SARS-CoV-2 Antibody Responses to the Ancestral SARS-CoV-2 Strain and Omicron BA.1 and BA.4/BA.5 Variants in Nursing Home Residents After Receipt of Bivalent COVID-19 Vaccine - Ohio and Rhode Island, September-November 2022.

Introduction of monovalent COVID-19 mRNA vaccines in late 2020 helped to mitigate disproportionate COVID-19-related morbidity and mortality in U.S. nursing homes (1); however, reduced effectiveness of monovalent vaccines during the period of Omicron variant predominance led to recommendations for booster doses with bivalent COVID-19 mRNA vaccines that include an Omicron BA.4/BA.5 spike protein component to broaden immune response and improve vaccine effectiveness against circulating Omicron variants (2). Recent studies suggest that bivalent booster doses provide substantial additional protection against SARS-CoV-2 infection and severe COVID-19-associated disease among immunocompetent adults who previously received only monovalent vaccines (3).* The immunologic response after receipt of bivalent boosters among nursing home residents, who often mount poor immunologic responses to vaccines, remains unknown. Serial testing of anti-spike protein antibody binding and neutralizing antibody titers in serum collected from 233 long-stay nursing home residents from the time of their primary vaccination series and including any subsequent booster doses, including the bivalent vaccine, was performed. The bivalent COVID-19 mRNA vaccine substantially increased anti-spike and neutralizing antibody titers against Omicron sublineages, including BA.1 and BA.4/BA.5, irrespective of previous SARS-CoV-2 infection or previous receipt of 1 or 2 booster doses. These data, in combination with evidence of low uptake of bivalent booster vaccination among residents and staff members in nursing homes (4), support the recommendation that nursing home residents and staff members receive a bivalent COVID-19 booster dose to reduce associated morbidity and mortality (2).

Cross-reactive SARS-CoV-2 epitope targeted across donors informs immunogen design.

The emergence of the antigenically distinct and highly transmissible Omicron variant highlights the possibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune escape due to viral evolution. This continued evolution, along with the possible introduction of new sarbecoviruses from zoonotic reservoirs, may evade host immunity elicited by current SARS-CoV-2 vaccines. Identifying cross-reactive antibodies and defining their epitope(s) can provide templates for rational immunogen design strategies for next-generation vaccines. Here, we characterize the receptor-binding-domain-directed, cross-reactive humoral repertoire across 10 human vaccinated donors. We identify cross-reactive antibodies from diverse gene rearrangements targeting two conserved receptor-binding domain epitopes. An engineered immunogen enriches antibody responses to one of these conserved epitopes in mice with pre-existing SARS-CoV-2 immunity; elicited responses neutralize SARS-CoV-2, variants, and related sarbecoviruses. These data show how immune focusing to a conserved epitope targeted by human cross-reactive antibodies may guide pan-sarbecovirus vaccine development, providing a template for identifying such epitopes and translating to immunogen design.

Multi-Model Attention Fusion Multilayer Perceptron Prediction Method for Subway OD Passenger Flow under COVID-19

At present, machine learning has been successfully applied in many fields and has achieved amazing results. Meanwhile, over the past few years, the pandemic has transformed the transportation industry. The two hot issues prompt us to rethink the traditional problem of passenger flow forecasting. As a special structure embedded in the machine learning model, the attention mechanism is used to automatically learn and calculate the contribution degree of input data to output data. Therefore, this paper uses the attention mechanism to find the best model to predict OD passenger flow under COVID-19. Holiday characteristics, minimum temperature, COVID-19 factors, and past origin-destination (OD) passenger flow were used as input characteristics. In the first stage, the attention mechanism was used to capture the advantages of the trained random forest, extreme gradient boosting (XGBoost), gradient boosting decision tree (GBDT), and Adaboost models, and then the MLP was trained. Afterward, the weight distribution of the two models is carried out by using the historical passenger flow. The multi-model attention+ MLP model was used to evaluate the OD passenger flow prediction of Dalian Metro Line 1 under COVID-19. All the possible choices in this process were taken as a comparison experiment. The results show that only the fusion model combining the attention mechanism of random forest and XGBoost with MLP has the highest prediction accuracy.

