A grid management system for COVID-19 antigen detection based on image recognition

Objective: To develop a SARS-CoV-2 antigen detection management system for Chinese residents under community grid management, which is supported by "health information technology" and "neural network image recognition", so as to give full play to the advantages of "grid management". This system is applied to the normalized prevention and control of COVID-19 epidemic. Method(s): The model of image recognition algorithm was built based on deep learning and convolution neural network (CNN) artificial intelligence algorithm. The improved Canny edge detection algorithm was used to monitor and locate the image edge, and then the image segmentation and judgment value calculation were completed according to projection method. The system construction was completed combing with the grid number design. Result(s): The proposed method had been tested and showed the accuracy of the algorithm. With a certain robustness, the algorithm error was proved to be small. Based on the image recognition algorithm model, the development of SARS-CoV-2 antigen detection management system covering user login, paper-strip test image upload, paper-strip test management, grid management, grid warning and regional traffic management was completed. Conclusion(s): Antigen detection is an important supplementary means of COVID-19 epidemic prevention and control in the new stage. The SARS-CoV-2 antigen detection management system for Chinese residents under community grid managemen based on image recognition enables mobile communication devices to recognize the image of SARS-CoV-2 antigen detection results, which is helpful to form a grid management mode for the epidemic and improve the management framework of epidemic monitoring, detection, early warning and prevention and control.Copyright © 2023 The Authors

Income and Wealth Inequality in Asia and the Pacific: Trends, Causes, and Policy Remedies

The Asia–Pacific region's rapid growth and poverty reduction in recent decades have been accompanied by rising income and wealth inequality. Technological progress, globalization, deregulation and market-oriented reform, and financialization have generated many new opportunities, but rewarded capital more than labor, benefited skilled workers more than the unskilled, widened spatial inequality, and produced a growing number of the superrich. For some countries, population aging has also contributed to rising inequality. The present paper provides an update on recent trends of income and wealth inequality in the Asia–Pacific region, examines causes behind rising inequality, and discusses policy actions needed to tackle inequality. It also assesses how the COVID-19 has likely worsened inequality in the region. © 2022 Japan Center for Economic Research.

Transmission Dynamics and Quarantine Control of COVID-19 in Cluster Community

Coronavirus Disease 2019 (COVID-19) is a zoonotic illness which has spread rapidly and widely in past two years and was identified as a global pandemic by the World Health Organization (WHO). The pandemic to date has been characterized by ongoing cluster community transmission. Quarantine intervention to prevent and control the transmission is expected to have a substantial impact on delaying the growth and mitigating the size of the epidemic. To our best knowledge, this study is among the initial efforts to analyze the interplay between transmission dynamics and quarantine intervention of the COVID-19 outbreak in a cluster community. In the chapter, we propose a novel Transmission-Quarantine epidemiological model by non-linear ordinary differential equations system. With the use of detailed epidemiologic data from the Cruise ship “Diamond Princess,” we design a Transmission-Quarantine work-flow to determine the optimal case-specific parameters and validate the proposed model by comparing the simulated curve with the real data. Firstly, we apply a general SEIR-type epidemic model to study the transmission dynamics of COVID-19 without quarantine intervention and present the analytic and simulation results for the epidemiological parameters such as the basic reproduction number, the maximal scale of infectious cases, the instant number of recovered cases, the popularity level, and the final scope of the epidemic of COVID-19. Secondly, we adopt the proposed Transmission-Quarantine interplay model to predict the varying trend of COVID-19 with quarantine intervention and compare the transmission dynamics with and without quarantine to illustrate the effectiveness of the quarantine measure, which indicates that with quarantine intervention, the number of infectious cases in 7 days decreases by about 60%, compared with the scenario of no intervention. Finally, we conduct sensitivity analysis to simulate the impacts of different parameters and different quarantine measures and identify the optimal quarantine strategy that can be used by the decision makers to achieve the maximal protection of population with the minimal interruption of economic and social development. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Mask or No Mask during the COVID-19 Pandemic: A Game-Theoretic Approach

