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1.
Zhonghua Er Ke Za Zhi ; 60(11): 1168-1171, 2022 Nov 02.
Article in Chinese | MEDLINE | ID: covidwho-2099942

ABSTRACT

Objective: To summarize the application experience and the therapeutic effect of Nirmatrelvir-Ritonavir (trade name: Paxlovid) for COVID-19 in children. Methods: A retrospective analysis was performed on the clinical data, including collecting the clinical manifestations and clinical outcomes, dynamically monitoring the blood routine, hepatic and renal function and SARS-CoV-2 nucleic acid results, and observing the related side effects during the treatment, etc, of 3 cases with COVID-19 treated with Paxlovid admitted to Shanghai Children's Hospital (designated referral hospital for SARS-CoV-2 infection in Shanghai) from May 1st to June 1st, 2022. Results: The 3 cases were 12, 14, 17 years of age, among which 2 cases were males, 1 case was female. All 3 cases were mild cases with underlying diseases and risk of developing into severe COVID-19, with symptoms of high fever, sore throat and dry cough. The treatment of Paxlovid at 3rd day of symptom onset contributed to the symptom-free after 1-2 days and negative results of SARS-CoV-2 nucleic acid after 2-4 days. All patients had no adverse manifestations of gastrointestinal tract and nervous system but a case had little skin rashes, which recovered after the withdrawal of Paxlovid. Three cases had normal hepatic and renal function during the Paxlovid treatment. At 3 months after discharge, no clinical manifestations of post-COVID syndrome were found in all 3 cases. Conclusion: Paxlovid was effective and relatively safe in the treatment of 3 children with COVID-19.


Subject(s)
COVID-19 , Nucleic Acids , Child , Male , Humans , Female , SARS-CoV-2 , Ritonavir/therapeutic use , Retrospective Studies , China
2.
Applied Sciences (Switzerland) ; 12(18), 2022.
Article in English | Scopus | ID: covidwho-2055127

ABSTRACT

Background: Comprehensive and evidence-based countermeasures against emerging infectious diseases have become increasingly important in recent years. COVID-19 and many other infectious diseases are spread by human movement and contact, but complex transportation networks in the 21st century make it difficult to predict disease spread in rapidly changing situations. It is especially challenging to estimate the network of infection transmission in countries where traffic and human movement data infrastructure is not yet developed. Methods: In this study, we devised a method utilizing an ordinary and partial differential equations-based mathematical model and a modified mathematical optimization method to estimate the network of transmission of COVID-19 from the time series data of its infection and applied it to determine its spread across areas in Japan. Furthermore, utilizing the estimated human mobility network, we predicted the spread of infection using the Tokyo Olympics as a model. Findings: We incorporated the effects of soft lockdowns, such as the declaration of a state of emergency, and changes in the infection network due to government-sponsored travel promotion, and revealed that the estimated effective distance captured human mobility changing dynamically in the different stages of the pandemic. The model predicted that the Tokyo Olympic and Paralympic Games would increase the number of infected cases in the host prefectures by up to 80%. Interpretation: The models used in this study are available online, and our data-driven infection network models are scalable, whether it be at the level of a city, town, country, or continent, and applicable anywhere in the world, as long as the time-series data of infections per region is available. These estimations of effective distance and the depiction of infectious disease networks based on actual infection data are expected to be useful in devising data-driven countermeasures against emerging infectious diseases worldwide. © 2022 by the authors.

3.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2009587

ABSTRACT

Background: The utilization of virtual second opinions in oncology has increased considerably in the last decade, driven by the increased complexity of care and desire for expert opinion, improved technologies in telemedicine, and the acceleration of virtual services due to the Covid-19 pandemic. Therefore, it is important to further understand the patient populations that currently use virtual second opinion programs and to measure their effectiveness. Virtual second opinion programs provide a platform for patients to submit their medical history and questions regarding their condition to remote specialists who then render their opinions on diagnosis and management. Currently there is a paucity of research on the types of patient populations that seek second opinions and the outcomes of these rendered opinions. Here we describe the patient characteristics and changes in management associated with utilization of a virtual second opinion service at an academic medical center. Methods: In this IRB-approved retrospective review, we identified 657 cancer patients that utilized a virtual digital health platform to engage in second opinions at Stanford Healthcare. Patient demographics, cancer staging, site of origin, and prior therapeutic and surgical history were collected. Physician opinions rendered were self-classified into “major change in treatment”, “minor change in treatment”, or “no change in treatment.”. Results: The majority of patients who utilized the virtual second-opinion platform had a diagnosis late-stage cancer (with 77.2% at Stage III or IV). Breast cancer was the most common primary tumor site (24.7% of patients) followed by GI (21.9%) and GU malignancies (14.0%). Patients diagnosed with dermatological (4.4%), head and neck (3.3%), and neurological (3.2%) malignancies were least common. Physicians providing the virtual second-opinion were primarily medical oncologists (67.6%), followed by gynecologists (6.8%), urologists (5.2%), radiation oncologists (5.0%), and surgical oncologists (4.4%). Physicians self-reported that in more than half of cases reviewed (53.8%) a minor or major treatment change was recommended. Conclusions: This study showed that patients access second opinion platforms at late stage of cancer disease progression. With treatment changes recommended for more than half of the cases, virtual second opinion programs can potentially have a significant impact on cancer care. Patient satisfaction and clinical outcomes from virtual second opinion programs is an area of on-going research.