Shared Cycling Demand Prediction during COVID-19 Combined with Urban Computing and Spatiotemporal Residual Network

The regularity and demand predictions of shared cycling are very necessary and challenging for the management and development of urban pedestrian and bicycle traffic. The bicycle-sharing system has the problem of spatial and temporal demand fluctuations and presents a very complex nonlinear regularity. The demand for shared bicycles is affected by many factors, including time, space, weather and the situation of COVID-19. This study proposes a new bicycle-sharing demand forecasting model (USTARN) based on the impact of COVID-19, which combines urban computing and spatiotemporal attention residual network. USTARN consists of two parts. In the first part, a spatiotemporal attention residual network model is established to learn the temporal correlation and spatial correlation of shared bicycle demand. The temporal characteristic branches of each spatial small region are trained, respectively, to predict the shared bicycle demand in batches in different regions and periods according to the historical data. In order to improve the prediction accuracy of the model, the second part of the model adjusts and redistributes the prediction results of the first part by learning other information of the city, such as the severity of COVID-19, weather, temperature, wind speed and holidays. It can predict the demand for shared bicycles in different urban areas in different periods and different severities of COVID-19. This study uses the order data of shared bicycles during the period of COVID-19 in 2020 obtained from the open data platform of Shenzhen municipal government as verification, analyzes the spatiotemporal regularity of the system demand and discusses the impact of the number of newly diagnosed patients and the daily minimum temperature on the demand for shared bicycles. The results show that USTARN can fully reflect time, space, the epidemic situation, weather and temperature, and the prediction results of the impact of wind speed and other factors on the demand for shared bicycles are better than the classical methods.

A convolutional neural network-based COVID-19 detection method using chest CT images.

Background: High-throughput population screening for the novel coronavirus disease (COVID-19) is critical to controlling disease transmission. Convolutional neural networks (CNNs) are a cutting-edge technology in the field of computer vision and may prove more effective than humans in medical diagnosis based on computed tomography (CT) images. Chest CT images can show pulmonary abnormalities in patients with COVID-19. Methods: In this study, CT image preprocessing are firstly performed using fuzzy c-means (FCM) algorithm to extracted the region of the pulmonary parenchyma. Through multiscale transformation, the preprocessed image is subjected to multi scale transformation and RGB (red, green, blue) space construction. After then, the performances of GoogLeNet and ResNet, as the most advanced CNN architectures, were compared in COVID-19 detection. In addition, transfer learning (TL) was employed to solve overfitting problems caused by limited CT samples. Finally, the performance of the models were evaluated and compared using the accuracy, recall rate, and F1 score. Results: Our results showed that the ResNet-50 method based on TL (ResNet-50-TL) obtained the highest diagnostic accuracy, with a rate of 82.7% and a recall rate of 79.1% for COVID-19. These results showed that applying deep learning technology to COVID-19 screening based on chest CT images is a very promising approach. This study inspired us to work towards developing an automatic diagnostic system that can quickly and accurately screen large numbers of people with COVID-19. Conclusions: We tested a deep learning algorithm to accurately detect COVID-19 and differentiate between healthy control samples, COVID-19 samples, and common pneumonia samples. We found that TL can significantly increase accuracy when the sample size is limited.

