Strengthening container shipping network connectivity during COVID-19: A graph theory approach.

A container shipping network connects coastal countries with each other and facilitates most of the world merchandise trade. Reliable maritime connectivity ensures the availability of commodities and economic growth. The global spread of COVID-19 has led to port failures and service cancellations, resulting in decreased connectivity level of container ports. To mitigate the impact of the pandemic, a graph theory approach is proposed to strength the container shipping network connectivity by considering topology and the possibility of opening new shipping links between ports. It is designed to maximize network connectivity with limited addable routes. The network connectivity is measured by algebraic connectivity, and the possibility of opening new shipping links is estimated by an extended gravity model. A heuristic algorithm based on Fiedler vector is introduced to obtain the optimal solutions. The performance of the proposed model and algorithm are verified by testing on a real-world container shipping network based on the Alphaliner database. Experimental results illustrate that the presented model is efficient and effective for strengthening the connectivity. Policy makers can refer to the suggested optimal shipping links to facilitate better shipping network connectivity in the context of the COVID-19 pandemic.

A case-case study on the effect of primary and booster immunization with China-produced COVID-19 vaccines on prevention of pneumonia and viral load among vaccinated persons infected by Delta and Omicron variants.

Using a three-prefecture, two-variant COVID-19 outbreak in Henan province in January 2022, we evaluated the associations of primary and booster immunization with China-produced COVID-19 vaccines and COVID-19 pneumonia and SARS-CoV-2 viral load among persons infected by Delta or Omicron variant. We obtained demographic, clinical, vaccination, and multiple Ct values of infections ≥3 years of age. Vaccination status was either primary series ≥180 days prior to infection; primary series <180 days prior to infection, or booster dose recipient. We used logistic regression to determine odds ratios (OR) of Delta and Omicron COVID-19 pneumonia by vaccination status. We analysed minimum Ct values by vaccination status, age, and variant. Of 826 eligible cases, 405 were Delta and 421 were Omicron cases; 48.9% of Delta and 19.0% of Omicron cases had COVID-19 pneumonia. Compared with full primary vaccination ≥180 days before infection, the aOR of pneumonia was 0.48 among those completing primary vaccination <180 days and 0.18 among booster recipients among these Delta infections. Among Omicron infections, the corresponding aOR was 0.34 among those completing primary vaccination <180 days. There were too few (ten) Omicron cases among booster dose recipients to calculate a reliable OR. There were no differences in minimum Ct values by vaccination status among the 356 Delta cases or 70 Omicron cases. COVID-19 pneumonia was less common among Omicron cases than Delta cases. Full primary vaccination reduced pneumonia effectively for 6 months; boosting six months after primary vaccination resulted in further reduction. We recommend accelerating the pace of booster dose administration.

Comparison and Analysis on the Existing Single-Herbal Strategies against Viral Myocarditis.

Purpose: Herbal medicine is one of crucial symbols of Chinese national medicine. Investigation on molecular responses of different herbal strategies against viral myocarditis is immeasurably conducive to targeting drug development in the current international absence of miracle treatment. Methods: Literature retrieval platforms were applied in the collection of existing empirical evidences for viral myocarditis-related single-herbal strategies. SwissTargetPrediction, Metascape, and Discovery Studio coordinating with multidatabases investigated underlying target genes, interactive proteins, and docking molecules in turn. Results: Six single-herbal medicines consisting of Huangqi (Hedysarum Multijugum Maxim), Yuganzi (Phyllanthi Fructus), Kushen (Sophorae Flavescentis Radix), Jianghuang (Curcumaelongae Rhizoma), Chaihu (Radix Bupleuri), and Jixueteng (Spatholobus Suberectus Dunn) meet the requirement. There were 11 overlapped and 73 unique natural components detected in these herbs. SLC6A2, SLC6A4, NOS2, PPARA, PPARG, ACHE, CYP2C19, CYP51A1, and CHRM2 were equally targeted by six herbs and identified as viral myocarditis-associated symbols. MCODE algorithm exposed the hub role of SRC and EGFR in strategies without Jianghuang. Subsequently, we learned intermolecular interactions of herbal components and their targeting heart-tissue-specific CHRM2, FABP3, TNNC1, TNNI3, TNNT2, and SCN5A and cardiac-myocytes-specific IL6, MMP1, and PLAT coupled with viral myocarditis. Ten interactive characteristics such as π-alkyl and van der Waals were modeled in which ARG111, LYS253, ILE114, and VAL11 on cardiac troponin (TNNC1-TNNI3-TNNT2) and ARG208, ASN106, and ALA258 on MMP1 fulfilled potential communicating anchor with ellagic acid, 5α, 9α-dihydroxymatrine, and leachianone g via hydrogen bond and hydrophobic interaction, respectively. Conclusions: The comprehensive outcomes uncover differences and linkages between six herbs against viral myocarditis through component and target analysis, fostering development of drugs.

