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1.
Br J Clin Pharmacol ; 88(5): 2452-2453, 2022 May.
Article in English | MEDLINE | ID: covidwho-1788831
2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313367

ABSTRACT

In December 2019, a novel coronavirus was found in a seafood wholesale market in Wuhan, China. WHO officially named this coronavirus as COVID-19. Since the first patient was hospitalized on December 12, 2019, China has reported a total of 78,824 confirmed CONID-19 cases and 2,788 deaths as of February 28, 2020. Wuhan's cumulative confirmed cases and deaths accounted for 61.1% and 76.5% of the whole China mainland , making it the priority center for epidemic prevention and control. Meanwhile, 51 countries and regions outside China have reported 4,879 confirmed cases and 79 deaths as of February 28, 2020. COVID-19 epidemic does great harm to people's daily life and country's economic development. This paper adopts three kinds of mathematical models, i.e., Logistic model, Bertalanffy model and Gompertz model. The epidemic trends of SARS were first fitted and analyzed in order to prove the validity of the existing mathematical models. The results were then used to fit and analyze the situation of COVID-19. The prediction results of three different mathematical models are different for different parameters and in different regions. In general, the fitting effect of Logistic model may be the best among the three models studied in this paper, while the fitting effect of Gompertz model may be better than Bertalanffy model. According to the current trend, based on the three models, the total number of people expected to be infected is 49852-57447 in Wuhan,12972-13405 in non-Hubei areas and 80261-85140 in China respectively. The total death toll is 2502-5108 in Wuhan, 107-125 in Non-Hubei areas and 3150-6286 in China respetively. COVID-19 will be over p robably in late-April, 2020 in Wuhan and before late-March, 2020 in other areas respectively.

3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312202

ABSTRACT

Background: Previous studies have documented the clinical characteristics of patients with Coronavirus disease 2019(COVID-19) and presented evidence of person-to-person transmission. Limited data are available for patients with asymptomatic infections. Some asymptomatic carriers, whom we characterize as “exposers” or “infectors”, may be responsible for family clustering of COVID-19. Methods: : A questionnaire survey and follow-up survey based on media reports were used to assess familial clustering of SARS-CoV-2 infection induced by asymptomatic exposers/infectors. Individual data were collected for all members of each tracked family. A transmission map was then drawn for each family. Results: : Our study of 5 families indicated that individuals with no obvious symptoms of COVID-19, regardless of the PCR results, transmitted the virus to other family members who were community contained at home and had no contact with other infected individuals. There was one death case in Family No.3. Conclusion: Asymptomatic exposers/infectors of SARS-CoV-2 were all middle-aged (average age: 44.4 ± 14.9 years) who had no symptoms but had the ability to disseminate the virus. Medical staff participating in treatment of COVID-19 cases all had a high risk of infection, they should be quarantined so as to protect their families. The morbidity and mortality of Case 3.2 remind us that although these asymptomatic infected people have no symptoms, they are also infectious. It is not ruled out that the subsequent infected people are seriously ill or even die. Therefore, we should not take it lightly.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315398

ABSTRACT

Coronavirus Disease 2019 (COVID-19) is a global pandemic that poses significant health risks. The sensitivity of diagnostic tests for COVID-19 is low due to irregularities in the handling of the specimens. We propose a deep learning framework that identifies COVID-19 from medical images as an effective auxiliary testing method to improve diagnostic sensitivity. We use pseudo-coloring methods and a platform for annotating X-ray and computed tomography (CT) images to train and evaluate the convolutional neural network (CNN). The CNN achieves a performance similar to that of experts and provides high scores for multiple statistical indices, with F1 scores above 96% and specificity over 99%. Heatmaps are used to visualize the salient features extracted by the CNN. The CNN-based regression provides strong correlations between the lesion areas in the images and five clinical indicators, improving the interpretation accuracy of the classification framework. The proposed method represents a potential computer-aided diagnosis method for COVID-19 in clinical practice.

