COVID-19 Infection Segmentation and Severity Assessment Using a Self-Supervised Learning Approach.

BACKGROUND: Automated segmentation of COVID-19 infection lesions and the assessment of the severity of the infections are critical in COVID-19 diagnosis and treatment. Based on a large amount of annotated data, deep learning approaches have been widely used in COVID-19 medical image analysis. However, the number of medical image samples is generally huge, and it is challenging to obtain enough annotated medical images for training a deep CNN model. METHODS: To address these challenges, we propose a novel self-supervised deep learning method for automated segmentation of COVID-19 infection lesions and assessing the severity of infection, which can reduce the dependence on the annotation of the training samples. In the proposed method, first, many unlabeled data are used to pre-train an encoder-decoder model to learn rotation-dependent and rotation-invariant features. Then, a small amount of labeled data is used to fine-tune the pre-trained encoder-decoder for COVID-19 severity classification and lesion segmentation. RESULTS: The proposed methods were tested on two public COVID-19 CT datasets and one self-built dataset. Accuracy, precision, recall, and F1-score were used to measure classification performance and Dice coefficient was used to measure segmentation performance. For COVID-19 severity classification, the proposed method outperformed other unsupervised feature learning methods by about 7.16% in accuracy. For segmentation, when the amount of labeled data was 100%, the Dice value of the proposed method was 5.58% higher than that of U-Net.; in 70% of the cases, our method was 8.02% higher than U-Net; in 30% of the cases, our method was 11.88% higher than U-Net; and in 10% of the cases, our method was 16.88% higher than U-Net. CONCLUSIONS: The proposed method provides better classification and segmentation performance under limited labeled data than other methods.

Effectiveness and mechanism of a 4-week online self-help mindfulness intervention among individuals with emotional distress during COVID-19 in China.

BACKGROUND: Many people suffered from emotional distress especially during the COVID-19 pandemic. In order to alleviate emotional distress, more accessible psychological intervention programs, such as online intervention programs, are needed. The study aimed to investigate the efficacy and the potential mechanism of a 4-week, online, self-help mindfulness-based intervention to manage emotional distress during the COVID-19 pandemic between February 3 and May 20, 2020. METHODS: A total of 302 individuals with high emotional distress completed a self-help mindfulness course, which lasted 30-60 min per day for 28 consecutive days. Participants who registered in the program later were included in the analyses as the control group (n = 315). Levels of mindfulness, perceived stress, emotional distress, anxiety and depression were assessed at baseline(T1), week 1(T2), week 2(T3), week 3(T4) and week 4(T5). RESULTS: Significant Group by Time interaction effects were found on mindfulness, perceived stress, emotional distress, anxiety and depression (p < 0.001). Compared to the control group, the intervention group had a greater increase in changes of all outcome variables (p < 0.001). Random intercept cross-lagged analyses showed that compared with control group, mindfulness at T2 and T4 negatively predicted stress at T3 and T5, and mindfulness at T2 and T4 negatively predicted depression at T3 and T5 while depression at T3 predicted mindfulness at T4 in the mindfulness group. CONCLUSIONS: The results suggest that a 4-week self-help online mindfulness intervention improved mindfulness and reduced stress, emotional distress, anxiety and depression symptoms. Compared to the control group, changes in mindfulness preceded changes in stress, and mindfulness and depression reciprocally influenced each other during the intervention. Trial registration Chinese Clinical Trial Registry: ChiCTR2000034539. Registered 9 July 2020-Retrospectively registered, http://www.chictr.org.cn/edit.aspx?pid=55721&htm=4 .

Transmission of COVID-19 from community to healthcare agencies and back to community: a retrospective study of data from Wuhan, China.