Wearing a mask as one of the crucial non-pharmaceutical interventions has demonstrated to be effective in the battle against the COVID-19 pandemic. The implementation of face coverings for the public remains controversial and still faces some challenges. Whether or not to wear the mask could be a complex decision-making processing, involving the trade-offs between self-interest and collective interest among multiple stakeholders. In the literature, there is a lack of quantitative analysis for strategic mask-wearing decisions during the pandemic. This paper fills the gap by studying a game-theoretic model on wearing the mask considering conflicting interests. Using a susceptible-infected-susceptible (SIS) model, we consider the players as either susceptible or infectious, characterized by homogeneous preferences within the group but heterogeneous preferences between groups. Then we propose a game-theoretic framework to model how both susceptible and infectious players make their decisions. We implement one-way sensitivity analyses to examine how the equilibrium solutions are sensitive to changes in the model parameters. The proposed game model shows that susceptible player is more likely to wear face masks compared to infectious player, when the likelihood or the cost of infection is large. Decreasing the cost of wearing masks or increasing the mask efficacy could help mitigate the reluctance of mask wearing. This paper provides insights on population mask-wearing behaviors, which can support policy makers to design regulations and incentives. © 2022 IISE Annual Conference and Expo 2022. All rights reserved.

Income and Wealth Inequality in Asia and the Pacific: Trends, Causes, and Policy Remedies

The Asia–Pacific region's rapid growth and poverty reduction in recent decades have been accompanied by rising income and wealth inequality. Technological progress, globalization, deregulation and market-oriented reform, and financialization have generated many new opportunities, but rewarded capital more than labor, benefited skilled workers more than the unskilled, widened spatial inequality, and produced a growing number of the superrich. For some countries, population aging has also contributed to rising inequality. The present paper provides an update on recent trends of income and wealth inequality in the Asia–Pacific region, examines causes behind rising inequality, and discusses policy actions needed to tackle inequality. It also assesses how the COVID-19 has likely worsened inequality in the region. © 2022 Japan Center for Economic Research.

Influence of COVID-19 outbreak on changing buying behaviors: Chinese consumer's growing concerns over food safety

The outbreak of COVID-19 in China has caused Chinese consumers to question the hidden danger of food safety after their experience with previous epidemics like SARS, H1N1, and swine flu. It is feared that the virus could spread from animal to human, similar to avian and swine influenza. They are also concerned that food purchased from supermarkets and farmer's markets could be infected due to improper control measures. This study reviews the potential impact of the COVID- 19 pandemic on Chinese consumers' growing health, ethical, and food safety concerns, which could influence their purchasing attitudes and intention to buy food. The implications of this research are to suggest to marketers the long- term behavioral and attitude shifts we could witness from the COVID- 19 pandemic is a primary concern that needs to be given attention. In order to study the effects of COVID-19 on consumers' attitudes, an online questionnaire was administered in this study. Participants are Chinese consumers from different areas who have different ages and educational backgrounds. This study applies regression analysis to figure out the relationships between the independent variables and dependent variables. The results show that, during the pandemic of COVID- 19, food safety concerns and health consciousness changed the purchasing behaviors of Chinese consumers. © Peter Lang GmbH Internationaler Verlag der Wissenschaften Berlin 2021. All rights reserved.

Stay Home or Not? Modeling Individuals' Decisions During the COVID-19 Pandemic

During the COVID-19 pandemic, staying home proved to be an effective way to mitigate the spread of the virus. Stay-at-home orders and guidelines were issued by governments across the globe and were followed by a large portion of the population in the early stages of the outbreak when there was a lack of COVID-specific medical knowledge. The decision of whether to stay home came with many trade-offs, such as risking personal exposure to the virus when leaving home or facing financial and mental health burdens when remaining home. In this research, we study how individuals make strategic decisions to balance these conflicting outcomes. We present a model to study individuals' decision making based on decision and prospect theory, and we conduct sensitivity analysis to study the fluctuations in optimal strategies when there are changes made to the model's parameters. A Monte Carlo simulation is implemented to further study the performance of our model, and we compare our simulation results with real data that captures individuals' stay-at-home decisions. Overall, this research models and analyzes the behaviors of individuals during the COVID-19 pandemic and can help support decision making regarding control measures and policy development when public health emergencies appear in the future.

