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1.
Human vaccines & Immunotherapeutics ; : 1-5, 2022.
Article in English | MEDLINE | ID: covidwho-1830889

ABSTRACT

PURPOSE: We explored the willingness to pay for booster dose of COVID-19 vaccine among health-care workers in Taizhou, China. METHODS: A population-based self-administered online questionnaire evaluating the willingness of health-care workers to pay for booster vaccination of COVID-19 vaccine was conducted in Taizhou, China. Of the 1102 health-care workers received the invitation, 1072 (97.3%) had received twice vaccination of COVID-19 vaccine. RESULTS: There were 1569 (53.1%) out of 1072 health-care workers not willing to pay for thebooster dose of COVID-19 vaccines, 348 (32.5%) were willing to pay less than 100CHY for the booster dose of COVID-19 vaccines, only 155 (14.5%) were willing to pay more than 100 CHY. The factors related to willingness to pay for booster dose of COVID-19 vaccines were education level (c2 = 9.42, P = .01) or whether they had adverse effect to COVID-19 vaccines (c2 = 11.87, P < .01) . CONCLUSION: This study found that about half of health-care workers were willing to pay for booster dose of inactivated SARS-CoV-2 vaccines in Taizhou, China, most of them are willing to pay less than 100 CHY. Health-care workers' willingness to pay for booster dose of COVID-19 vaccines were related to sex, education level, whether they had adverse effect to COVID-19 vaccines.

2.
Cellular & Molecular Immunology ; 19(5):577-587, 2022.
Article in English | MEDLINE | ID: covidwho-1830043

ABSTRACT

Neutrophil extracellular traps (NETs) can capture and kill viruses, such as influenza viruses, human immunodeficiency virus (HIV), and respiratory syncytial virus (RSV), thus contributing to host defense. Contrary to our expectation, we show here that the histones released by NETosis enhance the infectivity of SARS-CoV-2, as found by using live SARS-CoV-2 and two pseudovirus systems as well as a mouse model. The histone H3 or H4 selectively binds to subunit 2 of the spike (S) protein, as shown by a biochemical binding assay, surface plasmon resonance and binding energy calculation as well as the construction of a mutant S protein by replacing four acidic amino acids. Sialic acid on the host cell surface is the key molecule to which histones bridge subunit 2 of the S protein. Moreover, histones enhance cell-cell fusion. Finally, treatment with an inhibitor of NETosis, histone H3 or H4, or sialic acid notably affected the levels of sgRNA copies and the number of apoptotic cells in a mouse model. These findings suggest that SARS-CoV-2 could hijack histones from neutrophil NETosis to promote its host cell attachment and entry process and may be important in exploring pathogenesis and possible strategies to develop new effective therapies for COVID-19.

3.
BMC Geriatrics ; 22(1):395-395, 2022.
Article in English | PMC | ID: covidwho-1822167
4.
18th IEEE International Symposium on Biomedical Imaging (ISBI) ; : 1966-1970, 2021.
Article in English | Web of Science | ID: covidwho-1822031

ABSTRACT

Despite tremendous efforts, it is very challenging to generate a robust model to assist in the accurate quantification assessment of COVID-19 on chest CT images. Due to the nature of blurred boundaries, the supervised segmentation methods usually suffer from annotation biases. To support unbiased lesion localisation and to minimise the labelling costs, we propose a data-driven framework supervised by only image level labels. The framework can explicitly separate potential lesions from original images, with the help of an generative adversarial network and a lesion-specific decoder. Experiments on two COVID-19 datasets demonstrates the effectiveness of the proposed framework and its superior performance to several existing methods.