BACKGROUND: The early spatiotemporal transmission of COVID-19 remains unclear. The community to healthcare agencies and back to community (CHC) model was tested in our study to simulate the early phase of COVID-19 transmission in Wuhan, China. METHODS: We conducted a retrospective study. COVID-19 case series reported to the Municipal Notifiable Disease Report System of Wuhan from December 2019 to March 2020 from 17 communities were collected. Cases from healthcare workers (HW) and from community members (CM) were distinguished by documented occupations. Overall spatial and temporal relationships between HW and CM COVID-19 cases were visualised. The CHC model was then simulated. The turning point separating phase 1 and phase 2 was determined using a quadratic model. For phases 1 and 2, linear regression was used to quantify the relationship between HW and CM COVID-19 cases. RESULTS: The spatial and temporal distributions of COVID-19 cases between HWs and CMs were closely correlated. The turning point was 36.85±18.37 (range 15-70). The linear model fitted well for phase 1 (mean R2=0.98) and phase 2 (mean R2=0.93). In phase 1, the estimated [Formula: see text]s were positive (from 18.03 to 94.99), with smaller [Formula: see text]s (from 2.98 to 15.14); in phase 2, the estimated [Formula: see text]s were negative (from -4.22 to -81.87), with larger [Formula: see text]s (from 5.37 to 78.12). CONCLUSION: Transmission of COVID-19 from the community to healthcare agencies and back to the community was confirmed in Wuhan. Prevention and control measures for COVID-19 in hospitals and among HWs are crucial and warrant further attention.

Research on the Linkage Between the US and China Stock Markets in the Context of COVID-19 Based on the EMD Model

Using the COVID-19 and the Sino-US trade war as the background, the data of the stock markets in China and the US from March 1, 2017 to September 11, 2020 are divided into 3 phases, and the high-frequency return series are extracted by empirical mode decomposition algorithm, excluding the interference of the medium-frequency data and low-frequency data. The DCC-GARCH model is used to analyze the China-US stock market linkage in the 3 phases, and the results show that: both the China-US trade war and the COVID-19 have a significant impact on the China-US stock market linkage. The Sino US trade war makes the linkage of Sino US stock market decline in the short term, while The COVID-19 made the relationship between China and the United States present an inverted “U” shape of first rising and then falling.

Comparative study of hospitalized children with acute respiratory distress syndrome caused by SARS-CoV-2 and influenza virus.

BACKGROUND: Since the outbreak of coronavirus disease 2019 in December 2019, more than 8 million cases have occurred worldwide as of June 16, 2020. However, it is important to distinguish COVID-19 from other respiratory infectious diseases, such as influenza. Here, we comparatively described the clinical characteristics of children with COVID-19 and paediatric patients with influenza. METHODS: In this retrospective, single-centre study, we reviewed the electronic medical records of 585 paediatric patients with COVID-19 or influenza in Wuhan Children's Hospital, China. Clinical and epidemiological characteristics, laboratory findings, and clinical outcomes were comparatively analysed. RESULTS: The median ages were 6.96 years (IQR, 2-10.81) for children with confirmed COVID-19, 2.67 years (IQR, 1.03-15.25) for those with influenza A and 3.67 years (IQR, 1.62-5.54) for those with influenza B. Fever was a symptom in 84 (34.7%) COVID-19 cases, 132 (70.21%) influenza A cases and 111 (74.50%) influenza B cases. The median length of stay (LOS) was 11 (8-15) days for paediatric COVID-19 patients, 4 (3-6) days for influenza A patients and 5 (3-6) days for influenza B patients. Twenty-six (13.98%) influenza A patients and 18 (12.59%) influenza B patients presented with decreased white blood cell counts, while 13 (5.33%) COVID-19 patients presented with decreased white blood cell counts. Eight (3.28%) COVID-19 patients, 23 (12.71%) influenza A patients and 21 (14.79%) influenza B patients experienced lymphocytopenia. Acute cardiac injury occurred in 18 (7.29%) COVID-19 patients, while 37 (19.68%) influenza A and 27 (18.12%) influenza B patients had acute cardiac injury. CONCLUSION: In this study, the illnesses of children with COVID-19 were demonstrated to be less severe than those of paediatric patients with influenza, and COVID-19 patients had milder illness and fewer complications.

Examining Public Concerns and Attitudes toward Unfair Events Involving Elderly Travelers during the COVID-19 Pandemic Using Weibo Data.