Coronavirus disease 2019 combined with venous thromboembolism: Clinical features and prevention

Objective: To analyze the clinical characteristics and control methods of coronavirus disease 2019 (COVID-19) complicated with venous thromboembolism(VTE), and to provide scientific basis for disease prevention, diagnosis and treatment. Methods: We retrospectively studied the cases of COVID-19 complicated with VTE in Renmin Hospital of Wuhan University from January 30, 2020 to March 19, 2020, and their clinical features, results of exmaninations, treatment methods, complications, and prognosis were reviewed. Results: Among the 1 448 COVID-19 patients, 17(1.17%) were VTE positive, 60-69 years old patients were more common. The main clinical types were critical (64.7%) and severe (35.7%) types. The main clinical symptoms were lower extremity swelling (70.6%) and pain (35.7%);58.8% of the patients had a history of high risk factors related to VTE. Most VTE patients were peripheral (58.8%) and involved bilateral limbs (41.2%). The proportion of neutrophils, D-dimer and fibrin degradation products at the last examination were lower than those on admission to the hospital, while the total number and proportion of lymphocytes were higher. Of the 17 VTE cases, 64.7% received venous catheterization, 58.8% received endotracheal intubation or tracheotomy, and 2 patients received extracorporeal membrane oxygenation (ECMO). The rate of bleeding was as high as 53%, and the risk of cardiovascular and cerebrovascular accidents was very high;the prognosis of the patients was poor, and the mortality rate was 23.5%. The cure rate was 17.6%, and the improvement rate was 47.1%. Two patients were still in critically ill. Conclusion: Venous thromboembolism was common in elderly COVID-19 patients with severe types and critical types. Most patients were male and characterized by atypical symptoms, and the early active VTE risk assessment and prevention procedures should be adopted. The risk for bleeding and cardiovascular/cerebrovascular accidents was high, although most cases had good outcomes after active treatment. © 2021, Editorial Board of Medical Journal of Wuhan University. All right reserved.

Detection of Novel Coronavirus Pneumonia Based on CT Image with Convolutional Neural Network Processing

To improve the ability to distinguish novel coronavirus pneumonia from common pneumonia and assist medical staff in chest CT examination of pneumonia patients, a detection method using convolution neural network and CT image based on artificial intelligence image analysis was proposed. First, a convolution neural network model was built, and the influence of model depth on detection results was evaluated to select the best network structure. Second, a tabu genetic algorithm was proposed to obtain the optimal hyper-parameter combination of the network model and to enhance the performance of the model. Finally, the best network model was employed to distinguish novel coronavirus pneumonia from common pneumonia. Experimental results show that the accuracy, MCC, and F1Score of the proposed detection algorithm are 93.89%, 93.32% and 91.40%, respectively, which has higher detection accuracy than other algorithms. © 2021, Acta Metrologica Sinica Press. All right reserved.

Advanced “lab-on-a-chip” to detect viruses – Current challenges and future perspectives

Massive viral outbreaks draw attention to viruses that have not been thoroughly studied or understood. In recent decades, microfluidic chips, known as “lab-on-a-chip”, appears as a promising tool for the detection of viruses. Here, we review the development of microfluidic chips that could be used in response to viral detection, specifically for viruses involved in more recent outbreaks. The advantages as well as the disadvantages of microfluidic systems are discussed and analyzed. We also propose ideas for future development of these microfluidic chips and we expect this advanced technology to be used in the future for viral outbreaks.