Network characteristics and stock liquidity:Evidence from the UK

This article examines the effect of the Engle-Granger (E-G) price spillover network characteristics on firm's stock liquidity with a longitudinal dataset of FTSE 350 from 2006 to 2021. We find that the subprime crisis, European debt sovereign crisis, British Brexit and COVID-19 caused dramatic network structure change. We also find that firms with higher centrality are likely to suffer from more or greater price shocks leading to lower stock liquidity. Finally, the robust of our results has also been identified, and a general framework for network characteristics and stock liquidity has been established to some extent.

Guild-level microbiome signature associated with COVID-19 severity and prognosis (preprint)

COVID-19 severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples collected from 300 in-hospital COVID-19 patients at time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), Redundancy Analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Random Forest model based on these 33 HQMAGs classified patients from different severity groups (average AUC = 0.79). Co-abundance network analysis found that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Random Forest regression showed that these 33 HQMAGs at admission had the capacity to predict 8 clinical parameters, which are predictors for COVID-19 prognosis, at Day 7 in hospital. Moreover, the dominance of Guild 1 over Guild 2 at admission predicted the death/discharge outcome of the critical patients (AUC = 0.92). Random Forest models based on these 33 HQMAGs classified patients with different COVID-19 symptom severity, and differentiated COVID-19 patients from healthy subjects, non-COVID-19, and pneumonia controls in three independent datasets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission.

Rare Variants in Inborn Errors of Immunity Genes Associated with Covid-19 Severity (preprint)

Covid-19 is a contagious disease caused by SARS-CoV-2, a novel severe acute respiratory syndrome coronavirus. Common variants and networks underlying host genetic mechanisms have been extensively studied to identify disease-associated genetic factors. However, there are few studies about the rare variants, typically inborn errors of immunity, in understanding the host genetics behind Covid-19 infection, especially in the Chinese population. To fill this gap, we investigate likely-deleterious missense and high-confidence predicted loss-of-function variants by (a) performing gene- and pathway-level association analyses, (b) examining known genes involved in type I interferon signaling and others previously reported in Covid-19 disease, and (c) identifying candidate genes with accumulating mutations and their potential protein-protein interactions with known genes. Based on our analyses, several putative genes and pathways are uncovered and worth further investigation, for example, genes IL12RB1, TBK1, and TLR3, and pathways Tuberculosis (hsa:05152), Primary Immunodeficiency (hsa:05340), and Influenza A (hsa:05164). These regions generally play an essential role in regulating antiviral innate immunity responses to foreign pathogens and in responding to many inflammatory diseases. We believe that to some extent, as an acute inflammatory disease, Covid-19 is also affected by these inborn errors of immunity. We hope that the identification of these rare genetic factors will provide new insights into the genetic architecture of Covid-19.

Quantum Deep Learning for Mutant COVID-19 Strain Prediction (preprint)

New COVID-19 epidemic strains like Delta and Omicron with increased transmissibility and pathogenicity emerge and spread across the whole world rapidly while causing high mortality during the pandemic period. Early prediction of possible variants (especially spike protein) of COVID-19 epidemic strains based on available mutated SARS-CoV-2 RNA sequences may lead to early prevention and treatment. Here, combining the advantage of quantum and quantum-inspired algorithms with the wide application of deep learning, we propose a development tool named DeepQuantum, and use this software to realize the goal of predicting spike protein variation structure of COVID-19 epidemic strains. In addition, this hybrid quantum-classical model for the first time achieves quantum-inspired blur convolution similar to classical depthwise convolution and also successfully applies quantum progressive training with quantum circuits, both of which guarantee that our model is the quantum counterpart of the famous style-based GAN. The results state that the fidelities of random generating spike protein variation structure are always beyond 96% for Delta, 94% for Omicron. The training loss curve is more stable and converges better with multiple loss functions compared with the corresponding classical algorithm. At last, evidences that quantum-inspired algorithms promote the classical deep learning and hybrid models effectively predict the mutant strains are strong.