5.
Signal Transduct Target Ther ; 6(1): 428, 2021 12 17.
Article in English | MEDLINE | ID: covidwho-1585884

ABSTRACT

SARS-CoV-2 infection-induced hyper-inflammation links to the acute lung injury and COVID-19 severity. Identifying the primary mediators that initiate the uncontrolled hypercytokinemia is essential for treatments. Mast cells (MCs) are strategically located at the mucosa and beneficially or detrimentally regulate immune inflammations. In this study, we showed that SARS-CoV-2-triggered MC degranulation initiated alveolar epithelial inflammation and lung injury. SARS-CoV-2 challenge induced MC degranulation in ACE-2 humanized mice and rhesus macaques, and a rapid MC degranulation could be recapitulated with Spike-RBD binding to ACE2 in cells; MC degranulation altered various signaling pathways in alveolar epithelial cells, particularly, the induction of pro-inflammatory factors and consequential disruption of tight junctions. Importantly, the administration of clinical MC stabilizers for blocking degranulation dampened SARS-CoV-2-induced production of pro-inflammatory factors and prevented lung injury. These findings uncover a novel mechanism for SARS-CoV-2 initiating lung inflammation, and suggest an off-label use of MC stabilizer as immunomodulators for COVID-19 treatments.


Subject(s)
COVID-19/metabolism , Cell Degranulation , Lung Injury/metabolism , Mast Cells/metabolism , Pulmonary Alveoli/metabolism , SARS-CoV-2/metabolism , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/metabolism , Animals , COVID-19/genetics , Cell Line, Tumor , Female , Humans , Lung Injury/genetics , Lung Injury/virology , Macaca mulatta , Male , Mice, Inbred BALB C , Mice, Transgenic , Pulmonary Alveoli/virology , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/metabolism
6.
Sustainability ; 13(21):11667, 2021.
Article in English | MDPI | ID: covidwho-1480990

ABSTRACT

Since 2019, the novel coronavirus has spread rapidly worldwide, greatly affecting social stability and human health. Pandemic prevention has become China’s primary task in responding to the transmission of COVID-19. Risk mapping and the proposal and implementation of epidemic prevention measures emphasize many research efforts. In this study, we collected location information for confirmed COVID-19 cases in Beijing, Shenyang, Dalian, and Shijiazhuang from 5 October 2020 to 5 January 2021, and selected 15 environmental variables to construct a model that comprehensively considered the parameters affecting the outbreak and spread of COVID-19 epidemics. Annual average temperature, catering, medical facilities, and other variables were processed using ArcGIS 10.3 and classified into three groups, including natural environmental variables, positive socio-environmental variables, and benign socio-environmental variables. We modeled the epidemic risk distribution for each area using the MaxEnt model based on the case occurrence data and environmental variables in four regions, and evaluated the key environmental variables influencing the epidemic distribution. The results showed that medium-risk zones were mainly distributed in Changping and Shunyi in Beijing, while Huanggu District in Shenyang and the southern part of Jinzhou District and the eastern part of Ganjingzi District in Dalian also represented areas at moderate risk of epidemics. For Shijiazhuang, Xinle, Gaocheng and other places were key COVID-19 epidemic spread areas. The jackknife assessment results revealed that positive socio-environmental variables are the most important factors affecting the outbreak and spread of COVID-19. The average contribution rate of the seafood market was 21.12%, and this contribution reached as high as 61.3% in Shenyang. The comprehensive analysis showed that improved seafood market management, strengthened crowd control and information recording, industry-catered specifications, and well-trained employees have become urgently needed prevention strategies in different regions. The comprehensive analysis indicated that the niche model could be used to classify the epidemic risk and propose prevention and control strategies when combined with the assessment results of the jackknife test, thus providing a theoretical basis and information support for suppressing the spread of COVID-19 epidemics.