4.
Asian Journal of Social Psychology ; : No Pagination Specified, 2022.
Article in English | APA PsycInfo | ID: covidwho-1932263

ABSTRACT

Violence against healthcare professionals is a serious but understudied global problem and one that lacks evidence-based solutions. The current research offers a novel explanation and intervention for addressing this issue: We propose that low feelings of control among patients and their family members play an important role in shaping doctor-patient relationships. To regain a sense of control, we suggest that patients attribute responsibility to doctors for their suffering, which may in turn lead to aggressive behavioural intentions against one's doctors. We conducted three studies to understand whether individuals with low perceived control blame doctors more, and whether threats to their sense of control cause participants to attribute more responsibility to doctors. Study 1 found that feelings of lack of control were an important predictor of attributing responsibility for negative illness-related incidents to doctors in a manner consistent with blame. Study 2 specified that the chaotic and unpredictable nature of illness, and not just its negative valence, is what drives attributions of increased responsibility to doctors. Study 3, which utilized a field setting in hospitals, found that an experimental intervention to increase feelings of control decreased frustration against (Study 3a/3b) and intention to harm doctors (Study 3b). These findings suggest that increasing feelings of control among patients can improve patient-doctor relationships. We also discuss the role of control and scapegoating during the COVID-19 pandemic. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

5.
Information Technology & People ; : 31, 2022.
Article in English | Web of Science | ID: covidwho-1868481

ABSTRACT

Purpose Virtual reality (VR) technology is a potential tool for tourism marketers to maintain the attractiveness of their destinations and recover from the COVID-19 pandemic. However, the effectiveness of VR technology in motivating potential tourists' visit intention under lockdown conditions remains unknown. An integrated model based on the experience economy framework and mood management theory was, therefore, used to explain how tourists' VR experiences affect their mood management processes and subsequent behaviors. This research also examined how perceived travel risk influenced the relationship between mood management processes and future decisions. Design/methodology/approach This study used a cross-sectional design based on a sample collected from a Chinese survey company, Sojump. The author surveyed 285 respondents who had experienced VR tourism activities during the COVID-19 pandemic. The research model was tested using partial least squares-structural equation modeling. Findings The results demonstrated that the four dimensions of VR experiences differently affected mood management processes, while perceived travel risk differently moderated the influence of mood management processes on visit intention and VR stickiness. This provides insights for tourism marketers to adapt to the current tourism environment and develop recovery strategies. Originality/value In response to gaps in the literature, this research examined the effectiveness of VR technology in driving tourists' visit intention during the COVID-19 pandemic, providing insights for tourism marketers to successfully implement VR tourism and plan timely recovery strategies.

6.
Chinese Pharmacological Bulletin ; 36(9):1309-1316, 2020.
Article in Chinese | EMBASE | ID: covidwho-1863006

ABSTRACT

Aim To explore the active compound of Maxingganshi decoction in treatment of novel coronavirus pneumonia(COVID-19). Methods With the help of TCMSP database, the chemical components and action targets of ephedra, almond, licorice, and gypsum in Maxingganshi decoction were searched, and then a C-T network, protein interaction analysis, GO functional enrichment analysis, and KEGG pathway enrichment were constructed. Analysis was performed to predict its mechanism of action. Results A total of 120 compounds in Maxingganshi decoction corresponded to 222 targets. PTGS2, ESR1, PPARG, AR, NOS2, NCOA2 acted on PI3K-Akt signaling pathway, TNF signaling pathway, IL-17 signaling pathway, T cell receptor signaling pathways, etc. The results of molecular docking showed that the affinity of quercetin, kaempferol, glabridin and other core compounds was similar to recommended drugs in treatment of COVID-19. Conclusions The active compounds of Maxingganshi decoction can target multiple pathways to achieve the therapeutic effect of COVID-19.