Comparative analysis of single cell lung atlas of bat, cat, tiger and pangolin (preprint)

Horseshoe bats (Rhinolophus sinicus) might help maintain coronaviruses severely affecting human health, such as SARS-CoV and SARS-CoV-2. It has long been suggested that bats may be more tolerant of viral infection than other mammals due to their unique immune system, but the exact mechanism remains to be fully explored. During the COVID-19 pandemic, multiple animal species were diseased by SARS-CoV-2 infection, especially in the respiratory system. Herein, single-cell transcriptomic data of the lungs of a horseshoe bat, a cat, a tiger, and a pangolin were generated. The receptor distribution of twenty-eight respiratory viruses belonging to fourteen viral families were characterized for the four species. Comparison on the immune-related transcripts further revealed limited cytokine activations in bats, which might explain the reason why bats experienced only mild diseases or even no symptoms upon virus infection. Our findings might increase our understanding of the immune background of horseshoe bats and their insensitivity to virus infections.

Low Humoral Immune Response and Ineffective Clearance of SARS-Cov-2 in a COVID-19 Patient With CLL During a 69-Day Follow-Up

Background: A recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), which began in Wuhan, China, with a high level of human-to-human transmission has been reported. There are limited data available on Coronavirus Disease 2019 (COVID-19) patients with hematological malignancies with more than 60 days of follow-up. This study describes the clinical characteristics, including multiple recurrences of COVID-19, in a patient with chronic lymphocytic leukemia (CLL) during 69 days of follow-up. Case Presentation: A 72-year-old female was admitted to hospital isolation after being infected with COVID-19 as part of a family cluster on January 30, 2020. Apart from SARS-Cov-2 virus infection, laboratory results revealed lymphocytosis of uncertain etiology and abnormal distribution of T lymphocytes. On blood smears, small blue lymphocytes with scant cytoplasm were observed, and the presence of high levels of circulating clonal B cells was also demonstrated by flow cytometry. The patient was diagnosed with COVID-19 and CLL. Among her family members, she had the highest viral loads and the fastest progression on lung injury and developed severe pneumonia. Serological results showed she had both 2019-nCoV-specific IgM and IgG antibodies;however, only IgG antibodies were detected in her husband's plasma. Results: A combination regimen of antiviral therapy and high-dose intravenous immunoglobulin (IVIG) in the early stage seemed to be effective for treating CLL and SARS-Cov-2 infection. Because of the low humoral immune response, the CLL patient could not effectively clear the SARS-Cov-2 infection and suffered from recurrence twice during the 69-day follow-up. Conclusion: In CLL, a neoplastic antigen-specific B-cell clone proliferates, and the progeny cells accumulate and outgrow other B cells, leading to immune deficiency. Considering the low humoral immune response and ineffective clearance of SARS-Cov-2 in CLL patients, the follow-up and home quarantine period should be extended. We need further studies to clarify suspending or continuing CLL therapy during COVID infection. For those patients who are prone to progression to severe disease, administering humoral immunity therapies can help to prevent disease progression and quickly meet the cure criteria.

Relationship Between Depressive Symptoms, Job Burnout And Career Choice Regret of Postgraduates In Stomatology (preprint)