The Chinese government has launched a digital health code system to detect people potentially exposed to the coronavirus 2019 (COVID-19) disease and to curb its spread. Citizens are required to show the health code on their smartphones when using public transport. However, many seniors are not allowed to use public transport due to their difficulties in obtaining health codes, leading to widespread debates about these unfair events. Traditionally, public perceptions and attitudes toward such unfair events are investigated using analytical methods based on interviews or questionnaires. This study crawled seven-month messages from Sina Weibo, the Chinese version of Twitter, and developed a hybrid approach integrating term-frequency-inverse-document-frequency, latent Dirichlet allocation, and sentiment classification. Results indicate that a rumor about the unfair treatment of elderly travelers triggered public concerns. Primary subjects of concern were the status quo of elderly travelers, the provision of transport services, and unfair event descriptions. Following the government's responses, people still had negative attitudes toward transport services, while they became more positive about the status quo of elderly travelers. These findings will guide government authorities to explore new forms of automated social control and to improve transport policies in terms of equity and fairness in future pandemics.

Differentiation between COVID‐19 and bacterial pneumonia using radiomics of chest computed tomography and clinical features

To develop and validate an effective model for distinguishing COVID‐19 from bacterial pneumonia. In the training group and internal validation group, all patients were randomly divided into a training group (n = 245) and a validation group (n = 105). The whole lung lesion on chest computed tomography (CT) was drawn as the region of interest (ROI) for each patient. Both feature selection and model construction were first performed in the training set and then further tested in the validation set with the same thresholds. Additional tests were conducted on an external multicentre cohort with 105 subjects. The diagnostic model of LightGBM showed the best performance, achieving a sensitivity of 0.941, specificity of 0.981, accuracy of 0.962 on the validation dataset. In this study, we established a differential model to distinguish between COVID‐19 and bacterial pneumonia based on chest CT radiomics and clinical indexes.

Lessons Learned Comparing Immune System Alterations of Bacterial Sepsis and SARS-CoV-2 Sepsis.

Background: Bacterial sepsis has been used as a prototype to understand the pathogenesis of severe coronavirus disease 2019 (COVID-19). In addition, some management programs for critically ill COVID-19 patients are also based on experience with bacterial sepsis. However, some differences may exist between these two types of sepsis. Methods: This retrospective study investigated whether there are differences in the immune system status of these two types of sepsis. A total of 64 bacterial sepsis patients and 43 patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sepsis were included in this study. Demographic data were obtained from medical records. Laboratory results within 24 h after the diagnosis of sepsis were provided by the clinical laboratory. Results: The results of blood routine (neutrophil, lymphocyte, and monocyte counts), infection biomarkers (C-reactive protein, ferritin, and procalcitonin levels), lymphocyte subset counts (total T lymphocyte, CD4+ T cell, CD8+ T cell, B cell, and NK cell counts), and lymphocyte subset functions (the proportions of PMA/ionomycin-stimulated IFN-γ positive cells in CD4+, CD8+ T cells, and NK cells) were similar in bacterial sepsis patients and SARS-CoV-2 sepsis patients. Cytokine storm was milder, and immunoglobulin and complement protein levels were higher in SARS-CoV-2 sepsis patients. Conclusions: There are both similarities and differences in the immune system status of bacterial sepsis and SARS-CoV-2 sepsis. Our findings do not support blocking the cytokine storm or supplementing immunoglobulins in SARS-CoV-2 sepsis, at least in the early stages of the disease. Treatments for overactivation of the complement system and lymphocyte depletion may be worth exploring further.

Clinical and Epidemiological Features of 46 Children <1 Year Old With Coronavirus Disease 2019 in Wuhan, China: A Descriptive Study.

