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1.
EMBO Journal ; : e111737, 2022.
Article in English | MEDLINE | ID: covidwho-2164323

ABSTRACT

Bat-origin RshSTT182 and RshSTT200 coronaviruses (CoV) from Rhinolophus shameli in Southeast Asia (Cambodia) share 92.6% whole-genome identity with SARS-CoV-2 and show identical receptor binding domains (RBDs). In this study, we determined the structure of the RshSTT182/200 receptor binding domain (RBD) in complex with human angiotensin-converting enzyme 2 (hACE2) and identified the key residues that influence receptor binding. Binding of the RshSTT182/200 RBD to ACE2 orthologs from 39 animal species, including 18 bat species, was used to evaluate its host range. The RshSTT182/200 RBD broadly recognized 21 out of 39 ACE2 orthologs, although its binding affinities for the orthologs were weaker than those of the RBD of SARS-CoV-2. Furthermore, RshSTT182 pseudovirus could utilize human, fox and Rhinolophus affinis ACE2 receptors for cell entry. Moreover, we found that SARS-CoV-2 induces cross-neutralizing antibodies against RshSTT182 pseudovirus. Taken together, the findings indicate that RshSTT182/200 can potentially infect susceptible animals, but requires further evolution to obtain strong interspecies transmission abilities like SARS-CoV-2.

2.
Frontiers in Public Health ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2163174

ABSTRACT

Fever screening is an effective method to detect infectors associated with different variants of coronavirus disease 2019 (COVID-19) based on the fact that most infectors with COVID-19 have fever symptoms. Non-contact infrared thermometers (NCITs) are widely used in fever screening. Nevertheless, authoritative data is lacking in defining "fever" at different body surface sites when using NCITs. The purpose of this study was to determine the optimal diagnostic threshold for fever screening using NICTs at different body surface sites, to improve the accuracy of fever screening and provide theoretical reference for healthcare policy. Participants (n = 1860) who were outpatients or emergency patients at Chengdu Women's and Children's Central Hospital were recruited for this prospective investigation from March 1 to June 30, 2021. NCITs and mercury axillary thermometers were used to measure neck, temple, forehead and wrist temperatures of all participants. Receiver operating characteristic curves were used to reflect the accuracy of NCITs. Linear correlation analysis was used to show the effect of age on body temperature. Multilinear regression analysis was used to explore the association between non-febrile participant's covariates and neck temperature. The mean age of participants was 3.45 +/- 2.85 years for children and 28.56 +/- 7.25 years for adults. In addition 1,304 (70.1%) participants were children (<= 12), and 683 (36.7%) were male. The neck temperature exhibited the highest accuracy among the four sites. Further the optimal fever diagnostic thresholds of NCITs at the four body surface measurement sites were neck (36.75 degrees C, sensitivity: 0.993, specificity: 0.858);temple (36.55 degrees C, sensitivity: 0.974, specificity: 0.874);forehead (36.45 degrees C, sensitivity: 0.961, specificity: 0.813);and wrist (36.15 degrees C, sensitivity: 0.951, specificity: 0.434). Based on the findings of our study, we recommend 36.15, 36.45, 36.55, and 36.75 degrees C as the diagnostic thresholds of fever at the wrist, forehead, temple and neck, respectively. Among the four surface sites, neck temperature exhibited the highest accuracy.

3.
Eur J Med Res ; 27(1):283, 2022.
Article in English | PubMed | ID: covidwho-2162425

ABSTRACT

The coronavirus disease 2019 (COVID-19), caused by a novel virus of the beta-coronavirus genus (SARS-CoV-2), has spread rapidly, posing a significant threat to global health. There are currently no drugs available for effective treatment. Severe cases of COVID-19 are associated with hyperinflammation, also known as cytokine storm syndrome. The reduce inflammation are considered promising treatments for COVID-19. Necroptosis is a type of programmed necrosis involved in immune response to viral infection, and severe inflammatory injury. Inhibition of necroptosis is pivotal in preventing associated inflammatory responses. The expression of key regulators of the necroptosis pathway is generally up-regulated in COVID-19, indicating that the necroptosis pathway is activated. Thus, necroptosis inhibitors are expected to be novel therapeutic candidates for the treatment of COVID-19.Better knowledge of the necroptosis pathway mechanism is urgently required to solve the remaining mysteries surrounding the role of necroptosis in COVID-19. In this review, we briefly introduce the pathogenesis of necroptosis, the relationship between necroptosis, cytokine storm, and COVID-19 also summarizes the progress of inhibitors of necroptosis. This research provides a timely and necessary suggest of the development of necroptosis inhibitors to treat COVID-19 and clinical transformation of inhibitors of necroptosis.