7.
J Zhejiang Univ Sci B ; 21(5): 369-377, 2020 May.
Article in English | MEDLINE | ID: covidwho-1352747

ABSTRACT

BACKGROUND: A novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first identified in Wuhan, China, has been rapidly spreading around the world. This study investigates the epidemiological and clinical characteristics of coronavirus disease 2019 (COVID-19) patients in Zhejiang Province who did or did not have a history of Wuhan exposure. METHODS: We collected data from medical records of confirmed COVID-19 patients in Zhejiang Province from Jan. 17 to Feb. 7, 2020 and analyzed epidemiological, clinical, and treatment data of those with and without recorded recent exposure in Wuhan. RESULTS: Patients in the control group were older than those in the exposure group ((48.19±16.13) years vs. (43.47±13.12) years, P<0.001), and more were over 65 years old (15.95% control vs. 5.60% exposure, P<0.001). The rate of clustered onset was also significantly higher in the control group than in the exposure group (31.39% vs. 18.66%, P<0.001). The symptom of a sore throat in patients in the exposure group was significantly higher than that in the control group (17.30% vs. 10.89%, P=0.01); however, headache in the exposure group was significantly lower than that in the control group (6.87% vs. 12.15%, P=0.015). More patients in the exposure group had a significantly lower level of lactate dehydrogenase (LDH) and aspartate aminotransferase (AST) than those in the control group. There was no significant difference in any degree of COVID-19 including mild, severe, and critical between the two groups. CONCLUSIONS: From the perspective of epidemiological and clinical characteristics, there was no significant difference between COVID-19 patients with and without Wuhan exposure history.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Adolescent , Adult , Aged , Aspartate Aminotransferases/blood , Betacoronavirus , COVID-19 , Case-Control Studies , Child , Child, Preschool , China/epidemiology , Coronavirus Infections/physiopathology , Coronavirus Infections/therapy , Female , Humans , Infant , Infant, Newborn , L-Lactate Dehydrogenase/blood , Male , Middle Aged , Pandemics , Pneumonia, Viral/physiopathology , Pneumonia, Viral/therapy , Retrospective Studies , SARS-CoV-2 , Young Adult
8.
Preprint in English | bioRxiv | ID: ppbiorxiv-392407

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing an outbreak of coronavirus disease 2019 (COVID-19), has been undergoing various mutations. The analysis of the structural and energetic effects of mutations on protein-protein interactions between the receptor binding domain (RBD) of SARS-CoV-2 and angiotensin converting enzyme 2 (ACE2) or neutralizing monoclonal antibodies will be beneficial for epidemic surveillance, diagnosis, and optimization of neutralizing agents. According to the molecular dynamics simulation, a key mutation N439K in the SARS-CoV-2 RBD region created a new salt bridge which resulted in greater electrostatic complementarity. Furthermore, the N439K-mutated RBD bound hACE2 with a higher affinity than wild-type, which may lead to more infectious. In addition, the N439K-mutated RBD was markedly resistant to the SARS-CoV-2 neutralizing antibody REGN10987, which may lead to the failure of neutralization. These findings would offer guidance on the development of neutralizing antibodies and the prevention of COVID-19.

10.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-729

ABSTRACT

Recent studies have reported that 2019 novel coronavirus disease (COVID-19) patients with lung cancer have a higher risk of severe events than patients without

12.
J Zhejiang Univ Sci B ; 21(8): 628-636, 2020.
Article in English | MEDLINE | ID: covidwho-694091

ABSTRACT

BACKGROUND: Currently, there are no drugs that have been proven to be effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Because of its broad antiviral activity, interferon (IFN) should be evaluated as a potential therapeutic agent for treatment of coronavirus disease 2019 (COVID-19), especially while COVID-19-specific therapies are still under development. METHODS: Confirmed COVID-19 patients hospitalized in the First Affiliated Hospital, School of Medicine, Zhejiang University in Hangzhou, China, from January 19 to February 19, 2020 were enrolled in a retrospective study. The patients were separated into an IFN group and a control group according to whether they received initial IFN-α2b inhalation treatment after admission. Propensity-score matching was used to balance the confounding factors. RESULTS: A total of 104 confirmed COVID-19 patients, 68 in the IFN group and 36 in the control group, were enrolled. Less hypertension (27.9% vs. 55.6%, P=0.006), dyspnea (8.8% vs. 25.0%, P=0.025), or diarrhea (4.4% vs. 19.4%, P=0.030) was observed in the IFN group. Lower levels of albumin and C-reactive protein and higher level of sodium were observed in the IFN group. Glucocorticoid dosage was lower in the IFN group (median, 40 vs. 80 mg/d, P=0.025). Compared to the control group, fewer patients in the IFN group were ventilated (13.2% vs. 33.3%, P=0.015) and admitted to intensive care unit (ICU) (16.2% vs. 44.4%, P=0.002). There were also fewer critical patients in the IFN group (7.4% vs. 25.0%, P=0.017) upon admission. Although complications during admission process were comparable between groups, the discharge rate (85.3% vs. 66.7%, P=0.027) was higher and the hospitalization time (16 vs. 21 d, P=0.015) was shorter in the IFN group. When other confounding factors were not considered, virus shedding time (10 vs. 13 d, P=0.014) was also shorter in the IFN group. However, when the influence of other factors was eliminated using propensity score matching, virus shedding time was not significantly shorter than that of the control group (12 vs. 15 d, P=0.206). CONCLUSIONS: IFN-α2b spray inhalation did not shorten virus shedding time of SARS-CoV-2 in hospitalized patients.