5.
International Journal of Molecular Sciences ; 23(9), 2022.
Article in English | EMBASE | ID: covidwho-1818149

ABSTRACT

The impact of COVID-19 has rendered medical technology an important factor to maintain social stability and economic increase, where biomedicine has experienced rapid development and played a crucial part in fighting off the pandemic. Conductive hydrogels (CHs) are three-dimensional (3D) structured gels with excellent electrical conductivity and biocompatibility, which are very suitable for biomedical applications. CHs can mimic innate tissue’s physical, chemical, and biological properties, which allows them to provide environmental conditions and structural stability for cell growth and serve as efficient delivery substrates for bioactive molecules. The customizability of CHs also allows additional functionality to be designed for different requirements in biomedical applications. This review introduces the basic functional characteristics and materials for preparing CHs and elaborates on their synthetic techniques. The development and applications of CHs in the field of biomedicine are highlighted, including regenerative medicine, artificial organs, biosensors, drug delivery systems, and some other application scenarios. Finally, this review discusses the future applications of CHs in the field of biomedicine. In summary, the current design and development of CHs extend their prospects for functioning as an intelligent and complex system in diverse biomedical applications.

6.
Frontiers in Psychology ; 13:789844, 2022.
Article in English | MEDLINE | ID: covidwho-1818009

ABSTRACT

Purpose: College students in the pandemic area are experiencing the problems caused by COVID-19 by themselves or people around them, how to cope with the sudden changes and adjust the psychological stress response, and get experience and grow in the fight against the pandemic is a question worth in-depth discussion. The researchers constructed a mediated regulation model to examine the effects of intrusive rumination on the creativity of college students during the COVID-19 pandemic, as well as the mediating effect of post-traumatic growth and the moderating role of psychological resilience. Methods: A sample of 475 university students from Guangdong Province, China, were surveyed with the Runco Ideational Behavior Scale, the Event Related Rumination Inventory, the Posttraumatic Growth Inventory, and the Psychological Resilience Scale. SPSS (version 23) and PROCESS (version 3.3) were used for correlation analysis, mediation analysis, and mediated moderation analysis. Results: (1) Intrusive rumination was positively correlated with post-traumatic growth and creativity but negatively correlated with psychological resilience. Psychological resilience was positively correlated with post-traumatic growth and creativity. Post-traumatic growth and creativity were positively correlated. (2) Post-traumatic growth played a mediating role in the relationship between intrusive rumination and creativity. (3) Psychological resilience moderated the first half of the pathway "intrusive rumination -> post-traumatic growth -> creativity." Conclusion: Intrusive rumination affected creativity directly and also indirectly through post-traumatic growth. At the same time, psychological resilience played a moderating role between intrusive rumination and creativity. The correlation between intrusive rumination and post-traumatic growth was stronger when levels of psychological resilience levels were higher.

7.
Scientific Reports ; 12(1):8, 2022.
Article in English | Web of Science | ID: covidwho-1815582

ABSTRACT

Based on the findings from the Phase III clinical trials of inactivated SARS COV-2 Vaccine, (BBIBP-CORV) emergency use authorization (EUA) was granted for the vaccine to frontline workers in the UAE. A prospective cohort study was conducted among frontline workers to estimate the incidence rate and risk of symptomatic COVID-19 infection 14 days after the second dose of inoculation with BBIBP-CORV inactivated vaccine. Those who received two doses of the BBIBP-CORV vaccine in the period from 14th of September 2020 (first dose) to 21st of December 2020 (second dose) were followed up for COVID-19 infections. 11,322 individuals who received the two-dose BBIBP-CORV vaccine were included and were followed up post the second dose plus fourteen days. The incidence rate of symptomatic infection was 0.08 per 1000-person days (95% CI 0.07, 0.10). The estimated absolute risk of developing symptomatic infection was 0.97% (95% CI 0.77%, 1.17%). The confirmed seroconversion rate was 92.8%. There were no serious adverse events reported and no individuals suffered from severe disease. Our findings show that vaccinated individuals are likely to remain protected against symptomatic infection or becoming PCR positive for SARS COV 2 following the second dose of the vaccination.