4.
Proceedings of the Acm on Interactive Mobile Wearable and Ubiquitous Technologies-Imwut ; 6(3), 2022.
Article in English | Web of Science | ID: covidwho-2162013

ABSTRACT

When in front of a classroom, a skilled teacher can read the room, identifying when students are engaged, frustrated, distracted, etc. In recent years we have seen significant changes in the traditional classroom, with virtual classes becoming a normal learning environment. Reasons for this change are the increased popularity of Massive Open Online Courses (MOOCs) and the disruptions imposed by the ongoing COVID-19 pandemic. However, it is difficult for teachers to read the room in these virtual classrooms, and researchers have begun to look at using sensors to provide feedback to help inform teaching practices. The study presented here sought to ground classroom sensor data in the form of electrodermal activities (EDA) captured using a wrist-worn sensing platform (Empatica E4), with observations about students' emotional engagement in the class. We collected a dataset from eleven students over eight lectures in college-level computer science classes. We trained human annotators who provided ground truth information about student engagement based on in-class observations. Inspired by related work in the field, we implemented an automated data analysis framework, which we used to explore momentary assessments of student engagement in classrooms. Our findings surprised us because we found no significant correlation between the sensor data and our trained observers' data. In this paper, we present our study and framework for automated engagement assessment, and report on our findings that indicate some of the challenges in deploying current technology for real-world, automated momentary assessment of student engagement in the classroom. We offer reflections on our findings and discuss ways forward toward an automated reading the room approach.

5.
Journal of Medical Virology ; 15:15, 2022.
Article in English | MEDLINE | ID: covidwho-2157855

ABSTRACT

To control the ongoing COVID-19 pandemic, a variety of SARS-CoV-2 vaccines have been developed. However, the rapid mutations of SARS-CoV-2 spike (S) protein may reduce the protective efficacy of the existing vaccines which is mainly determined by the level of neutralizing antibodies targeting S. In this study, we screened prevalent S mutations and constructed 124 pseudotyped lentiviral particles carrying these mutants. We challenged these pseudoviruses with sera vaccinated by Sinovac CoronaVac and ZF2001 vaccines, two popular vaccines designed for the initial strain of SARS-CoV-2, and then systematically assessed the susceptivity of these SARS-CoV-2 variants to the immune sera of vaccines. As a result, 14 S mutants (H146Y, V320I+S477N, V382L, K444R, L455F+S477N, L452M+F486L, F486L, Y508H, P521R, A626S, S477N+S698L, A701V, S477N+T778I, E1144Q) were found to be significantly resistant to neutralization, indicating reduced protective efficacy of the vaccines against these SARS-CoV-2 variants. In addition, F486L and Y508H significantly enhanced the utilization of human ACE2, suggesting a potentially elevated infectivity of these two mutants. In conclusion, our results show that some prevalent S mutations of SARS-CoV-2 reduced the protective efficacy of current vaccines and enhance the infectivity of the virus, indicating the necessity of vaccine renewal and providing direction for the development of new vaccines. This article is protected by copyright. All rights reserved.