Subject(s)
Coronavirus Infections/drug therapy , Interferon alpha-2/administration & dosage , Nasal Sprays , Pneumonia, Viral/drug therapy , Virus Shedding/drug effects , Albumins/analysis , Antiviral Agents/administration & dosage , Betacoronavirus , C-Reactive Protein/analysis , COVID-19 , Case-Control Studies , China , Glucocorticoids/pharmacology , Hospitalization , Humans , Pandemics , Propensity Score , Retrospective Studies , SARS-CoV-2 , Sodium/blood
13.
Infect Dis Poverty ; 9(1): 85, 2020 Jul 08.
Article in English | MEDLINE | ID: covidwho-635127

ABSTRACT

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) is now becoming an enormous threat to public health. The clinical spectrum of COVID-19 is extensive, of which critical cases are with rapid disease progression and high mortality. The aim of our study is to summarize the characteristics of different subtypes and explore risk factors of illness severity for early identification and prompt treatment. METHODS: In this retrospective study, we collected data of patients confirmed COVID-19 in Zhejiang Province from 17 January to 12 February 2020. According to the definition of clinical classification, we divided confirmed cases into four types, and summarize epidemiological and clinical characteristics, laboratory and radiograph findings, treatments, and outcomes, respectively. Moreover, we used univariate and multivariate ordinal logistic regression models to explore risk factors for the severity of illness in patients with COVID-19. RESULTS: A total of 788 patients were enrolled in our study, of whom 52 cases (6.6%) were mild type, 658 cases (83.5%) were common type, 61 cases (7.2%) were severe type, and 17 cases (2.2%) were critical type. Multivariate ordinal logistic regression demonstrated increasing odds of the severity of illness in patients with COVID-19 associated with male (odds ratio [OR] = 1.7, 95% confidence interval [CI]: 1.2-2.6 P = 0.008), fever (OR = 3.6, 95% CI: 2.1-6.3, P <  0.001), cough (OR = 1.7, 95% CI: 1.0-2.9, P = 0.041), hemoptysis (OR = 3.4, 95% CI: 1.1-10.3, P = 0.032), gastrointestinal symptoms (OR = 1.9, 95% CI: 1.0-3.5, P = 0.047), hypertension (OR = 2.6, 95% CI: 1.2-5.6, P = 0.013). With the increase of age-grading, risk for the severity of illness was gradually higher (≤ 18 years [OR = 1.0], 19-40 years [OR = 12.7, 95% CI: 4.5-36.0, P < 0.001], 41-65 years [OR = 14.8, 95% CI: 5.2-42.1, P <  0.001], ≥ 66 years [OR = 56.5, 95% CI: 17.1-186.5, P < 0.001]). CONCLUSIONS: Clinicians should pay close attention to these features in patients with COVID-19 including older age, male, fever, cough, hemoptysis, gastrointestinal symptoms and hypertension to identify the severity of illness as early as possible.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/pathology , Pneumonia, Viral/epidemiology , Pneumonia, Viral/pathology , Adult , Age Distribution , Aged , Betacoronavirus , COVID-19 , China/epidemiology , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Early Diagnosis , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , Retrospective Studies , Risk Factors , SARS-CoV-2 , Treatment Outcome , Young Adult
14.
Am J Gastroenterol ; 115(7): 1075-1083, 2020 07.
Article in English | MEDLINE | ID: covidwho-459522