Association between detectable SARS-COV-2 RNA in anal swabs and disease severity in patients with coronavirus disease 2019.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in the intestines and feces, but its clinical significance is not completely clear. We aim to characterize the longitudinal test results of SARS-CoV-2 RNA in anal swabs and to explore the association with disease severity. METHODS: We included laboratory-confirmed coronavirus disease 2019 (COVID-19) patients, who were hospitalized in Guangzhou Eighth People's Hospital and excluded those who had not received anal swabs for SARS-COV-2 RNA testing. Epidemiological, clinical, and laboratory data were obtained. Throat swabs and anal swabs were collected periodically for SARS-COV-2 RNA detection. RESULTS: Two hundred and seventeen eligible patients (median aged 50 years, 50.2% were females) were analyzed. 21.2% (46/217) of the patients were detected with SARS-CoV-2 RNA in anal swabs. The duration of viral RNA was longer, but the viral load was lower in anal swabs than throat swabs in the early stage of the disease. During a median follow-up of 20 days, 30 (13.8%) patients were admitted to the intensive care unit (ICU) for high-flow nasal cannula or higher-level oxygen support measures to correct hypoxemia. Detectable viral RNA in anal swabs (adjusted hazard ratio [aHR], 2.50; 95% confidence interval [CI], 1.20-5.24), increased C-reactive protein (aHR, 3.14; 95% CI, 1.35-7.32) and lymphocytopenia (aHR, 3.12; 95% CI, 1.46-6.67) were independently associated with ICU admission. The cumulative incidence of ICU admission was higher among patients with detectable viral RNA in anal swabs (26.3% vs 10.7%, P = .006). CONCLUSION: Detectable SARS-CoV-2 RNA in the digestive tract was a potential warning indicator of severe disease.

Air curtain dust-collecting technology：Investigation of industrial application in tobacco factory of the air curtain dust-collecting system

The air curtain system can collect the dust particles from hard-to-seal sources, which proves to be a feasible method for satisfying the increasing dust prevention requirements in China. In this study, aiming at addressing the dust escape problem at the tobacco stem loading point in a tobacco factory, a rotational flow air curtain dust-collecting system with a size of 2m x 2m x 2m was used for dust collection. The dust-collecting characteristics using the original dust suction hood and the developed air curtain dust-collecting system were analyzed and compared. Results show that the external dust concentration when the original dust suction hood operated was as high as 83.65 mg/m3, with a dust-collecting efficiency of only 16.35%, suggesting serious dust escape;after the use of the developed air curtain dust-collecting system, the dust-collecting efficiency reached up to 86.93∼94.76% under the same operating conditions. By studying the influence of two factors, air curtain jet velocity and exhaust-to-pressure ratio, on the dust collection efficiency of the air curtain system, at an exhaust-to-pressure ratio of 0.8 and an air curtain jet velocity of 13.5 m/s, the corresponding dust-collecting efficiency reached a maximum of 94.76%. The present test results confirmed a better application effect of the developed air curtain dust-collecting system than the original dust-collecting system at the industrial loading point. Using the developed air curtain dust-collecting system is mainly aimed at the dust source, reduce the dust in the workshop dissemination and dispersion that can lower the transmission path of COVID-19 via aerosol.

Risk factors for severe and critically ill COVID-19 patients: A review.

The pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused an unprecedented global social and economic impact, and high numbers of deaths. Many risk factors have been identified in the progression of COVID-19 into a severe and critical stage, including old age, male gender, underlying comorbidities such as hypertension, diabetes, obesity, chronic lung diseases, heart, liver and kidney diseases, tumors, clinically apparent immunodeficiencies, local immunodeficiencies, such as early type I interferon secretion capacity, and pregnancy. Possible complications include acute kidney injury, coagulation disorders, thoromboembolism. The development of lymphopenia and eosinopenia are laboratory indicators of COVID-19. Laboratory parameters to monitor disease progression include lactate dehydrogenase, procalcitonin, high-sensitivity C-reactive protein, proinflammatory cytokines such as interleukin (IL)-6, IL-1ß, Krebs von den Lungen-6 (KL-6), and ferritin. The development of a cytokine storm and extensive chest computed tomography imaging patterns are indicators of a severe disease. In addition, socioeconomic status, diet, lifestyle, geographical differences, ethnicity, exposed viral load, day of initiation of treatment, and quality of health care have been reported to influence individual outcomes. In this review, we highlight the scientific evidence on the risk factors of severity of COVID-19.