6.
JMIR Public Health Surveill ; 2022.
Article in English | PubMed | ID: covidwho-2154534

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, infodemic spread even more rapidly than the pandemic itself. The COVID-19 vaccine hesitancy has been prevalent worldwide and hindered pandemic exiting strategies. Misinformation around COVID-19 vaccine is a vital contributor to vaccine hesitancy. However, no evidence systematically summarized COVID-19 vaccine misinformation. OBJECTIVE: To synthesize the global evidence on misinformation related to COVID-19 vaccines, including its prevalence, features, influencing factors, impacts, and solutions for combating misinformation. METHODS: We performed a systematic review by searching five peer-reviewed databases (PubMed, EMBASE, Web of Science, Scopus, and EBSCO). We included original articles that investigated misinformation related to COVID-19 vaccine and were published in English from January 1, 2020, to August 18, 2022. We excluded publications that did not cover or focus on COVID-19 vaccine misinformation. The Appraisal tool for Cross-Sectional Studies, Cochrane RoB 2.0 tool, and Critical Appraisal Skills Programme Checklist were used to assess the study quality. The review was guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses and registered with PROSPERO (CRD42021288929). RESULTS: Of 8864 studies identified, 91 observational studies and 11 interventional studies met the inclusion criteria. Misinformation around COVID-19 vaccine covered conspiracy, concerns on vaccine safety and efficacy, no need for vaccine, morality, liberty, and humor. Conspiracy and safety concerns were the most prevalent misinformation. There was a great variation in misinformation prevalence with 2.5~55.4% in general population and 6.0~96.7% in antivaccine/vaccine hesitant groups from survey-based studies, and the prevalence of 0.1~41.3% on general online data and 0.5~56% on antivaccine/vaccine hesitant data from Internet-based studies. Younger age, lower education and economic status, right-wing and conservative ideology, having psychological problems enhanced beliefs in misinformation. The content, format, and source of misinformation influenced its spread. A five-step framework was proposed to address vaccine-related misinformation, including identifying misinformation, regulating producers and distributors, cutting production and distribution, supporting target audiences, and disseminating trustworthy information. The debunking messages/videos were found to be effective in several experimental studies. CONCLUSIONS: Our review provided comprehensive and up-to-date evidence on COVID-19 vaccine misinformation and helps responses to vaccine infodemic in future pandemics.

7.
BMC Nephrol ; 23(1):389, 2022.
Article in English | PubMed | ID: covidwho-2153529

ABSTRACT

BACKGROUND: Observational studies have shown home hemodialysis (HHD) to be associated with better survival than facility hemodialysis (HD) and peritoneal dialysis (PD). Patients on HHD have reported higher quality of life and independence. HHD is considered to be an economical way to manage end-stage kidney disease (ESKD). The coronavirus disease 2019 pandemic has had a significant impact on patients with ESKD. Patients on HHD may have an advantage over in-center HD patients because of a lower risk of exposure to infection. PARTICIPANTS AND METHODS: We enrolled HD patients from our dialysis center. We first established the HHD training center. The training center was approved by the Chinese government. Doctors, nurses and engineers train and assess patients separately. There are three forms of patient monitoring: home visits, internet remote monitoring, and outpatient services. Demographic and medical data included age, sex, blood pressure, and dialysis-related data. Laboratory tests were conducted in our central testing laboratory, including hemoglobin (Hgb), serum creatinine (Cr), urea nitrogen (BUN), uric acid (UA), albumin (Alb), calcium (Ca), phosphorus (P), parathyroid hormone (PTH), and brain natriuretic peptide (BNP) levels. RESULTS: Six patients who underwent regular dialysis in the HD center of our hospital were selected for HHD training. We enrolled 6 patients, including 4 males and 2 females. The mean age of the patients was 47.5 (34.7-55.7) years, and the mean dialysis age was 33.5 (11.2-41.5) months. After an average of 16.0 (11.2-25.5) months of training, Alb, P and BNP levels were improved compared with the baseline values. After training, three patients returned home to begin independent HD. During the follow-up, there were no serious adverse events leading to hospitalization or death, but there were several adverse events. They were solved quickly by extra home visits of the technicians or online by remote monitoring. During the follow-up time, the laboratory indicators of all the patients, including Hgb, Alb, Ca, P, PTH, BNP, and β2-MG levels, remained stable before and after HHD treatment. CONCLUSION: HHD is feasible and safe for ESKD in China, but larger-scale and longer-term studies are needed for further confirmation.

