Finding Asymptomatic Spreaders in a COVID-19 Transmission Network by Graph Attention Networks.

In the COVID-19 epidemic the mildly symptomatic and asymptomatic infections generate a substantial portion of virus spread; these undetected individuals make it difficult to assess the effectiveness of preventive measures as most epidemic prevention strategies are based on the detected data. Effectively identifying the undetected infections in local transmission will be of great help in COVID-19 control. In this work, we propose an RNA virus transmission network representation model based on graph attention networks (RVTR); this model is constructed using the principle of natural language processing to learn the information of gene sequence and using a graph attention network to catch the topological character of COVID-19 transmission networks. Since SARS-CoV-2 will mutate when it spreads, our approach makes use of graph context loss function, which can reflect that the genetic sequence of infections with close spreading relation will be more similar than those with a long distance, to train our model. Our approach shows its ability to find asymptomatic spreaders both on simulated and real COVID-19 datasets and performs better when compared with other network representation and feature extraction methods.

Detection and genetic characterization of novel infectious bronchitis viruses from recent outbreaks in broiler and layer chicken flocks in southern China, 2021.

Avian infectious bronchitis virus (IBV) is a prevalent RNA virus that causes respiratory distress, nephritis, salpingitis, and egg production decline in chickens, resulting in significant economic loss. IBV is composed of complex genotypes and serotypes, which poses a great challenge for disease control. The current study reports 2 IBV outbreaks which were characterized by respiratory symptoms in IBV vaccinated commercial broilers and layers in Guangdong, China, in 2021. Two IBV strains, ZH01 and HH09, were identified via a RT-PCR assay through targeting the N gene and further characterization through full-length spike (S) gene sequence analysis. Phylogenetic analysis of S1 gene revealed that both ZH01 and HH09 belonged to the GI-19 lineage but contained a certain genetic distance from the GI-19 strain. Of note, the ZH01 and HH09 strains share a low homology of 70 and 86%, respectively, with common vaccine strains (H120), resulting in low vaccine protection. Further recombination analysis based on the S1 sequence suggested the newly identified IBV strains emerged through an intragroup recombination events between CK/CH/SCDY2003-2 and I0305/19 from G1-19 lineage. In addition, a number of novel mutations such as T273I, T292A, and S331K were found in the emerging IBV strains. Taken together, this study reports the genetic characteristics of 2 recent IBV outbreaks in southern China and emphasizes the urgent need for enhanced surveillance and development of novel vaccines for the control of IBV.

Clinical Analysis of Kidney Injury in Elderly Patients with COVID-19

Objective: The aim of the study was to analyze the clinical features of elderly patients with coronavirus disease 2019 (COVID-19) and to explore the relationship between COVID-19 patients and kidney injury. Methods: A total of 188 elderly patients with confirmed COVID-19 enrolled in this study were hospitalized for at least 1 week in the Central Theater Command General Hospital of Chinese People's Liberation Army from January 3, 2020 to March 14, 2020. The recorded information included clinical data and results of kidney-related laboratory tests. Retrospective analysis was performed. Results: The median age of the patients was 69 years (interquartile range 65–78, range: 60–97 years);31.4% were 60–74 years old, and 68.6% were over 75 years old. A total of 12.8% and 18.6% of the patients were in critical and severe stages of COVID-19, respectively. The proportions of patients using mechanical ventilators and deaths were 9.5% and 8.5%, respectively. A total of 26.1% and 8.5% of the patients showed mild elevation of blood urea nitrogen (BUN) and serum creatinine (SCr) levels at admission. A total of 18.6% and 5.9% of the patients had elevated BUN and SCr 1 week after admission, respectively. A total of 3.1% of the patients were diagnosed with acute kidney injury, and 75% of those patients had chronic kidney disease before admission. Compared with the patients aged 60–74 years, those over 75 years exhibited significantly increased proportions of elevated BUN levels, critical illness, use of mechanical ventilated, and death. Multivariate logistic regression analysis revealed that an elevated BUN level at admission and 1 week after admission were independent risk factors for death in the elderly patients with COVID-19. Conclusion: There were more critical cases and a high mortality in elderly patients with COVID-19. An increased BUN level was an independent risk factor for death in elderly patients with COVID-19.