Clinical, radiological, and laboratory characteristics and risk factors for severity and mortality of 289 hospitalized COVID-19 patients.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a global pandemic, with 10%-20% of severe cases and over 508 000 deaths worldwide. OBJECTIVE: This study aims to address the risk factors associated with the severity of COVID-19 patients and the mortality of severe patients. METHODS: 289 hospitalized laboratory-confirmed COVID-19 patients were included in this study. Electronic medical records, including patient demographics, clinical manifestation, comorbidities, laboratory tests results, and radiological materials, were collected and analyzed. According to the severity and outcomes of the patients, they were divided into three groups: nonsurvived (n = 49), survived severe (n = 78), and nonsevere (n = 162) groups. Clinical, laboratory, and radiological data were compared among these groups. Principal component analysis (PCA) was applied to reduce the dimensionality and visualize the patients on a low-dimensional space. Correlations between clinical, radiological, and laboratory parameters were investigated. Univariate and multivariate logistic regression methods were used to determine the risk factors associated with mortality in severe patients. Longitudinal changes of laboratory findings of survived severe cases and nonsurvived cases during hospital stay were also collected. RESULTS: Of the 289 patients, the median age was 57 years (range, 22-88) and 155 (53.4%) patients were male. As of the final follow-up date of this study, 240 (83.0%) patients were discharged from the hospital and 49 (17.0%) patients died. Elder age, underlying comorbidities, and increased laboratory variables, such as leukocyte count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), procalcitonin (PCT), D-dimer, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and blood urea nitrogen (BUN) on admission, were found in survived severe cases compared to nonsevere cases. According to the multivariate logistic regression analysis, elder age, a higher number of affected lobes, elevated CRP levels on admission, increased prevalence of chest tightness/dyspnea, and smoking history were independent risk factors for death of severe patients. A trajectory in PCA was observed from "nonsevere" toward "nonsurvived" via "severe and survived" patients. Strong correlations between the age of patients, the affected lobe numbers, and laboratory variables were identified. Dynamic changes of laboratory findings of survived severe cases and nonsurvived cases during hospital stay showed that continuing increase of leukocytes and neutrophil count, sustained lymphopenia and eosinopenia, progressing decrease in platelet count, as well as high levels of NLR, CRP, PCT, AST, BUN, and serum creatinine were associated with in-hospital death. CONCLUSIONS: Survived severe and nonsurvived COVID-19 patients had distinct clinical and laboratory characteristics, which were separated by principle component analysis. Elder age, increased number of affected lobes, higher levels of serum CRP, chest tightness/dyspnea, and smoking history were risk factors for mortality of severe COVID-19 patients. Longitudinal changes of laboratory findings may be helpful in predicting disease progression and clinical outcome of severe patients.

Clinical characteristics of 182 pediatric COVID-19 patients with different severities and allergic status.