Mask-wearing intentions on airplanes during COVID-19 - Application of theory of planned behavior model.

The COVID-19 pandemic has devastated the air transport industry, forcing airlines to take measures to ensure the safety of passengers and crewmembers. Among the many protective measures, mask mandate onboard the airplane is an important one, but travelers' mask-wearing intentions during flight remain uninvestigated especially in the US where mask use is a topic of on-going debate. This study focused on the mask use of airline passengers when they fly during COVID-19, using the theory of planned behavior (TPB) model to examine the relationship between nine predicting factors and the mask-wearing intention in the aircraft cabin. A survey instrument was developed to collect data from 1124 air travelers on Amazon Mechanical Turk (MTurk), and the data was statistically analyzed using structural equation modeling and logistic regression. Results showed that attitude, descriptive norms, risk avoidance, and information seeking significantly influenced the travelers' intention to wear a mask during flight in COVID-19. Group analysis further indicated that the four factors influenced mask-wearing intentions differently on young, middle-aged, and senior travelers. It was also found that demographic and travel characteristics including age, education, income, and travel frequency can be used to predict if the airline passenger was willing to pay a large amount to switch to airlines that adopted different mask policies during COVID-19. The findings of this study fill the research gap of air travelers' intentions to wear a mask when flying during a global pandemic and provide recommendations for mask-wearing policies to help the air transport industry recover from COVID-19.

Mask-wearing intentions on airplanes during COVID-19 – Application of theory of planned behavior model

The COVID-19 pandemic has devastated the air transport industry, forcing airlines to take measures to ensure the safety of passengers and crewmembers. Among the many protective measures, mask mandate onboard the airplane is an important one, but travelers' mask-wearing intentions during flight remain uninvestigated especially in the US where mask use is a topic of on-going debate. This study focused on the mask use of airline passengers when they fly during COVID-19, using the theory of planned behavior (TPB) model to examine the relationship between nine predicting factors and the mask-wearing intention in the aircraft cabin. A survey instrument was developed to collect data from 1124 air travelers on Amazon Mechanical Turk (MTurk), and the data was statistically analyzed using structural equation modeling and logistic regression. Results showed that attitude, descriptive norms, risk avoidance, and information seeking significantly influenced the travelers' intention to wear a mask during flight in COVID-19. Group analysis further indicated that the four factors influenced mask-wearing intentions differently on young, middle-aged, and senior travelers. It was also found that demographic and travel characteristics including age, education, income, and travel frequency can be used to predict if the airline passenger was willing to pay a large amount to switch to airlines that adopted different mask policies during COVID-19. The findings of this study fill the research gap of air travelers’ intentions to wear a mask when flying during a global pandemic and provide recommendations for mask-wearing policies to help the air transport industry recover from COVID-19.