7.
35th AAAI Conference on Artificial Intelligence, AAAI 2021 ; 6A:4821-4829, 2021.
Article in English | Scopus | ID: covidwho-1857257

ABSTRACT

The COVID-19 pandemic has spread globally for several months. Because its transmissibility and high pathogenicity seriously threaten people’s lives, it is crucial to accurately and quickly detect COVID-19 infection. Many recent studies have shown that deep learning (DL) based solutions can help detect COVID-19 based on chest CT scans. However, most existing work focuses on 2D datasets, which may result in low quality models as the real CT scans are 3D images. Besides, the reported results span a broad spectrum on different datasets with a relatively unfair comparison. In this paper, we first use three state-of-the-art 3D models (ResNet3D101, DenseNet3D121, and MC3 18) to establish the baseline performance on three publicly available chest CT scan datasets. Then we propose a differentiable neural architecture search (DNAS) framework to automatically search the 3D DL models for 3D chest CT scans classification and use the Gumbel Softmax technique to improve the search efficiency. We further exploit the Class Activation Mapping (CAM) technique on our models to provide the interpretability of the results. The experimental results show that our searched models (CovidNet3D) outperform the baseline human-designed models on three datasets with tens of times smaller model size and higher accuracy. Furthermore, the results also verify that CAM can be well applied in CovidNet3D for COVID-19 datasets to provide interpretability for medical diagnosis. Code: https://github.com/HKBU-HPML/CovidNet3D. Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

8.
Policy and Society ; : 15, 2022.
Article in English | Web of Science | ID: covidwho-1722570

ABSTRACT

The coronavirus disease (COVID-19) pandemic has created tremendous hazards to people worldwide. Incidence, hospitalization, and mortality rates have varied by individual and regional socioeconomic indicators. However, little is known about the indirect social and economic losses following the COVID-19 pandemic and to what extent they have disproportionately affected different groups of people. Building on the traditional conceptualizations of "old" and "new social risks," this article tracks and analyzes the emerging "COVID social risks" in five critical areas: physical health, employment and income, skills and knowledge, care, and social relationships. The article empirically examines to what extent the manifestations of "COVID social risks" describe the makings of a new class divide in South Korea, Hong Kong, and Taiwan. Finally, this article discusses whether "COVID social risks" present a temporary or lasting phenomenon and to what extent interactions with processes of digitization and de-globalization are likely to produce similar problem pressures for East Asian governments amid future crises. East Asian governments should facilitate individuals' ability to absorb "COVID social risks" and institutionalize a new welfare policy settlement that emphasizes complementarities between the social protection, social investment, and social innovation policy paradigms.

9.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326911

ABSTRACT

Previous work indicated that the nucleocapsid 203 mutation increase the virulence and transmission of the SARS-CoV-2 Alpha variant. However, Delta later outcompeted Alpha and other lineages, promoting a new wave of infections. Delta also possesses a nucleocapsid 203 mutation, R203M. Large-scale epidemiological analyses suggest a synergistic effect of the 203 mutation and the spike L452R mutation, associated with Delta expansion. Viral competition experiments demonstrate the synergistic effect in fitness and infectivity. More importantly, we found that the combination of R203M and L452R brings in a 3.2-fold decrease in neutralizing titers to the neutralizing serum relative to L452R-only virus. R203M/L452R show an increased fitness after the initiation of global vaccination programmes, possibly associated with the enhanced immune evasion. Another rapidly emerging variant Omicron also bears the 203 mutation. Thus, we proposed that nucleocapsid mutations play an essential role for the rise and predominance of variants in concern.

10.
Traditional Medicine and Modern Medicine ; 3(1):71-76, 2020.
Article in English | EMBASE | ID: covidwho-1582955

ABSTRACT

The highly infectious coronavirus disease 2019 (COVID-19) that emerged in Wuhan, China, was caused by a novel strain of coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Subsequently, it was considered as one of the serious potential threats to global public health due to rapid spread worldwide. The purpose of this paper is to describe the characteristics of epidemiology, clinical manifestations, diagnosis, differential diagnosis, and treatment of traditional Chinese medicine and modern medicine in critically ill adults with COVID-19. We searched the related papers published up to April 20, 2020 on the PubMed and the China National Knowledge Infrastructure database. The findings will improve the potential recognition of COVID-19 among clinicians and the general public, and presumably contribute to the reduction of mortality.