BACKGROUND: The pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has made widespread impact recently. We aim to investigate the clinical characteristics of COVID-19 children with different severities and allergic status. METHODS: Data extracted from the electronic medical records, including demographics, clinical manifestations, comorbidities, laboratory and immunological results, and radiological images of 182 hospitalized COVID-19 children, were summarized and analyzed. RESULTS: The median age was 6 years, ranging from 3 days to 15 years, and there were more boys (male-female ratio about 2:1) within the studied 182 patients. Most of the children were infected by family members. Fever (43.4%) and dry cough (44.5%) were common symptoms, and gastrointestinal manifestations accounted for 11.0%, including diarrhea, abdominal discomfort, and vomiting. 71.4% had abnormal chest computed tomography (CT) scan images, and typical signs of pneumonia were ground-glass opacity and local patchy shadowing on admission. Laboratory results were mostly within normal ranges, and only a small ratio of lymphopenia (3.9%) and eosinopenia (29.5%) were observed. The majority (97.8%) of infected children were not severe, and 24 (13.2%) of them had asymptomatic infections. Compared to children without pneumonia (manifested as asymptomatic and acute upper respiratory infection), children with pneumonia were associated with higher percentages of the comorbidity history, symptoms of fever and cough, and increased levels of serum procalcitonin, alkaline phosphatase, and serum interleukins (IL)-2, IL-4, IL-6, IL-10, and TNF-α. There were no differences in treatments, duration of hospitalization, time from first positive to first negative nucleic acid testing, and outcomes between children with mild pneumonia and without pneumonia. All the hospitalized COVID-19 children had recovered except one death due to intussusception and sepsis. In 43 allergic children with COVID-19, allergic rhinitis (83.7%) was the major disease, followed by drug allergy, atopic dermatitis, food allergy, and asthma. Demographics and clinical features were not significantly different between allergic and nonallergic groups. Allergic patients showed less increase in acute phase reactants, procalcitonin, D-dimer, and aspartate aminotransferase levels compared with all patients. Immunological profiles including circulating T, B, and NK lymphocyte subsets, total immunoglobulin and complement levels, and serum cytokines did not show any difference in allergic and pneumonia groups. Neither eosinophil counts nor serum total immunoglobulin E (IgE) levels showed a significant correlation with other immunological measures, such as other immunoglobulins, complements, lymphocyte subset numbers, and serum cytokine levels. CONCLUSION: Pediatric COVID-19 patients tended to have a mild clinical course. Patients with pneumonia had higher proportion of fever and cough and increased inflammatory biomarkers than those without pneumonia. There was no difference between allergic and nonallergic COVID-19 children in disease incidence, clinical features, and laboratory and immunological findings. Allergy was not a risk factor for developing and severity of SARS-CoV-2 infection and hardly influenced the disease course of COVID-19 in children.

Longitudinal clinical and radiographic evaluation reveals interleukin-6 as an indicator of persistent pulmonary injury in COVID-19.

Rationale: Previous studies of coronavirus disease 2019 (COVID-19) were mainly focused on cross-sectional analysis. In this study, we sought to evaluate the dynamic changes of immunological and radiographic features, and the association with the outcome of pulmonary lesions in COVID-19 patients. Methods: Peripheral blood samples and radiographic data were collected longitudinally for up to 8 weeks from 158 laboratory-confirmed COVID-19 patients. The chest computed tomography (CT) scans were scored based on a semi-quantification assessment according to the extent of pulmonary abnormalities; the temporal change of the immunological and radiographic features was analyzed. Results: Compared with mild and moderate patients, severe patients had significantly decreased counts of lymphocytes, CD4+ T cells, CD8+ T cells, and CD19+ B cells but dramatically elevated counts of neutrophils and levels of interleukin (IL)-6. Sequential monitoring showed a sustained increase in lymphocytes counts and significantly decreased levels of IL-6 in severe patients during the disease course. Notably, patients with persistent pulmonary lesions (CT score ≥ 5 in week 8) showed high levels of IL-6 during the follow-up period, compared with those with recovery lesions (CT score < 5 in week 8). More importantly, the peak expression of IL-6 prior to the aggravated lung injury was mainly found in patients with persistent lesions, and multivariate analysis showed that IL-6 level upon admission was an independent factor associated with the persistent pulmonary injury. Conclusion: Prolonged elevation of IL-6 is associated with persistent pulmonary lesions in COVID-19 patients. Sequential monitoring and timely intervention of IL-6 may favor the clinical management of COVID-19.