8.
6th International Conference on Education and Multimedia Technology, ICEMT 2022 ; : 436-443, 2022.
Article in English | Scopus | ID: covidwho-2153126

ABSTRACT

This study crawled the cross-sectional data of the contents and comments from Microblog Account Xiake Island during the outbreak of coronavirus pneumonia as subjects, to examine the deviation and resonance association among affective fluctuations of the Chinese public, media framework, and audiences' cognitive framework. Using SnowNLP to conduct sentiment analysis of text comments, we found that during the outbreak of coronavirus pneumonia, the public spent most of the time in low-intensity negative affectivity, and the average affective propensity in response to individual microblog fluctuated greatly, and the public was easily caught in an emotional frenzy, which reduces the level of trust in government. Through a comparison of public affectivity and related epidemic data, Xiake Island focuses on reporting emotional facts, whose construction of social reality contains obvious emotional trajectories. Clustering analysis of thematic framework by LDA algorithm reveals that in terms of framework, the framework Xiake Island uses resonates to a large degree with the framework users focus on. In terms of the level of concerns over the framework, Xiake Island deviates to a certain extent from the public. This deviation, together with the strategy of focusing on reporting emotional facts, is a discursive strategy adopted by the new mainstream media to seek the reconstruction of cultural leadership. © 2022 Owner/Author.

9.
Research in International Business and Finance ; 64, 2023.
Article in English | Scopus | ID: covidwho-2150516

ABSTRACT

This study brings some new insights into EPU risk management. By categorizing China's energy futures (CEF) investors by risk preference, investment position and investment horizon, we identify how EPU in four energy-exporting countries affects CEF investors. The Russian EPU mainly produces influence on short-run investors and risk-seeking investors. The Australian EPU affects risk-seeking investors heavily, while the Brazilian EPU acts on risk-seeking investors with short positions. In terms of China's coking coal futures, changes in Russian EPU generate the weakest impact on various types of investors, while the US EPU affects medium-run risk-averse and long-run investors. The Australian EPU's impact on investor types covers a wide range, while the Brazilian EPU affects short-run risk-averse and long-run investors. Moreover, for medium-run CEF investors, energy-exporting countries’ EPU risk characteristics is most dynamic. Changes in the EPU risk impact type mainly occurred during the US-China trade war and the outbreak of COVID-19. © 2022 Elsevier B.V.

10.
Journal of Operations Management ; 2022.
Article in English | Scopus | ID: covidwho-2148400

ABSTRACT

The outbreak of the COVID-19 pandemic has disrupted supply chains and increased the uncertainties faced by firms. While firms are struggling to survive and recover from the pandemic, Chinese e-commerce platforms have demonstrated resilient supply chains. We develop a framework that investigates the impacts of integration between an e-commerce platform and suppliers on supply chain resilience and the moderating effect of the suppliers' product flexibility. An analysis of data from a Chinese e-commerce platform using operational indicators finds that integration between the e-commerce platform and suppliers in terms of information sharing, joint planning and logistics cooperation has positive impacts on supply chain resilience, while procurement automation has the opposite effect. Furthermore, product flexibility positively moderates the impacts of information sharing, joint planning and logistics cooperation. The results enhance current understandings of the factors that contribute to the development of supply chain resilience and reveal that the relationship between integration and resilience should be examined within a contingency framework. The findings also provide guidelines for managers taking measures to mitigate the negative influences of supply chain disruptions. © 2022 Association for Supply Chain Management, Inc.