11.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ; 2021.
Article in English | Scopus | ID: covidwho-1483754

ABSTRACT

High spatial resolution and broad spatial coverage data on fine particulate matter (PM2.5) are of great significance to estimating the exposure to PM2.5. However, the data is currently very limited worldwide. In addition, the COVID-19 pandemic in China, starting in January 2020, have led to significant variations in the PM2.5 concentrations. To identify the variations and causes of PM2.5 concentrations before and after the COVID-19 pandemic from 23 January to 24 March during 20182020, a geographically weighted regression model with a 1 km spatial resolution covering all of mainland China was developed. The overall R and RMSE values of the model cross validation were 0.91 and 17.19 g/m3, respectively, indicating that the model performed satisfactorily in estimating the PM2.5 values. Then, based on the satellite-based PM2.5 values, the results show that the PM2.5 values fluctuated significantly across mainland China before and after the COVID-19 outbreak. Additionally, the mean PM2.5 values decreased by 5.41 g/m3 in 2020 compared to 2019. In Hubei Province, the mean PM2.5 values increased by 1.85 g/m3 in 2019 compared to 2018, whereas they dramatically decreased by 23.18 g/m3 in 2020 compared to 2019. Finally, the results show that anthropogenic factors were primarily responsible for the variations in the PM2.5 concentrations in Heilongjiang, Jilin, and Liaoning provinces;whereas, both meteorological and anthropogenic factors were responsible for the variations in Hubei, Henan, Anhui, Shandong, and Jiangsu provinces during the study period. These results provide an important reference for the future development of air pollution control policies in China. Author

12.
3rd EAI International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021 ; 388:331-337, 2021.
Article in English | Scopus | ID: covidwho-1446002

ABSTRACT

To investigate the relationship between emotional status and physical activity in adolescents during the epidemic period of Corona Virus Disease 2019. 600 junior and senior high school students from three municipal middle schools were randomly selected as the research objects. The self-evaluation of anxiety and depression and the evaluation of physical activity were carried out in the form of questionnaire survey. A total of 600 questionnaires were put in and 562 were recovered. The scores of SDS and SAS were 49.30 ± 7.02, and 53.42 ± 5.37 respectively. According to different age groups, there was significant difference in SAS among the three groups in different age groups (P <0.05). The total score of PA was (3.24 ± 0.98). According to different age groups, there were significant differences in PA total score, MVPA activities, physical education activities, weekend activities and one week total activities among the three groups (P <0.05). The total score of anxiety was negatively correlated with the total score of PA (r = −0.54, P = 0.024), MVPA (r = −0.38, P = 0.049) and physical education (r = −0.62, P = 0.016), and the total score of one week was negatively correlated (r = −0.44, P = 0.041). During the period of Corona Virus Disease 2019 epidemic, the anxiety level of adolescents increases with age, while the physical activity status decreases gradually, and is negatively correlated with anxiety. It is necessary to strengthen sports activities and protect emotional health in this special period. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

13.
35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence ; 35:4821-4829, 2021.
Article in English | Web of Science | ID: covidwho-1381682

ABSTRACT

The COVID-19 pandemic has spread globally for several months. Because its transmissibility and high pathogenicity seriously threaten people's lives, it is crucial to accurately and quickly detect COVID-19 infection. Many recent studies have shown that deep learning (DL) based solutions can help detect COVID-19 based on chest CT scans. However, most existing work focuses on 2D datasets, which may result in low quality models as the real CT scans are 3D images. Besides, the reported results span a broad spectrum on different datasets with a relatively unfair comparison. In this paper, we first use three state-of-the-art 3D models (ResNet3D101, DenseNet3D121, and MC3 18) to establish the baseline performance on three publicly available chest CT scan datasets. Then we propose a differentiable neural architecture search (DNAS) framework to automatically search the 3D DL models for 3D chest CT scans classification and use the Gumbel Softmax technique to improve the search efficiency. We further exploit the Class Activation Mapping (CAM) technique on our models to provide the interpretability of the results. The experimental results show that our searched models (CovidNet3D) outperform the baseline human-designed models on three datasets with tens of times smaller model size and higher accuracy. Furthermore, the results also verify that CAM can be well applied in CovidNet3D for COVID-19 datasets to provide interpretability for medical diagnosis. Code: https://github.com/HKBU-HPML/CovidNet3D.

