

Aims: To investigate the psychological distress experienced by healthcare workers (HCWs) at a tertiary hospital in Changzhou, China, outside Wuhan, during the early stage of COVID-19 and evaluate the moderating effects of resilience and social support on the relationship between stress and psychological distress. Methods: The study was conducted between February 10 and 15, 2020, in a non-probabilistic way. The survey included questions regarding the risk of exposure, sociodemographics, perceived stress [10-item Perceived Stress Scale (PSS-10)], resilience [10-item Connor-Davidson Psychological Resilience (CD-RISC-10)], social support [Multidimensional Scale of Perceived Social Support (MSPSS)], and psychological distress [12-item General Health Questionnaire (GHQ-12)]. We applied the PROCESS macro for SPSS to test the hypotheses that resilience and social support moderated the stress response. In addition, a simple slope analysis was conducted when the interaction effect was statistically significant. Results: Some 33.6% of participants suffered from psychological distress (GHQ-12 ≥ 12). Perceived stress was positively related to psychological distress (r = 0.42, p < 0.001). In addition, resilience (ΔR2 = 0.03, p for interaction < 0.001) and social support (ΔR2 = 0.01, p for interaction <0.01) moderated the stress response. The impact of perceived stress on psychological distress was attenuated when subjects who were resilient (high ß = 0.15, p < 0.001; low ß = 0.36, p < 0.001), and perceived stress had less impact on psychological distress when social support was high (ß = 0.24, p < 0.001) rather than low (ß = 0.34, p < 0.001). Limitations: The cross-sectional design led to a lack of causal relationships between variables. Conclusions: Our data showed that resilience and social support moderated the stress response among HCWs in the pandemic, suggesting that improving resilience and social support could be appropriate targets to improve HCWs' mental health in the pandemic.

The impact of the Beirut blast on the COVID-19 situation in Lebanon.

AIM: On August 4, 2020, a massive explosion hit Lebanon's capital city, Beirut. The aim of this study was to explore the effect of the Beirut blast on the COVID-19 situation in the country. SUBJECT AND METHODS: Data on COVID-19 were retrieved from the Lebanese Ministry of Public Health (LMOPH), where all the COVID-19 positive cases were reported. The study was divided into two periods, considering the incubation period of the COVID-19 virus: (July 27-August 9, 2020) and (August 10-23, 2020). Information obtained included daily number of cases, tests, deaths, hospitalized patients, intensive care unit (ICU) patients, and mode of acquisition (local vs. expat). Daily positivity rates were reported per 100 tests. An independent sample t-test and a Joinpoint regression analysis were used to determine significance. A p value less than 0.05 was considered significant. RESULTS: A total of 201,010 tests were conducted during our studied period, with 8993 positive cases, constituting a total positivity rate of 4.5 per 100 tests. Case fatality rate over the studied period was 0.8%. The positivity rate of the period prior to August 10, 2020, was 2.7 per 100 tests, significantly less than that of the period following the explosion, which was 6.4 per 100 tests (p < 0.001). During our studied period, daily positivity rates were significantly increasing at a slope of 0.29 (p < 0.001). A significant increase in slope was noted on August 13, 2020 (p < 0.001). The number of hospitalized patients increased from 139 patients on July 27 to 266 on August 23, 2020, and that of ICU patients increased from 36 to 75. CONCLUSION: The port of Beirut explosion resulted in a significant increase in the daily number of positive COVID-19 cases. The aftermath of the explosion, the damage to healthcare facilities, and the overcrowding due to emergency efforts were contributing factors to that increase.

Effectiveness of BNT162b2 Vaccine against Omicron Variant Infection among Children 5-11 Years of Age, Israel.