Background: In China, the shortage of doctors leads to an increase in workload. Especially after the new crown epidemic（COVID-19）, excessive workload may lead to both physical and mental fatigue of doctors. Students' choices and opinions about the doctoral （health care）industry are particularly important. However, we don't know much about the work and living conditions of postgraduates in Stomatology. The purpose of this research is to investigate the depressive symptoms, job burnout and job satisfaction of individual dental graduate students and their personal professional characteristics after the outbreak of coronavirus disease-2019. Methods: The study directed to the correlations between depressive symptoms, burnout and career choice regret and their factors. The questionnaire covers demographic information, Maslach Burnout Inventory, and added programs to evaluate career choice regret. Results: There are 580 dental graduate students who will return to complete the questionnaire in 2021. After excluding partial questionnaires, the data of 558 participants were analyzed. In total, 44.1% of the participants had symptoms of depression. 41.0% of the participants experienced symptoms of burnout and 41.6% of the participants had regrets about their career choices. Binary logistic regression analysis showed that the average daily sleep time was associated to depressive symptoms (P<0.05). At the same time, job burnout (OR = 5.38, 95% CI 3.67–7.88) and career choice regret (OR = 2.07, 95% CI 1.41–3.05) were risk factors for depressive symptoms. There was a relationship between job burnout, average study time per week and average daily sleep time(all P<0.05). Depressive symptoms were the biggest risk factor for burnout (OR = 5.28, 95% CI3.62-7.69). There was a relationship between career choice regret, postgraduate entrance examination score and average daily sleep time(all P<0.05). Job burnout (OR = 1.82, 95% CI1.24-2.66) and depressive symptoms (OR = 2.15, 95% CI1.48-3.14) were both risk factors for career choice regret. Conclusions: Depressive symptoms, job burnout, and career choice regrets are common in postgraduates majoring in Stomatology . An in-depth understanding of relevant factors is essential to determine the reduction and prevention of burnout and career choice regrets in this group.

Plasma cell-free DNA promise disease monitoring and tissue injury assessment of COVID-19 (preprint)

COVID-19 is a huge threat to global health. Due to the lack of definitive etiological therapeutics currently, effective disease monitoring is of high clinical value for better healthcare and management of the large number of COVID-19 patients. In this study, we recruited 37 COVID-19 patients, collected 176 blood samples upon diagnosis and during treatment, and analyzed cell-free DNA (cfDNA) in these samples. We report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA characteristics reflect patient-specific physiological conditions during treatment. Further analysis on tissue origin tracing of cfDNA reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, we demonstrate the translational merit of cfDNA as valuable analyte for effective disease monitoring, as well as tissue injury assessment in COVID-19 patients.

A Chinese host genetic study discovered type I interferons and causality of cholesterol levels and WBC counts on COVID-19 severity (preprint)

As of early May 2021, the ongoing pandemic COVID-19 has caused over 160 million of infections and over 3 million deaths worldwide. Many risk factors, such as age, gender, and comorbidities, have been studied to explain the variable symptoms of infected patients. However, these effects may not fully account for the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory features. Based on these findings, we performed Mendelian randomization (MR) analysis to investigate the causality of laboratory traits on disease severity. From the MR study, we identified two causal traits, cholesterol levels and WBC counts. The functional gene related to cholesterol levels is ApoE and people with particular ApoE genotype are more likely to have higher cholesterol levels, facilitating the process that SARS-CoV-2 binds on its receptor ACE2 and aggravating COVID-19 disease. The functional gene related to WBC counts is MHC system that plays a central role in the immune system. The host immune response to the SARS-CoV-2 infection greatly affects the patients severity status and clinical outcome. Additionally, our gene-based and GSEA analysis revealed interferon pathways, including type I interferon receptor binding, regulation of IFNA signaling, and SARS coronavirus and innate immunity. We hope that our work will make a contribution in studying the genetic mechanisms of disease illness and serve as useful reference for the clinical diagnosis and treatment of COVID-19.

Genomic epidemiology of SARS-CoV-2 in the United Arab Emirates reveals novel virus mutation, patterns of co-infection and tissue specific host responses (preprint)