14.
Geomatics Natural Hazards & Risk ; 12(1):2023-2047, 2021.
Article in English | Web of Science | ID: covidwho-1341081

ABSTRACT

The novel infectious disease (COVID-19) took only a few weeks from its official inception in December 2019 to become a global pandemic in early 2020. Countries across the world went to lockdown, and various strict measures were implemented to reduce the further spread of the infection. Although, the strict lockdown measures were aimed at stopping the spread of COVID-19, however, Its positive implications were also observed for the environmental conditions across the global regions. The present study attempted to explore the eco-restoration of coastal marine system in response to reduced deposition of atmospheric nitrogen (NO2) emission during the substantial shift in human activities across the global metropolitan cities. Remotely data of NO2 emission were taken from Ozone Monitoring Instrument and the coastal water quality along the marine system was estimated from MODIS-Aqua Level-3 using Semi-Analytic Sediment Model (SASM). The changes in tropospheric NO2 in 2020s were also compared with the long-term average changes over the baseline period 2015 - 2019. A significant reduction in anthropogenic mobility (85 - 90%) has been observed in almost all countries over different places, especially grocery, parks, workplaces, and transit stations. A massive reduction in tropospheric NO2 was detected in Wuhan (53%), Berlin (42%), London (41%), Karachi (40%), Paris (38%), Santiago (35%), and Chennai (34%) during the strict lockdown period of the early 2020 as compared to the last five years. However, after the partial lockdown was lifted, tropospheric NO2 values bounced back and slightly increased over Karachi (6%) and Bremen (12%). For water turbidity, the rate of reduction was found to be the highest along the different coastal regions of the Mediterranean Sea and Black Sea (51%), West Atlantic Ocean (32%), East Atlantic Ocean (29%), and Indian Ocean (21%) from Apr to Jun 2020. The monthly comparison of overland-runoff in 2020 compared to 2019 across the different costal watersheds indicates that the observed decline in turbidity might have been due to the reduced deposition of atmospheric nitrogen. The findings of this study suggest that the recent decline in tropospheric NO2 and water turbidity might be associated with reduced emissions from fossil fuels and road transports followed by COVID-19 forced restrictions in the twenty-first century. The inferences made here highlight the hope of improving the global environmental quality by reducing greenhouse gas emissions using innovative periodic confinement measures on heavy transport and industries while securing public health and socioeconomics.

15.
Chinese Journal of Clinical Infectious Diseases ; 13(6):467-474, 2020.
Article in Chinese | Scopus | ID: covidwho-1143652

ABSTRACT

COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases. © 2020 Chinese Medical Association

16.
Chemistry and Technology of Fuels and Oils ; 2021.
Article in English | Scopus | ID: covidwho-1049676

ABSTRACT

In this study, we have analyzed the impact of COVID-19 on natural gas supply reliability. Natural gas supply reliability is defined as the ability to satisfy the market demand and is determined by both supply-side and demand-side policy. To evaluate the gas supply reliability of the natural gas pipeline system, we have applied the method of gas supply capacity calculation based on the results of the previous gas supply reliability studies. The method combines the unsteady flow hydraulic analysis, simulation of the state transition process, and the forecasting analysis of the demand and consumption. The analysis presents a case study based on the gas pipeline system in China. The analysis results indicate that the COVID-19 consequences will cause a decrease in gas supply reliability. © 2021, Springer Science+Business Media, LLC, part of Springer Nature.

17.
International Journal of Bifurcation and Chaos ; 30(16), 2020.
Article in English | Scopus | ID: covidwho-1015722

ABSTRACT

It has been reported that COVID-19 patients had an increased neutrophil count and a decreased lymphocyte count in the severe phase and neutrophils may contribute to organ damage and mortality. In this paper, we present the bifurcation analysis of a dynamical model for the initial innate system response to pulmonary infection. The model describes the interaction between a pathogen and neutrophilis (also known as polymorphonuclear leukocytes). It is shown that the system undergoes a sequence of bifurcations including subcritical and supercritical Bogdanov-Takens bifurcations, Hopf bifurcation, and degenerate Hopf bifurcation as the parameters vary, and the model exhibits rich dynamics such as the existence of multiple coexistent periodic oscillations, homoclinic orbits, bistability and tristability, etc. Numerical simulations are presented to explain the theoretical results. © 2020 World Scientific Publishing Company.