We assessed effectiveness of the BNT162b2 vaccine against infection with the B.1.1.529 (Omicron) variant (mostly BA.1 subvariant), among children 5-11 years of age in Israel. Using a matched case-control design, we matched SARS-CoV-2-positive children (cases) and SARS-CoV-2-negative children (controls) by age, sex, population group, socioeconomic status, and epidemiologic week. Vaccine effectiveness estimates after the second vaccine dose were 58.1% for days 8-14, 53.9% for days 15-21, 46.7% for days 22-28, 44.8% for days 29-35, and 39.5% for days 36-42. Sensitivity analyses by age group and period demonstrated similar results. Vaccine effectiveness against Omicron infection among children 5-11 years of age was lower than vaccine efficacy and vaccine effectiveness against non-Omicron variants, and effectiveness declined early and rapidly.

Should Medical Students Be Overprotected? A Survey from China and Review About the Roles of Medical Student Under the COVID-19.

Objective: The impact of COVID-19 continues to this day, there are many disputes about how medical students should be managed and diverse arrangements were adopted by medical schools around all over the world. The purpose of this study was to discuss the risks and benefits of medical student participation in healthcare in the context of COVID-19. Methods: An online cross-sectional survey was distributed to 300 Medical students undergoing standardized training program (STP) in China-Japan Union Hospital of Jilin University. The survey included questions about basic demographic characteristics, roles and mental state of interns during the pandemic, comments on the University's management of medical students. Data were processed using SPSS 25.0 statistical analysis software, the comparison between two groups of data was performed using t-test; the non-normally distributed variables were analyzed using Mann-Whitney U-test, differences between groups were compared using chi-square test for analysis. p < 0.05 was considered statistically significant. Results: A total of 191 students completed the survey (response rate 63.67%). The epidemic had a significant psychological impact on students, but most of them believed that participation in clinical work under voluntary, precise protective measures and strict supervision were benefit for their future. Older, married, female, and salaried students are more willing to engage in pandemic-related activities. The biggest challenge of working under the pandemic focused on high working pressure and insufficient protection, the biggest harvest was getting knowledge and accumulating experience. Conclusion: Circumstances, cultures, outbreaks and strategies for coping with COVID-19 varied around the world. Medical students do not need to be overprotected, participation in pandemic work in an optimized system is acceptable and beneficial to their career plan. Medical education should focus on improving the social status of infectious diseases and cultivating future doctors with awareness of epidemic prevention and control.

Insights into COVID-19-associated critical illness: a narrative review.

Background and Objective: Since the outbreak of the 2019 novel coronavirus disease (COVID-19), acute respiratory distress syndrome (ARDS) and sepsis resulting from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have surged in intensive care units around the world. The heterogeneity of ARDS and sepsis has long been observed, and multiple subphenotypes and endotypes correlated with different outcomes and treatment response have been identified in the search for treatable traits. Despite their similarity to typical ARDS and sepsis, COVID-19-associated ARDS and sepsis harbor distinct features, raising the question as to whether they could be considered as subphenotypes or endotypes of the historical syndromes and, accordingly, benefit from specific therapeutic strategies. This review aimed to summarize and discuss the current knowledge of COVID-19-associated critical illness and the intrinsic subphenotypes or endotypes. Methods: Literature on the pathogenesis of COVID-19 and the subphenotyping of COVID-19-associated critical illness was derived from the PubMed database and reviewed. Key Content and Findings: Accumulating evidence, varying from clinical observation to basic research, has contributed to revealing the fundamental pathophysiological features of severe COVID-19 and has advanced our knowledge of the disease. COVID-19-associated ARDS and sepsis exhibit some distinctive features compared to the classic syndromes, including remarkable vascular abnormality and coagulopathy, and distinct respiratory mechanics and immune response. Some conventional subphenotypes derived from classic ARDS and sepsis have been validated in COVID-19, while novel subphenotypes and endotypes have also been identified in patients with this disease, who experience variable clinical outcomes and treatment responses. Conclusions: Subphenotyping of COVID-19-associated ARDS and sepsis can provide new insights into the development and management of these illnesses.