Intelligent disinfection robots assist medical institutions in controlling environmental surface disinfection

In recent years, noncontact crewless operations have become prominent in the field of environmental disinfection. Robots that automatically disinfect the air and surfaces of hospital environments can help reduce the human resources spent on environmental cleaning and disinfection and minimize the risk of occupational exposure for staff. These robots also facilitate informatized management of environmental disinfection, reduce costs, and increase the efficiency of disinfection efforts.

Multiplex quantitative detection of SARS-CoV-2 specific IgG and IgM antibodies based on DNA-assisted nanopore sensing.

The coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread into a global pandemic. Early and accurate diagnosis and quarantine remain the most effective mitigation strategy. Although reverse transcriptase polymerase chain reaction (RT-qPCR) is the gold standard for COVID-19 diagnosis, recent studies suggest that nucleic acids were undetectable in a significant number of cases with clinical features of COVID-19. Serologic assays that detect human antibodies to SARS-CoV-2 serve as a complementary method to diagnose these cases, as well as to identify asymptomatic cases and qualified convalescent serum donors. However, commercially available enzyme-linked immunosorbent assays (ELISA) are laborious and non-quantitative, while point-of-care assays suffer from low detection accuracy. To provide a serologic assay with high performance and portability for potential point-of-care applications, we developed DNA-assisted nanopore sensing for quantification of SARS-CoV-2 related antibodies in human serum. Different DNA structures were used as detection reporters for multiplex quantification of immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies against the nucleocapsid protein of SARS-CoV-2 in serum specimens from patients with conformed or suspected infection. Comparing to a clinically used point-of-care assay and an ELISA assay, our technology can reliably quantify SARS-CoV-2 antibodies with higher accuracy, large dynamic range, and potential for assay automation.

Anatomical and Pathological Observation and Analysis of SARS and COVID-19: Microthrombosis Is the Main Cause of Death.

The spread of the coronavirus (SARS-CoV-2, COVID-19 for short) has caused a large number of deaths around the world. We summarized the data reported in the past few months and emphasized that the main causes of death of COVID-19 patients are DAD (Diffuse Alveolar Damage) and DIC (Disseminated intravascular coagulation). Microthrombosis is a prominent clinical feature of COVID-19, and 91.3% of dead patients had microthrombosis.Endothelial damage caused by SARS-CoV-2 cell invasion and subsequent host response disorders involving inflammation and coagulation pathways play a key role in the progression of severe COVID-19. Microvascular thrombosis may lead to microcirculation disorders and multiple organ failure lead to death.The characteristic pathological changes of DAD include alveolar epithelial and vascular endothelial injury, increased alveolar membrane permeability, large numbers of neutrophil infiltration, alveolar hyaline membrane formation, and hypoxemia and respiratory distress as the main clinical manifestations. DAD leads to ARDS in COVID-19 patients. DIC is a syndrome characterized by the activation of systemic intravascular coagulation, which leads to extensive fibrin deposition in the blood. Its occurrence and development begin with the expression of tissue factor and interact with physiological anticoagulation pathways. The down-regulation of fibrin and the impaired fibrinolysis together lead to extensive fibrin deposition.DIC is described as a decrease in the number of platelets and an increase in fibrin degradation products, such as D-dimer and low fibrinogen. The formation of microthrombus leads to the disturbance of microcirculation, which in turn leads to the death of the patient. However, the best prevention and treatment of COVID-19 microthrombosis is still uncertain.This review discusses the latest findings of basic and clinical research on COVID-19-related microthrombosis, and then we proposed the theory of microcirculation perfusion bundle therapy to explore effective methods for preventing and treating COVID-19-related microthrombosis. Further research is urgently needed to clarify how SARS-CoV-2 infection causes thrombotic complications, and how it affects the course and severity of the disease. To cultivate a more comprehensive understanding of the underlying mechanism of this disease. Raise awareness of the importance of preventing and treating microthrombosis in patients with COVID-19.

Clinical Characteristics and Outcomes of Severe and Critical Patients With 2019 Novel Coronavirus Disease (COVID-19) in Wenzhou: A Retrospective Study.