Genetic characterization and phylogenetic analysis of porcine epidemic diarrhea virus in Guangdong, China, between 2018 and 2019.

Porcine epidemic diarrhea virus (PEDV), a leading cause of piglet diarrhea outbreaks, poses a significant danger to the swine industry. The aim of this study was to investigate the epidemic characteristics of PEDV that was circulating in Guangdong province, one of China's major pig producing provinces. Clinical samples were collected from eight pig farms in Guangdong province between 2018 and 2019 and tested for the major porcine enteric pathogens, including PEDV, transmissible gastroenteritis virus (TGEV), Swine enteric coronavirus (SeCoV), Swine acute diarrhea syndrome coronavirus (SADS-CoV), porcine deltacoronavirus (PDCoV), and porcine rotavirus (RV). As a result, only PEDV and RV were detected at a rate of 47.0% (16/34) and 18.6% (8/34), respectively. Coinfectoin with PEDV and RV occurred at a rate of PEDV 12.5% (2/16). Subsequently, the full-length S gene sequences of 13 PEDV strains were obtained, and phylogenetic analysis suggested the presence of GII-c group PEDV strains in this region (non-S-INDEL). Two novel common amino acid insertions (55T/IG56 and 551L) and one novel glycosylation site (1199G+) were detected when the CV777 and ZJ08 vaccine strains were compared. Furthermore, intragroup recombination events in the S gene regions 51-548 and 2478-4208 were observed in the PEDV strains studied. In summary, the observations provide current information on the incidence of viral agents causing swine diarrhea in southern China and detailed the genetic characteristics and evolutionary history of the dominant PEDV field strains. Our findings will aid in the development of an updated vaccine for the prevention and control of PEDV variant strains.

Heterogeneity and effectiveness analysis of COVID-19 prevention and control in major cities in China through time-varying reproduction number estimation.

Beginning on December 31, 2019, the large-scale novel coronavirus disease 2019 (COVID-19) emerged in China. Tracking and analysing the heterogeneity and effectiveness of cities' prevention and control of the COVID-19 epidemic is essential to design and adjust epidemic prevention and control measures. The number of newly confirmed cases in 25 of China's most-affected cities for the COVID-19 epidemic from January 11 to February 10 was collected. The heterogeneity and effectiveness of these 25 cities' prevention and control measures for COVID-19 were analysed by using an estimated time-varying reproduction number method and a serial correlation method. The results showed that the effective reproduction number (R) in 25 cities showed a downward trend overall, but there was a significant difference in the R change trends among cities, indicating that there was heterogeneity in the spread and control of COVID-19 in cities. Moreover, the COVID-19 control in 21 of 25 cities was effective, and the risk of infection decreased because their R had dropped below 1 by February 10, 2020. In contrast, the cities of Wuhan, Tianmen, Ezhou and Enshi still had difficulty effectively controlling the COVID-19 epidemic in a short period of time because their R was greater than 1.

Clinical characteristics of the first known cases of death caused by COVID-19 pneumonia.