11.
J Med Virol ; 2022.
Article in English | PubMed | ID: covidwho-2148396

ABSTRACT

Children are the high-risk group for COVID-19, and in need of vaccination. However, humoral and cellular immune responses of COVID-19 vaccine remain unclear in vaccinated children. To establish the rational immunization strategy of inactivated COVID-19 vaccine for children, the immunogenicity of either one dose or two doses of the vaccine in children was evaluated. A prospective cohort study of 322 children receiving inactivated COVID-19 vaccine was established in China. The baseline was conducted after 28 days of the first dose, and the follow-up was conducted after 28 days of the second dose. The median titers of RBD-IgG, and neutralizing antibody (NAb) against prototype strain and Omicron variant after the second dose increased significantly compared to those after the first dose (first dose: 70.0, [IQR, 30.0-151.0] vs second dose: 1261.0 [636.0-2060.0] for RBD-IgG;2.5 [2.5-18.6] vs 252.0 [138.6-462.1] for NAb against prototype strain;2.5 [2.5-2.5] vs 15.0 [7.8-26.5] for NAb against Omicron variant, all P <0.05). The flow cytometry results showed that the first dose elicited SARS-CoV-2 specific cellular immunity, while the second dose strengthened SARS-CoV-2 specific IL-2(+) or TNF-α(+) monofunctional, IFN-γ(+) TNF-α(+) bifunctional, and IFN-γ(-) IL-2(+) TNF-α(+) multifunctional CD4(+) T cell responses (P <0.05). Moreover, SARS-CoV-2 specific memory T cells were generated after the first vaccination, including the central memory T cells and effector memory T cells. The present findings provide scientific evidence for the vaccination strategy of inactive vaccine among children against COVID-19 pandemic. This article is protected by copyright. All rights reserved.

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13.
Jisuanji Gongcheng/Computer Engineering ; 48(7):42-50, 2022.
Article in Chinese | Scopus | ID: covidwho-2145861

ABSTRACT

Standardized usage of face masks is effective as a non-pharmaceutical intervention to prevent the spread of infectious respiratory diseases,such as COVID-19 and influenza. In the current epidemic situation,wearing face masks correctly is especially important. Most existing mask-wearing detection algorithms involve problems such as complex structures,high training difficulty,and insufficient feature extraction. Therefore,this study proposes a lightweight mask-wearing detection algorithm based on multi-scale feature fusion and the YOLOv4-Tiny network,called L-MFFN-YOLO. L-MFFN-YOLO improves on the original residual structure and uses a lightweight residual module to promote rapid convergence. Moreover,it reduces the computational load while ensuring detection accuracy. Based on the original network’s 13×13 and 26×26 feature maps,52×52 feature branches are added to enhance the ability of the lower feature layer to express information and reduce the false negative rate for small targets.On this basis,a Multi-level Cross Fusion (MCF) structure is used to maximally extract useful information so as to improve feature utilization. In addition to detecting mask-wearing,a category of masks worn incorrectly is added to the dataset and manually labeled. The www.eciexperimental results show that the size of the proposed L-MFFN-YOLO model is only 5.8 MB,which is 76% smaller than that of the original YOLOv4-Tiny. Moreover,the mean Average Precision(mAP)of the proposed approach is 5.25 percentage points higher,and its processing time is 14 ms faster on an equivalent CPU.These results demonstrate that the proposed approach can meet the requirements of accuracy and real-time operation in resource-constrained devices to detect faces wearing masks. © 2022, Editorial Office of Computer Engineering. All rights reserved.

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15.
Multiple Sclerosis Journal ; 28(3 Supplement):518-520, 2022.
Article in English | EMBASE | ID: covidwho-2138912