Background: The United Arab Emirates is a major business hub with substantial amount of international travel. Like many other countries, it was greatly affected by the COVID-19 pandemic since late January 2020, with recurring waves of infection. This study aimed at combining genomic and epidemiological data to unravel the source of SARS-CoV-2 introduction, transmission and evolution in the country. Methods: We performed meta-transcriptomic sequencing of 1,067 nasopharyngeal swab samples collected from qRT-PCR positive COVID-19 patients in Abu Dhabi, UAE, between May 9th and June 29th 2020. We investigated the genetic diversity and transmission dynamics of the viral population and analyzed the infection and transmission potential of novel genomic clusters. Within-host SARS-CoV-2 genetic variation was analyzed to determine the occurrence and prevalence of multiple infections. Finally, we evaluated innate host responses during the prolonged period of local infection. Results: All globally known SARS-CoV-2 clades were identified within the UAE sequenced strains, with a higher occurrence of European and East Asian clades. We defined 5 subclades based on 11 unique genetic variants within the UAE strains, which were associated with no significantly different viral loads. Multiple infection of different SARS-CoV-2 strains was observed for at least 5% of the patients. We also discovered an enrichment of cytosine-to-uracil mutation among the viral population collected from the nasopharynx, that is different from the adenosine-to-inosine change previously observed in the bronchoalveolar lavage fluid samples. This observation is accompanied with an upregulation of APOBEC4, an under-studied putative cytidine-uridine editing enzyme in the infected nasopharynx. Conclusions: The genomic epidemiological and molecular biological knowledge obtained in the study provides new insights for the SARS-CoV-2 evolution and transmission. We highlight the importance of sustained surveillance of the virus mutation using genomic sequencing as a public health strategy. Keywords: SARS-CoV-2, meta-transcriptomic sequencing, novel mutations and subclades, co-infection, cyosine depletion, host RNA editing

Genomic Epidemiology of SARS-CoV-2 in the United Arab Emirates Reveals Novel Insights into the Virus Mutation, Co-Infection and Host-Dependent RNA Editing (preprint)

Background: The United Arab Emirates is a major business hub with substantial amount of international travel. Like many other countries, it was greatly affected by the COVID-19 pandemic since late January 2020, with recurring waves of infection. This study aimed at combining genomic and epidemiological data to unravel the source of SARS-CoV-2 introduction, transmission and evolution in the country.Methods: We performed meta-transcriptomic sequencing of 1,067 nasopharyngeal swab samples collected from qRT-PCR positive COVID-19 patients in Abu Dhabi, UAE, between May 9th and June 29th 2020. We investigated the genetic diversity and transmission dynamics of the viral population and analyzed the infection and transmission potential of novel genomic clusters. Within-host SARS-CoV-2 genetic variation was analyzed to determine the occurrence and prevalence of multiple infections. Finally, we evaluated innate host responses during the prolonged period of local infection.Findings: All globally known SARS-CoV-2 clades were identified within the UAE sequenced strains, with a higher occurrence of European and East Asian clades. We defined 5 subclades based on 11 unique genetic variants within the UAE strains, which were associated with higher viral loads (p<0.001). Multiple infection of different SARS-CoV-2 strains was observed for at least 5% of the patients. We also observed a host-defense mechanism via RNA editing, likely mediated by APOBEC3 rather than ADAR in nasopharyngeal samples.Interpretation: The SARS-CoV-2 epidemic in the UAE was founded by international importation followed by local transmission, leading to prevalent multiple infection and large subclade descendances. While RNA editing mechanisms mutate the viral population, newly arisen genetic variation can contribute to a heavier viral burden. Meta-transcriptomic sequencing can help to determine the transmission patterns of SARS-CoV-2.Funding: Department of Health of Abu Dhabi, UAE and National Natural Science Foundation of China.Declaration of Interests: None to declareEthics Approval Statement: The study was approved by the Abu Dhabi COVID19 Research IRB Committee (approval number DOH/CVDC/2020/1945).

The Trans-omics Landscape of COVID-19 (preprint)

The outbreak of coronavirus disease 2019 (COVID-19) has been causing a global health emergency. Although previous studies investigated COVID-19 at different omics levels, the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here, we presented a trans-omics landscape for COVID-19 based on integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles from blood samples of 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Notably, we found neutrophils heterogeneity existed between asymptomatic and critically ill patients. Expression discordance of inflammatory cytokines at mRNA and protein levels in asymptomatic patients could possibly be explained by post-transcriptional regulation by RNA binding proteins (RBPs) and microRNAs. Neutrophils over-activation, induced arginine depletion, and tryptophan metabolites accumulation contributed to T/NK cell dysfunction in critical patients. Anti-virus interferons were gradually suppressed along with disease severity. Overall, our study systematically revealed multi-omics characteristics of COVID-19, and the data we generated could hopefully help illuminate COVID-19 pathogenesis and provide valuable clues about potential therapeutic strategies for COVID-19.