Factors associated with clinical outcomes in patients with Coronavirus Disease 2019 in Guangzhou, China.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) is threatening billions of people. We described the clinical characteristics and explore virological and immunological factors associated with clinical outcomes. METHODS: 297 COVID-19 patients hospitalized in Guangzhou Eighth People's Hospital between January 20 and February 20, 2020 were included. Epidemiological, clinical and laboratory data were collected and analyzed. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) RNA in respiratory tract, blood samples and digestive tract was detected and lymphocyte subsets were tested periodically. RESULT: Among the 297 patients (median age of 48 years), 154 (51.9 %) were female, 245 (82.5 %) mild/moderate cases, and 52 (17.5 %) severe/critical cases. 270 patients were detected for SARS-CoV-2 RNA in anal swabs and/or blood samples, and the overall positive rate was 23.0 % (62/270), higher in severe/critical cases than in mild/moderate cases (52.0 % vs. 16.4 %, P < 0.001). The CD4/CD8 ratio on admission was significantly higher in severe/critical cases than in mild/moderate cases (1.84 vs. 1.50, P = 0.022). During a median follow-up period of 17 days, 36 (12.1 %) patients were admitted to intensive care unit (ICU), 16 (5.4 %) patients developed respiratory failure and underwent mechanical ventilation, four (1.3 %) patients needed extracorporeal membrane oxygenation (ECMO), only one (0.34 %) patients died of multiple organ failure. Detectable SARS-CoV-2 RNA in anal swabs and/or blood samples, as well as higher CD4/CD8 ratio were independent risk factors of respiratory failure and ICU admission. CONCLUSIONS: Most of COVID-19 patients in Guangzhou are mild/moderate, and presence of extrapulmonary virus and higher CD4/CD8 ratio are associated with higher risk of worse outcomes.

Eleven faces of coronavirus disease 2019.

BACKGROUND AND AIMS: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has recently spread worldwide and been declared a pandemic. We aim to describe here the various clinical presentations of this disease by examining eleven cases. METHODS: Electronic medical records of 11 patients with COVID-19 were collected, and demographics, clinical manifestations, outcomes, key laboratory results, and radiological images are discussed. RESULTS: The clinical course of the eleven cases demonstrated the complexity of the COVID-19 profile with different clinical presentations. Clinical manifestations range from asymptomatic cases to patients with mild and severe symptoms, with or without pneumonia. Laboratory detection of the viral nucleic acid can yield false-negative results, and serological testing of virus-specific IgG and IgM antibodies should be used as an alternative for diagnosis. Patients with common allergic diseases did not develop distinct symptoms and severe courses. Cases with a pre-existing condition of chronic obstructive pulmonary disease or complicated with a secondary bacterial pneumonia were more severe. CONCLUSION: All different clinical characteristics of COVID-19 should be taken into consideration to identify patients that need to be in strict quarantine for the efficient containment of the pandemic.

Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been widely spread. We aim to investigate the clinical characteristic and allergy status of patients infected with SARS-CoV-2. METHODS: Electronic medical records including demographics, clinical manifestation, comorbidities, laboratory data, and radiological materials of 140 hospitalized COVID-19 patients, with confirmed result of SARS-CoV-2 viral infection, were extracted and analyzed. RESULTS: An approximately 1:1 ratio of male (50.7%) and female COVID-19 patients was found, with an overall median age of 57.0 years. All patients were community-acquired cases. Fever (91.7%), cough (75.0%), fatigue (75.0%), and gastrointestinal symptoms (39.6%) were the most common clinical manifestations, whereas hypertension (30.0%) and diabetes mellitus (12.1%) were the most common comorbidities. Drug hypersensitivity (11.4%) and urticaria (1.4%) were self-reported by several patients. Asthma or other allergic diseases were not reported by any of the patients. Chronic obstructive pulmonary disease (COPD, 1.4%) patients and current smokers (1.4%) were rare. Bilateral ground-glass or patchy opacity (89.6%) was the most common sign of radiological finding. Lymphopenia (75.4%) and eosinopenia (52.9%) were observed in most patients. Blood eosinophil counts correlate positively with lymphocyte counts in severe (r = .486, P < .001) and nonsevere (r = .469, P < .001) patients after hospital admission. Significantly higher levels of D-dimer, C-reactive protein, and procalcitonin were associated with severe patients compared to nonsevere patients (all P < .001). CONCLUSION: Detailed clinical investigation of 140 hospitalized COVID-19 cases suggests eosinopenia together with lymphopenia may be a potential indicator for diagnosis. Allergic diseases, asthma, and COPD are not risk factors for SARS-CoV-2 infection. Older age, high number of comorbidities, and more prominent laboratory abnormalities were associated with severe patients.