18.
Zhonghua Yu Fang Yi Xue Za Zhi ; 54(12): 1448-1452, 2020 Dec 06.
Article in Chinese | MEDLINE | ID: covidwho-983952

ABSTRACT

Objective: To analyze the antibody levels and dynamic changes in patients infected with 2019-novel coronavirus(2019-nCoV). Methods: The average age of 72 corona virus disease 2019 (COVID-19) patients was (45.53±16.74)years(median age:47 year), including (44.88±17.09) years(median age:46 year) for 38 males and (46.32±16.52)years (median age:46 year) for 34 females in Loudi City, Hunan Province. There is no significant difference in genders between the severe and mild groups (χ²=0.916, P>0.05). There is a significant difference in the age between the severe and mild groups (F=3.315, P<0.05). The blood samples of 72 discharged patients were collected and the consistence of IgM and IgG antibodies were detected by chemiluminescence method. SPSS25.0 was used for gender, age, case type and antibody analysis of variance, χ2 test and other analysis. Results: The average time of the serum samples collection of 72 patients was (34.89±9.02)days (median time: 34 days) from onset of COVID-19, and (14.53±8.35) days (median time: 14 days) from discharge. The positive rate of IgM or IgG was 97.22% (70/72), and the positive rate of IgM and IgG was 48.61% (35/72) and 97.22% (70/72) respectively. Serum COVID-19 antibodies were detected in 72 patients from 1st to 40th days after discharge. The average concentration of IgM in 1-7 days, 8-14 days, 15-21 days, 22-28 days, above 29 days were 21.91(7.07-52.84)AU/ml, 14.16(6.19-32.88)AU/ml, 11.36(6.65-42.15)AU/ml, 8.15(3.66-30.12)AU/ml, 2.98(0.46-6.37)AU/ml. There was no significant difference in the time of IgM antibody concentration (H= 8.439, P>0.05). The average concentrations of IgG in 1-7 days, 8-14 days, 15-21 days, 22-28 days, 29 days and above were 169.90 (92.06-190.91) AU/ml, 163.89 (91.19-208.02) AU/ml, 173.31 (95.06-191.28) AU/ml, 122.84 (103.19-188.34) AU/ml, 101.98 (43.75-175.30) AU/ml, respectively, (H=2.232, P>0.05). The IgM becomes negative after the 3rd week of discharge and decreases rapidly with time. The IgG concentration higher than IgM during the same period, and keep at high level without any change, and decrease in the fourth week. Among them, 5 cases developed "re-infection" within 1-3 weeks after discharge, and the rate of "re-infection" was 6.94% (5/72 cases). Conclusions: After the COVID-19 patients are discharged from the hospital, the level of antibodies produced varies greatly among individuals, but the overall changes in antibodies have a certain pattern. It is recommended to strengthen the antibody monitoring during hospitalization and after discharge from the hospital to reduce the "re-infection" rate and potential risk of infection.


Subject(s)
COVID-19 , Adult , Antibodies, Viral , Female , Humans , Immunoglobulin G , Immunoglobulin M , Male , Middle Aged , SARS-CoV-2
19.
China and World Economy ; 28(6):1-27, 2020.
Article in English | Scopus | ID: covidwho-970717

ABSTRACT

The decoupling policies enforced by the Trump Administration aim to break the US economic relationship with China. Those policies, however, are escalating strategic costs for the US in at least three unanticipated ways: the decoupling policies are losing the endorsement of US multinational corporations, undermining the solidarity of the US and its allies, and making supply chains more likely to disengage from the US than to disengage from China. We argue that the ongoing decoupling policies are costing more than the US can bear and will end in vain. If the Trump Administration enforces further decoupling policies without considering those implicit costs, it will only set the US up for a more expensive failure. © 2020 Institute of World Economics and Politics, Chinese Academy of Social Sciences

20.
Discov Med ; 29(158):201-209, 2020.
Article in English | PubMed | ID: covidwho-812916

ABSTRACT

Sepsis is an important disorder in intensive care medicine, and the emphasis is not on infections but the imbalance in body reactions and life-threatening organ dysfunction. The infection, the imbalance in the body's reaction, and the deadly organ dysfunction are three aspects of sepsis. Currently, there is still a debate on suitable criteria for the diagnosis of patients with sepsis with continuing changes in the guidelines on sepsis management. Here we summarize recent advances on the definitions, diagnosis, and treatment in the clinical practice of sepsis management in the emergency department. We also highlight future research directions on sepsis. In particular, given the global outbreak of coronavirus disease 2019 (COVID-19), we briefly describe the relationship between COVID-19 and sepsis. How to manage sepsis caused by emerging pathogens such as COVID-19 is a new challenge for care professionals in the emergency department.

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