The Trans-omics Landscape of COVID-19 (preprint)

System-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive molecular profiles of blood samples from 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Amongst the major findings, asymptomatic patients were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation of inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these cytokine mRNAs could be effectively destabilized hence preserving normal cytokine levels. In contrast, in critically ill patients, cytokine storm due to RBPs inhibition and tryptophan metabolites accumulation contributed to T/NK cell dysfunction. A machine-learning model was constructed which accurately stratified the COVID-19 severities based on their multi-omics features. Overall, our analysis provides insights into COVID-19 pathogenesis and identifies targets for intervening in treatment.

Population Bottlenecks and Intra-host Evolution during Human-to-Human Transmission of SARS-CoV-2Population Bottlenecks and Intra-host Evolution during Human-to-Human Transmission of SARS-CoV-2 (preprint)

The emergence of the novel human coronavirus, SARS-CoV-2, causes a global COVID-19 (coronavirus disease 2019) pandemic. Here, we have characterized and compared viral populations of SARS-CoV-2 among COVID-19 patients within and across households. Our work showed an active viral replication activity in the human respiratory tract and the co-existence of genetically distinct viruses within the same host. The inter-host comparison among viral populations further revealed a narrow transmission bottleneck between patients from the same households, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions. Author summaryIn this study, we compared SARS-CoV-2 populations of 13 Chinese COVID-19 patients. Those viral populations contained a considerable proportion of viral sub-genomic messenger RNAs (sgmRNA), reflecting an active viral replication activity in the respiratory tract tissues. The comparison of 66 identified intra-host variants further showed a low viral genetic distance between intra-household patients and a narrow transmission bottleneck size. Despite the co-existence of genetically distinct viruses within the same host, most intra-host minor variants were not shared between transmission pairs, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions. Furthermore, the narrow bottleneck and active viral activity in the respiratory tract show that the passage of a small number of virions can cause infection. Our data have therefore delivered a key genomic resource for the SARS-CoV-2 transmission research and enhanced our understanding of the evolutionary dynamics of SARS-CoV-2.

Single-cell screening of SARS-CoV-2 target cells in pets, livestock, poultry and wildlife (preprint)

A few animals have been suspected to be intermediate hosts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, a large-scale single-cell screening of SARS-CoV-2 target cells on a wide variety of animals is missing. Here, we constructed the single-cell atlas for 11 representative species in pets, livestock, poultry, and wildlife. Notably, the proportion of SARS-CoV-2 target cells in cat was found considerably higher than other species we investigated and SARS-CoV-2 target cells were detected in multiple cell types of domestic pig, implying the necessity to carefully evaluate the risk of cats during the current COVID-19 pandemic and keep pigs under surveillance for the possibility of becoming intermediate hosts in future coronavirus outbreak. Furthermore, we screened the expression patterns of receptors for 144 viruses, resulting in a comprehensive atlas of virus target cells. Taken together, our work provides a novel and fundamental strategy to screen virus target cells and susceptible species, based on single-cell transcriptomes we generated for domesticated animals and wildlife, which could function as a valuable resource for controlling current pandemics and serve as an early warning system for coping with future infectious disease threats.

Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States (preprint)

Despite social distancing and shelter-in-place policies, COVID-19 continues to spread in the United States. A lack of timely information about factors influencing COVID-19 spread and testing has hampered agile responses to the pandemic. We developed How We Feel, an extensible web and mobile application that aggregates self-reported survey responses, to fill gaps in the collection of COVID-19-related data. How We Feel collects longitudinal and geographically localized information on users' health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self- reported surveys can be used to build predictive models of COVID-19 test results, which may aid in identification of likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, as well as for household and community exposure, occupation, and demographics being strong risk factors for COVID-19. We further reveal factors for which users have been SARS-CoV-2 PCR tested, as well as the temporal dynamics of self- reported symptoms and self-isolation behavior in positive and negative users. These results highlight the utility of collecting a diverse set of symptomatic, demographic, and behavioral self- reported data to fight the COVID-19 pandemic.