Information about severe cases of 2019 novel coronavirus disease (COVID-19) infection is scarce. The aim of this study was to report the clinical characteristics and outcomes of severe and critical patients with confirmed COVID-19 infection in Wenzhou city. In this single-centered, retrospective cohort study, we consecutively enrolled 37 RT-PCR confirmed positive severe or critical patients from January 28 to February 16, 2020 in a tertiary hospital. Outcomes were followed up until 28-day mortality. Fifteen severe and 22 critical adult patients with the COVID-19 infection were included. Twenty-six (68.4%) were men. Echocardiography data results suggest that normal or increased cardiac output and diastolic dysfunction are the most common manifestations. Compared with severe patients, critical patients were older, more likely to exhibit low platelet counts and high blood urea nitrogen, and were in hospital for longer. Most patients had organ dysfunction during hospitalization, including 11 (29.7%) with ARDS, 8 (21.6%) with acute kidney injury, 17 (45.9%) with acute cardiac injury, and 33 (89.2%) with acute liver dysfunction. Eighteen (48.6%) patients were treated with high-flow ventilation, 9 (13.8%) with non-invasive ventilation, 10 (15.4%) with invasive mechanical ventilation, 7 (18.9%) with prone position ventilation, 6 (16.2%) with extracorporeal membrane oxygenation (ECMO), and 3 (8.1%) with renal replacement therapy. Only 1 (2.7%) patient had died in the 28-day follow up in our study. All patients had bilateral infiltrates on their chest CT scan. Twenty-one (32.3%) patients presented ground glass opacity (GGO) with critical patients more localized in the periphery and the center. The mortality of critical patients with the COVID-19 infection is low in our study. Cardiac function was enhanced in the early stage and less likely to develop into acute cardiac injury, but most patients suffered with acute liver injury. The CT imaging presentations of COVID-19 in critical patients were more likely with consolidation and bilateral lung involvement.

The mental health of frontline and non-frontline medical workers during the coronavirus disease 2019 (COVID-19) outbreak in China: A case-control study.

BACKGROUND AND OBJECTIVE: Coronavirus disease 2019 (COVID-19) is a new infectious disease with high transmissibility and morbidity. It has caused substantial mental distress to medical professionals. We aimed to compare the psychological impact of the COVID-19 outbreak between frontline and non-frontline medical workers in China. METHODS: This case-control study recruited 1173 frontline and 1173 age- and sex-matched non-frontline medical workers during the COVID-19 outbreak (February 11 to 26, 2020). A set of online questionnaires were used to measure mental problems (i.e., anxiety, insomnia, and depressive symptoms), and help-seeking behavior and treatment for these mental problems. RESULTS: Frontline medical workers had higher rates of any mental problem (52.6% vs. 34.0%, adjusted OR=1.88, 95% CI=1.57-2.25), anxiety symptoms (15.7% vs. 7.4%, adjusted OR=1.95, 95% CI=1.46-2.61), depressed mood (marginally insignificant; 14.3% vs. 10.1%, adjusted OR=1.32, 95% CI=0.99-1.76) and insomnia (47.8% vs. 29.1%, adjusted OR=1.96, 95% CI=1.63-2.36) than non-frontline medical workers. No significant difference was observed in terms of suicidal ideation (12.0% vs. 9.0%, adjusted OR=1.25, 95% CI=0.92-1.71), help-seeking (4.5% vs. 4.5%, adjusted OR=1.00, 95% CI=0.53-1.87) or treatment (3.4% vs. 2.3%, adjusted OR=1.38, 95% CI=0.54-3.52) for mental problems. LIMITATIONS: The case-control nature of the data precludes causal inferences, and there is a possibility of bias related to self-reports. CONCLUSIONS: Frontline medical workers had more mental problems but comparable help-seeking behaviors and treatment for these problems than non-frontline medical workers. These findings highlight the timely mental support and intervention for medical workers, especially for those on the frontline.