ABSTRACT

Background: Understanding outcomes of Coronavirus Disease 2019 (COVID-19) and the impact of COVID-19 vaccination deserve significant consideration for people with multiple sclerosis (MS) treated with ocrelizumab (OCR). Aim(s): To report the number, characteristics and outcomes of COVID-19 cases in all OCR-treated patients and in those with COVID-19 vaccination (i.e. breakthrough cases) in two realworld cohort studies. Method(s): We analysed data from OCR-treated patients enrolled in ongoing, prospective, noninterventional studies conducted in Germany (CONFIDENCE, EUPAS22951) and in 25 other countries (MuSicalE, NCT03593590). COVID-19 seriousness was assessed per ICH guidelines. Outcomes were captured as recovered, recovered with sequelae, recovering, not recovered or fatal. Vaccine breakthroughs were cases with COVID-19 onset >=14 days after completion of the primary immunisation schedule recommended for each COVID-19 vaccine platform. 'Unvaccinated' included patients without COVID-19 vaccination recorded (including the prevaccination era) or with incomplete immunisation scheme. Result(s): Analyses included 1,702 OCR-treated patients from MuSicalE (73.1% relapsing-remitting MS, 21.2% primary progressive MS [PPMS], 5.6% relapsing secondary progressive MS) and 2,784 from CONFIDENCE (81.7% relapsing MS, 18.3% PPMS). As of March 2022 (preliminary data), completion of primary immunisation schedule was recorded for 542 (31.8%) and 710 (25.5%) patients in each study, mainly with mRNA vaccines (72.3% and 93.8%). COVID-19 infection was reported in 189 and 122 patients in MuSicalE and CONFIDENCE (11.1% and 4.4% among all patients), mostly reported as nonserious (85.2% and 83.6%), including 71 and 31 vaccine breakthroughs (13.1% and 4.4% among fully vaccinated patients). The following rates were reported in vaccinated and unvaccinated patients in MuSicalE and CONFIDENCE, respectively: (a) hospitalisations, 8.5% (6/71) vs 16.0% (19/118) and 9.7% (3/31) vs 14.3% (13/91);(b) serious cases, 8.5% (6/71) vs 17.8% (21/118) and 9.7% (3/31) vs 18.7% (17/91);(c) fatalities, 1.4% (1/71) vs 2.5% (3/118) and 0 deaths vs 2.2% (2/91). In both studies, the majority of patients had fully recovered (79.9% and 74.6%) or were recovering (11.1% and 7.4%) at last follow-up. Updated vaccination rates will be presented. Conclusion(s): Most COVID-19 cases were nonserious in these OCR-treated patient cohorts. Initial data suggest more favourable clinical outcomes associated with COVID-19 vaccination.

16.
Evaluation Review ; : 193841X221141812, 2022.
Article in English | MEDLINE | ID: covidwho-2138404

ABSTRACT

The COVID-19 pandemic poses a serious threat to investors in the crude oil market. Furthermore, investors have an increasing need to find a safe haven in their investment portfolios when facing unprecedented risks in crude oil markets during the COVID-19 pandemic. According to a review of the literature, there are contradictory findings on which investment is the safer haven for the oil market. Therefore, this paper aims to evaluate whether bitcoin is a safer haven for the crude oil market than the commonly used gold during the COVID-19 pandemic. Three spillover measurements based on the time, and frequency domains, and a network framework are employed to quantify the return spillover effects among bitcoin, gold and three major crude oil futures markets. We divide the sample into two periods, pre-COVID-19 and post-COVID-19. The results show that bitcoin has a weak safe-haven effect on the crude oil market only over a short period, while gold maintains a good safe-haven ability for crude oil futures across various time horizons (frequencies), both before and after the outbreak of the COVID-19 pandemic. The findings of this study have important implications for policy-makers, crude oil producers and global investors. In particularly, investors cannot ignore the importance of bitcoin and gold in selecting more profitable portfolio policies when searching for safe-haven assets.

17.
25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022 ; 2022-October:3849-3854, 2022.
Article in English | Scopus | ID: covidwho-2136418

ABSTRACT

The outbreak of COVID-19 has made a profound impact on mobility, especially for public transport users. Extensive research has been conducted on the change of travel patterns in major cities where public transport systems have been well developed and heavily used. However, in small cities, the public transport network is relatively sparse, especially in suburban areas, which makes the corresponding travel patterns differ from those in major cities. Therefore, proper investigation of the public transport usage in such small cities is still needed, especially under the COVID-19 impact. This paper aims to reveal the change of public transport users' travel patterns based on a comparative study of public transport usage Pre-COVID and during the COVID-19 period. The Illawarra, a coastal region close to Sydney in Australia is used as a case study. Smart card data is used to reveal relevant changes in both intraregion (in the Illawarra) and inter-region (between the Illawarra and Sydney) travels in consideration of heterogeneous user groups. The results show a significant decrease (around 47%) in public transport ridership by both train and bus. However, compared to intra-region ridership, the inter-region trips by train drop much more (around 62%). Moreover, heterogeneous age group passengers show different changes after the COVID-19 outbreak. The research findings are expected to provide valuable suggestions for policy making and public transport service adjustment when a similar crisis occurs again. © 2022 IEEE.