ABSTRACT

INTRODUCTION: Elevated liver enzyme levels are observed in patients with coronavirus disease 2019 (COVID-19); however, these features have not been characterized. METHODS: Hospitalized patients with COVID-19 in Zhejiang Province, China, from January 17 to February 12, 2020, were enrolled. Liver enzyme level elevation was defined as alanine aminotransferase level >35 U/L for men and 25 U/L for women at admission. Patients with normal alanine aminotransferase levels were included in the control group. Reverse transcription polymerase chain reaction was used to confirm severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and patients symptomatic with SARS-CoV-2 infection were defined as patients with COVID-19. Epidemiological, demographic, clinical, laboratory, treatment, and outcome data were collected and compared. RESULTS: Of 788 patients with COVID-19, 222 (28.2%) patients had elevated liver enzyme levels (median [interquartile range {IQR}] age, 47.0 [35.0-55.0] years; 40.5% women). Being male, overweight, and smoking increased the risk of liver enzyme level elevation. The liver enzyme level elevation group had lesser pharyngalgia and more diarrhea than the control group. The median time from illness onset to admission was 3 days for liver enzyme level elevation groups (IQR, 2-6), whereas the median hospitalization time for 86 (38.7%) discharged patients was 13 days (IQR, 11-16). No differences in disease severity and clinical outcomes were noted between the groups. DISCUSSION: We found that 28.2% of patients with COVID-19 presented with elevated liver enzyme levels on admission, which could partially be related to SARS-CoV-2 infection. Male patients had a higher risk of liver enzyme level elevation. With early medical intervention, liver enzyme level elevation did not worsen the outcomes of patients with COVID-19.


Subject(s)
Coronavirus Infections , Hepatitis, Viral, Human/enzymology , Liver Function Tests , Pandemics , Pneumonia, Viral , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/complications , Cross-Sectional Studies , Female , Hepatitis, Viral, Human/virology , Humans , Liver Diseases/enzymology , Liver Diseases/virology , Male , Middle Aged , Pneumonia, Viral/complications , Retrospective Studies , Risk Factors , SARS-CoV-2
15.
Gut ; 69(6): 1002-1009, 2020 06.
Article in English | MEDLINE | ID: covidwho-18560

ABSTRACT

OBJECTIVE: The SARS-CoV-2-infected disease (COVID-19) outbreak is a major threat to human beings. Previous studies mainly focused on Wuhan and typical symptoms. We analysed 74 confirmed COVID-19 cases with GI symptoms in the Zhejiang province to determine epidemiological, clinical and virological characteristics. DESIGN: COVID-19 hospital patients were admitted in the Zhejiang province from 17 January 2020 to 8 February 2020. Epidemiological, demographic, clinical, laboratory, management and outcome data of patients with GI symptoms were analysed using multivariate analysis for risk of severe/critical type. Bioinformatics were used to analyse features of SARS-CoV-2 from Zhejiang province. RESULTS: Among enrolled 651 patients, 74 (11.4%) presented with at least one GI symptom (nausea, vomiting or diarrhoea), average age of 46.14 years, 4-day incubation period and 10.8% had pre-existing liver disease. Of patients with COVID-19 with GI symptoms, 17 (22.97%) and 23 (31.08%) had severe/critical types and family clustering, respectively, significantly higher than those without GI symptoms, 47 (8.14%) and 118 (20.45%). Of patients with COVID-19 with GI symptoms, 29 (39.19%), 23 (31.08%), 8 (10.81%) and 16 (21.62%) had significantly higher rates of fever >38.5°C, fatigue, shortness of breath and headache, respectively. Low-dose glucocorticoids and antibiotics were administered to 14.86% and 41.89% of patients, respectively. Sputum production and increased lactate dehydrogenase/glucose levels were risk factors for severe/critical type. Bioinformatics showed sequence mutation of SARS-CoV-2 with m6A methylation and changed binding capacity with ACE2. CONCLUSION: We report COVID-19 cases with GI symptoms with novel features outside Wuhan. Attention to patients with COVID-19 with non-classic symptoms should increase to protect health providers.


Subject(s)
Betacoronavirus , Clinical Laboratory Techniques , Coronavirus Infections , Gastrointestinal Tract , Pandemics , Pneumonia, Viral , Adult , COVID-19 , COVID-19 Testing , China , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Coronavirus Infections/virology , Female , Gastrointestinal Tract/physiopathology , Gastrointestinal Tract/virology , Humans , Male , Middle Aged , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Pneumonia, Viral/virology , Risk Factors , SARS-CoV-2
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