Initial Study of Human Genetic Contribution to COVID-19 Severity and Susceptibility (preprint)

The COVID-19 pandemic has accounted for more than five million infections and hundreds of thousand deaths worldwide in the past six months. The patients demonstrate a great diversity in clinical and laboratory manifestations and disease severity. Nonetheless, little is known about the host genetic contribution to the observed inter-individual phenotypic variability. Here, we report the first host genetic study in China by deeply sequencing and analyzing 332 COVID-19 patients categorized by varying levels of severity from the Shenzhen Third Peoples Hospital. Upon a total of 22.2 million genetic variants, we conducted both single-variant and gene-based association tests among five severity groups including asymptomatic, mild, moderate, severe and critical ill patients after the correction of potential confounding factors. The most significant gene locus associated with severity is located in TMEM189-UBE2V1 involved in the IL-1 signaling pathway. The p.Val197Met missense variant that affects the stability of the TMPRSS2 protein displays a decreasing allele frequency among the severe patients compared to the mild and the general population. We also identified that the HLA-A*11:01, B*51:01 and C*14:02 alleles significantly predispose the worst outcome of the patients. This initial study of Chinese patients provides a comprehensive view of the genetic difference among the COVID-19 patient groups and highlighted genes and variants that may help guide targeted efforts in containing the outbreak. Limitations and advantages of the study were also reviewed to guide future international efforts on elucidating the genetic architecture of host-pathogen interaction for COVID-19 and other infectious and complex diseases.

Time-series plasma cell-free DNA analysis reveals disease severity of COVID-19 patients (preprint)

Symptoms of coronavirus disease 2019 (COVID-19) range from asymptomatic to severe pneumonia and death. Detection of individuals at high risk for critical condition is crucial for control of the disease. Herein, for the first time, we profiled and analyzed plasma cell-free DNA (cfDNA) of mild and severe COVID-19 patients. We found that in comparison between mild and severe COVID-19 patients, Interleukin-37 signaling was one of the most relevant pathways; top significantly altered genes included POTEH, FAM27C, SPATA48, which were mostly expressed in prostate and testis; adrenal glands, small intestines and liver were tissues presenting most differentially expressed genes. Our data thus revealed potential tissue involvement, provided insights into mechanism on COVID-19 progression, and highlighted utility of cfDNA as a noninvasive biomarker for disease severity inspections.

The values of coagulation function in COVID-19 patients (preprint)

ObjectiveTo investigate the blood coagulation function in COVID-19 patients, and the correlation between coagulopathy and disease severity. MethodsWe retrospectively collected 147 clinically diagnosed COVID-19 patients at Wuhan Leishenshan Hospital of Hubei, China. We analyzed the coagulation function in COVID-19 patients through the data including thrombin-antithrombin complex (TAT), 2-plasmininhibitor-plasmin Complex (PIC), thrombomodulin (TM), t-PA/PAI-1 Complex (t-PAIC), prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (APTT), fibrinogen (FIB), thrombin time (TT), D-Dimer (DD), and platelet (PLT). ResultThe levels of TAT, PIC, TM, t-PAIC, PT, INR, FIB, and DD in COVID-19 patients were higher than health controls (p<0.05), and also higher in the patients with thrombotic disease than without thrombotic disease (p<0.05). Whats more, the patients with thrombotic disease had a higher case-fatality (p<0.05). TAT, PIC, TM, t-PAIC, PT, INR, APTT, FIB, DD, and PLT were also found correlated with disease severity. Meanwhile, we found that there were significant difference in TAT, TM, t-PAIC, PT, INR, APTT, DD, and PLT in the death and survival group. Further using univariate and multivariate logistic regression analysis also found that t-PAIC and DD were independent risk factors for death in patients and are excellent predicting the mortality risk of COVID-19. ConclusionThe coagulation systems in COVID-19 patients are inordinate, and dynamic monitoring of them, might be a key in the control of COVID-19 death.