The number of coronavirus disease 2019 (COVID-19) cases has exceeded 10 million. However, little is known about the epidemiology and clinical characteristics of COVID-19 infants. We collected medical information of 46 confirmed patients (<1 year old) and retrospectively analyzed epidemiological history, clinical symptoms, and laboratory test results. The median age was 5 (interquartile range, 2-7) months. Sixteen cases had fever and 27 cases had cough. Moderate disease was present in 40 cases and cardiac injury occurred in 38 cases, following by liver dysfunction in 20 cases and lymphocytosis in no cases. Of all infant patients, 2 received invasive mechanical ventilation and 1 died with multiple organ dysfunction syndrome.

Light and corona: guided-wave readout for coronavirus spike protein-host-receptor binding.

We show that waveguide sensors can enable a quantitative characterization of coronavirus spike glycoprotein-host-receptor binding-the process whereby coronaviruses enter human cells, causing disease. We demonstrate that such sensors can help quantify and eventually understand kinetic and thermodynamic properties of viruses that control their affinity to targeted cells, which is known to significantly vary in the course of virus evolution, e.g., from SARS-CoV to SARS-CoV-2, making the development of virus-specific drugs and vaccine difficult. With the binding rate constants and thermodynamic parameters as suggested by the latest SARS-CoV-2 research, optical sensors of SARS-CoV-2 spike protein-receptor binding may be within sight.

Epidemiology of COVID-19 in older persons, Wuhan, China.

BACKGROUND: the epidemiological characteristics of older patients with COVID-19 was far from clear. OBJECTIVE: to explore the epidemiology of older patients with COVID-19 in Wuhan, China. DESIGN: a retrospective cross-sectional study. SETTING: a population-based study. SUBJECTS: the resident older patients (>65 years) diagnosed with COVID-19. METHODS: city-wide case series reported to Wuhan Center for Disease Control and Prevention from 12 December 2019 to 17 March 2020 were included. The epidemic curves were constructed by dates of disease onset. RESULTS: 14,238 confirmed COVID-19 cases were older persons. The number of male cases were slightly less than female cases (1:1.01). The attack rate of COVID-19 in the older persons was 11.49‰ in Wuhan. There was a rapid increase of disease at the early stage of the epidemic and then a gradual and steady decrease was performed. 3,723 (26.15%) and 734 (5.16%) patients were diagnosed as severe and critical cases, respectively. The attributable crude fatality ratio of COVID-19 in the older population was 222.57/100,000, and the crude fatality ratio of COVID was 19.37%. The proportion of severe and critical cases, and fatality ratio were both higher in downtown area and increased with age. CONCLUSIONS: the older persons are sensitive to COVID-19. The proportion of severe and critical cases and fatality ratio are higher than that in children and younger adults. Strengthen the protection and control strategies for the older adults are of priorities. More detailed epidemiological and clinical information should be measured in further studies.

Characteristics of Household Transmission of COVID-19.

BACKGROUND: Since December 2019, SARS-CoV-2 has extended to most parts of China with >80 000 cases and to at least 100 countries with >60 000 international cases as of 15 March 2020. Here we used a household cohort study to determine the features of household transmission of COVID-19. METHODS: A total of 105 index patients and 392 household contacts were enrolled. Both index patients and household members were tested by SARS-CoV-2 RT-PCR. Information on all recruited individuals was extracted from medical records and confirmed or supplemented by telephone interviews. The baseline characteristics of index cases and contact patients were described. Secondary attack rates of SARS-CoV-2 to contact members were computed and the risk factors for transmission within the household were estimated. RESULTS: Secondary transmission of SARS-CoV-2 developed in 64 of 392 household contacts (16.3%). The secondary attack rate to children was 4% compared with 17.1% for adults. The secondary attack rate to the contacts within the households with index patients quarantined by themselves since onset of symptoms was 0% compared with 16.9% for contacts without quarantined index patients. The secondary attack rate to contacts who were spouses of index cases was 27.8% compared with 17.3% for other adult members in the households. CONCLUSIONS: The secondary attack rate of SARS-CoV-2 in household is 16.3%. Age of household contacts and spousal relationship to the index case are risk factors for transmission of SARS-CoV-2 within a household. Quarantine of index patients at home since onset of symptoms is useful to prevent the transmission of SARS-Co-2 within a household.