Severe pneumonia caused by COVID-19 has resulted in many deaths worldwide. Here, we analyzed the clinical characteristics of the first 17 reported cases of death due to COVID-19 pneumonia in Wuhan, China. Demographics, initial symptoms, complications, chest computerized tomography (CT) images, treatments, and prognoses were collected and analyzed from the National Health Committee of China data. The first 17 reported deaths from COVID-19 were predominately in older men; 82.35% of patients were older than 65 years, and 76.47% were males. The most common initial symptoms were fever or fatigue (14 cases, 82.35%), respiratory symptoms, such as cough (12 cases, 70.59%), and neurological symptoms, such as headache (3 cases, 17.65%). The most common finding of chest CT was viral pneumonia (5 cases, 29.41%). Anti-infectives (11 cases, 64.71%) and mechanical ventilation (9 cases, 52.94%) were commonly used for treatment. Most of the patients (16 cases, 94.12%) died of acute respiratory distress syndrome (ARDS). Our findings show that advanced age and male gender are effective predictors of COVID-19 mortality, and suggest that early interventions to reduce the incidence of ARDS may improve prognosis of COVID-19 pneumonia patients.

Diagnosis and treatment of emergency surgeries in otorhinolaryngology, head and neck surgery during the covid-19 outbreak: A single center experience.

The 2019 Novel Coronavirus (2019-nCoV, SARS-CoV-2) infection has already been assigned as a Class B infectious disease requiring Class A management strategy according to "the Law on the Prevention and Control of Infectious Diseases of the People's Republic of China" and become a global pandemic. The incidence of emergencies in otorhinolaryngology, head and neck surgery such as foreign bodies in the esophagus and the respiratory tract, epistaxis, laryngeal obstruction with dyspnea, and head and neck trauma are relatively high. Emergency surgeries are required as some of these diseases progress rapidly and probably be life-threatening. In this article, we drafted the recommendations for diagnosis and treatment of emergency surgeries in otorhinolaryngology, head and neck surgery in the epidemic area of novel coronavirus pneumonia based on "Novel Coronavirus Pneumonia Diagnosis and Treatment Plan (Provisional; 7th Edition Revisions)"and WHO guidelines, combined with the experience of emergency surgeries in the Department of Otorhinolaryngology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, which is at the center outbreak area of the SARS-CoV-2 pneumonia (COVID-19) in China, to improve the success rate of treatment for otorhinolaryngology, head and neck surgery emergency surgeries and to reduce the SARS-CoV-2 infection rate in the perioperative period.

Diabetes increases the mortality of patients with COVID-19: a meta-analysis.

AIMS: Nowadays, the ongoing pandemic of COVID-19 caused by the novel coronavirus Syndrome-Coronavirus-2 (SARS-CoV-2) is an emerging, rapidly evolving situation. Complications such as hypertension, diabetes, COPD, cardiovascular disease, and cerebrovascular disease are major risk factors for patients with COVID-19. METHODS: No meta-analysis has explored if or not diabetes related to mortality of patients with COVID-19. Therefore, this meta-analysis first aims to explore the possible clinical mortality between diabetes and COVID-19, analyze if diabetes patients infected with SARS-CoV-2 are exposed to the worst clinical prognostic risk, and to evaluate the reliability of the evidence. RESULTS: Our results showed a close relationship between diabetes and mortality of COVID-19, with a pooled OR of 1.75 (95% CI 1.31-2.36; P = 0.0002). The pooled data were calculated with the fixed effects model (FEM) as no heterogeneity appeared in the studies. Sensitivity analysis showed that after omitting any single study or converting a random effect model to FEM, the main results still held. CONCLUSIONS: Our meta-analysis showed that diabetes increases the mortality of patients with COVID-19. These results indicated the disturbance of blood glucose in the COVID-19 patients. More importantly, this meta-analysis grades the reliability of evidence for further basic and clinical research into the diabetes dysfunction in COVID-19 patients.

Comparison of Hospitalized Patients With ARDS Caused by COVID-19 and H1N1.