18.
Energy Strategy Reviews ; 44, 2022.
Article in English | Scopus | ID: covidwho-2130801

ABSTRACT

The lockdown policies related with the COVID-19 pandemic brings carbon emissions slump, but emissions potentially restore to increase as lockdown policies relaxed and the economy recovers. In this context, this study aims to explore the changes in carbon emissions and their underlying factors in the post-COVID-19 era from a national and sectoral perspective by drawing on the experience of carbon emissions before and after the 2008 global crisis. The latest extreme event and carbon emission trends might provide some implications for curbing potential emission rebound after the pandemic. The results indicate that, (i) developing countries like China and India still struggle with carbon reduction, which need more efforts made to control continuously increased carbon emission;(ii) energy intensity and economic level are respectively major contributor and inhibitor to national and industrial emission reduction whether in developing or developed countries, while in developed countries, energy intensity has a slightly stronger impact on carbon emissions than economic level. Carbon intensity had both positive and negative impact on carbon emission, and population scale usually drove carbon emission increase, particularly in developing countries like India;(iii) Industrial carbon emissions vary widely across economies, but most industrial carbon emissions continue to decrease in developed countries while increase in developing countries. Therefore, we contend that energy intensity is the key point to prevent a potential rebound of emission in post-COVID-19 era. © 2022

19.
Journal of the American Society of Nephrology ; 33:323, 2022.
Article in English | EMBASE | ID: covidwho-2125560

ABSTRACT

Background: Antiviral medications such as remdesivir, molnupiravir, and nirmatrelvir/ritonavir are most effective when used early in the course of COVID-19. These medications are authorized for patients with COVID-19 with mild symptoms who are at high risk for severe disease. ESKD is among the strongest risk factors for mortality from COVID-19. As the ESKD population is highly linked to care, we hypothesized that they are more likely to be admitted to the hospital within five days of symptom onset when antiviral medications are maximally effective. Method(s): We identified patients with ESKD on dialysis who were admitted to Massachusetts General Hospital with COVID-19 by using dialysis records and manually extracted the date of symptom onset as shown in the admission note. Primary outcome was the proportion of patients with ESKD admitted within 5 days of symptom onset;secondary outcome was the risk of respiratory failure within 90 days among the early presenters. Result(s): After implementing the exclusion criteria shown in Figure 1, we included 99 patients with community-acquired COVID-19 admitted between March 2020 and Jan 2022. Thirty patients (30%) remained asymptomatic during their hospitalization. Among patients with symptomatic COVID-19, 56 (81%) were admitted within 5 days of symptom onset;among them, 17 developed respiratory failure within 90 days (30%) and 11 died from respiratory failure (20%). (Figure1) Conclusion(s): We found that most patients with ESKD on dialysis admitted for symptomatic COVID-19 presented within 5 days of symptom onset. We conjectured that because of this, inpatient antiviral therapy may be more effective in the ESKD population than in a typical inpatient population with COVID-19 that presents later in the disease course. Given the high risk of respiratory failure in ESKD population who developed COVID-19, improved treatment strategies are urgently needed.

20.
5th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2022 ; : 225-234, 2022.
Article in English | Scopus | ID: covidwho-2120784

ABSTRACT

The epidemic of infectious diseases has become a major problem threatening the world public health, and the dynamic models of virus spreading are widely used for epidemic tracking and prediction. The existing dynamic models do not consider the synergistic effects of population migration factors and changes in transmission rates on diseases. Therefore, based on the SIR (Susceptible-Infectious-Recovered) model, the time-dependent M-SIR (Migration-Susceptible-Infectious-Recovered) model was proposed by introducing the population migration (Migration) factor. Meanwhile, introducing the machine learning LightGBM (Light Gradient Boosting Machine) method to track the infection rate and recovery rate, and explored the impact of cross-regional population movement and prevention and control measures on the development of the epidemic. Take the new crown epidemic as an example, firstly, the data of population migration and epidemic spread were statistically analyzed to monitor the relationship between population mobility and epidemic development. Then, the m-sir model is used to predict the infected cases and removed cases in Beijing and Shanghai. Through comparative analysis with the SIR model, the prediction accuracy of the model has been greatly improved. At the same time, the development trend of the epidemic situation in related cities before and after control is explored, which can provide some theoretical support for future epidemic prediction and control decisions. © 2022 IEEE.

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