BACKGROUND: Since the outbreak of coronavirus disease 2019 (COVID-19) in China in December 2019, considerable attention has been focused on its elucidation. However, it is also important for clinicians and epidemiologists to differentiate COVID-19 from other respiratory infectious diseases such as influenza viruses. RESEARCH QUESTION: The aim of this study was to explore the different clinical presentations between COVID-19 and influenza A (H1N1) pneumonia in patients with ARDS. STUDY DESIGN AND METHODS: This analysis was a retrospective case-control study. Two independent cohorts of patients with ARDS infected with either COVID-19 (n = 73) or H1N1 (n = 75) were compared. Their clinical manifestations, imaging characteristics, treatments, and prognosis were analyzed and compared. RESULTS: The median age of patients with COVID-19 was higher than that of patients with H1N1, and there was a higher proportion of male subjects among the H1N1 cohort (P < .05). Patients with COVID-19 exhibited higher proportions of nonproductive coughs, fatigue, and GI symptoms than those of patients with H1N1 (P < .05). Patients with H1N1 had higher Sequential Organ Failure Assessment (SOFA) scores than patients with COVID-19 (P < .05). The Pao2/Fio2 of 198.5 mm Hg in the COVID-19 cohort was significantly higher than the Pao2/Fio2 of 107.0 mm Hg in the H1N1 cohort (P < .001). Ground-glass opacities was more common in patients with COVID-19 than in patients with H1N1 (P < .001). There was a greater variety of antiviral therapies administered to COVID-19 patients than to H1N1 patients. The in-hospital mortality of patients with COVID-19 was 28.8%, whereas that of patients with H1N1 was 34.7% (P = .483). SOFA score-adjusted mortality of H1N1 patients was significantly higher than that of COVID-19 patients, with a rate ratio of 2.009 (95% CI, 1.563-2.583; P < .001). INTERPRETATION: There were many differences in clinical presentations between patients with ARDS infected with either COVID-19 or H1N1. Compared with H1N1 patients, patients with COVID-19-induced ARDS had lower severity of illness scores at presentation and lower SOFA score-adjusted mortality.

Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study.

The aim of this study was to identify factors associated with the death of patients with COVID-19 pneumonia caused by the novel coronavirus SARS-CoV-2.All clinical and laboratory parameters were collected prospectively from a cohort of patients with COVID-19 pneumonia who were hospitalised to Wuhan Pulmonary Hospital (Wuhan City, Hubei Province, China) between 25 December 2019 and 7 February 2020. Univariate and multivariate logistic regression analysis revealed that age ≥65 years (OR 3.765, 95% CI 1.146­17.394; p=0.023), pre-existing concurrent cardiovascular or cerebrovascular diseases (OR 2.464, 95% CI 0.755­8.044; p=0.007), CD3+CD8+ T-cells ≤75 cells·µL−1 (OR 3.982, 95% CI 1.132­14.006; p<0.001) and cardiac troponin I ≥0.05 ng·mL−1 (OR 4.077, 95% CI 1.166­14.253; p<0.001) were associated with an increase in risk of mortality from COVID-19 pneumonia." has been corrected to: "Univariate and multivariate logistic regression analysis revealed that age ≥65 years (OR 3.765, 95% CI 1.201−11.803; p=0.023), pre-existing concurrent cardiovascular or cerebrovascular diseases (OR 2.464, 95% CI 1.279−4.747; p=0.007), CD3+CD8+ T-cells ≤75 cells·µL−1 (OR 3.982, 95% CI 1.761­9.004; p<0.001) and cardiac troponin I ≥0.05 ng·mL−1 (OR 4.077, 95% CI 1.778­9.349; p<0.001) were associated with an increase in risk of mortality from COVID-19 pneumonia. In a sex-, age- and comorbid illness-matched case-control study, CD3+CD8+ T-cells ≤75 cells·µL-1 and cardiac troponin I ≥0.05 ng·mL-1 remained as predictors for high mortality from COVID-19 pneumonia.We identified four risk factors: age ≥65 years, pre-existing concurrent cardiovascular or cerebrovascular diseases, CD3+CD8+ T-cells ≤75 cells·µL-1 and cardiac troponin I ≥0.05 ng·mL-1 The latter two factors, especially, were predictors for mortality of COVID-19 pneumonia patients.