8.
JAMA Network Open ; 5(4):e229317, 2022.
Article in English | MEDLINE | ID: covidwho-1813429

ABSTRACT

Importance: An overall household secondary attack rate (SAR) of 18.9% (95% CI, 16.2%-22.0%) through June 17, 2021 was previously reported for SARS-CoV-2. Emerging variants of concern and increased vaccination have affected transmission rates. Objective: To evaluate how reported household SARs changed over time and whether SARs varied by viral variant and index case and contact vaccination status. Data Sources: PubMed and medRxiv from June 18, 2021, through March 8, 2022, and reference lists of eligible articles. Preprints were included. Study Selection: Articles with original data reporting the number of infected and total number of household contacts. Search terms included SARS-CoV-2, COVID-19, variant, vaccination, secondary attack rate, secondary infection rate, household, index case, family contacts, close contacts, and family transmission. Data Extraction and Synthesis: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline was followed. Meta-analyses used generalized linear mixed models to obtain SAR estimates and 95% CIs. Main Outcomes and Measures: SAR stratified by covariates according to variant, index case and contact vaccination status, and index case identification period. SARs were used to estimate vaccine effectiveness on the basis of the transmission probability for susceptibility to infection (VES,p), infectiousness given infection (VEI,p), and total vaccine effectiveness (VET,p). Results: Household SARs were higher for 33 studies with midpoints in 2021 to 2022 (37.3%;95% CI, 32.7% to 42.1%) compared with 63 studies with midpoints through April 2020 (15.5%;95% CI, 13.2% to 18.2%). Household SARs were 42.7% (95% CI, 35.4% to 50.4%) for Omicron (7 studies), 36.4% (95% CI, 33.4% to 39.5%) for Alpha (11 studies), 29.7% (95% CI, 23.0% to 37.3%) for Delta (16 studies), and 22.5% (95% CI, 18.6% to 26.8%) for Beta (3 studies). For full vaccination, VES,p was 78.6% (95% CI, 76.0% to 80.9%) for Alpha, 56.4% (95% CI, 54.6% to 58.1%) for Delta, and 18.1% (95% CI, -18.3% to 43.3%) for Omicron;VEI,p was 75.3% (95% CI, 69.9% to 79.8%) for Alpha, 21.9% (95% CI, 11.0% to 31.5%) for Delta, and 18.2% (95% CI, 0.6% to 32.6%) for Omicron;and VET,p was 94.7% (95% CI, 93.3% to 95.8%) for Alpha, 64.4% (95% CI, 58.0% to 69.8%) for Delta, and 35.8% (95% CI, 13.0% to 52.6%) for Omicron. Conclusions and Relevance: These results suggest that emerging SARS-CoV-2 variants of concern have increased transmissibility. Full vaccination was associated with reductions in susceptibility and infectiousness, but more so for Alpha than Delta and Omicron. The changes in estimated vaccine effectiveness underscore the challenges of developing effective vaccines concomitant with viral evolution.

9.
Brief Bioinform ; 2022.
Article in English | PubMed | ID: covidwho-1806277

ABSTRACT

Target prediction and virtual screening are two powerful tools of computer-aided drug design. Target identification is of great significance for hit discovery, lead optimization, drug repurposing and elucidation of the mechanism. Virtual screening can improve the hit rate of drug screening to shorten the cycle of drug discovery and development. Therefore, target prediction and virtual screening are of great importance for developing highly effective drugs against COVID-19. Here we present D3AI-CoV, a platform for target prediction and virtual screening for the discovery of anti-COVID-19 drugs. The platform is composed of three newly developed deep learning-based models i.e., MultiDTI, MPNNs-CNN and MPNNs-CNN-R models. To compare the predictive performance of D3AI-CoV with other methods, an external test set, named Test-78, was prepared, which consists of 39 newly published independent active compounds and 39 inactive compounds from DrugBank. For target prediction, the areas under the receiver operating characteristic curves (AUCs) of MultiDTI and MPNNs-CNN models are 0.93 and 0.91, respectively, whereas the AUCs of the other reported approaches range from 0.51 to 0.74. For virtual screening, the hit rate of D3AI-CoV is also better than other methods. D3AI-CoV is available for free as a web application at http://www.d3pharma.com/D3Targets-2019-nCoV/D3AI-CoV/index.php, which can serve as a rapid online tool for predicting potential targets for active compounds and for identifying active molecules against a specific target protein for COVID-19 treatment.

10.
Expert Rev Anti Infect Ther ; 2022.
Article in English | PubMed | ID: covidwho-1806119

ABSTRACT

INTRODUCTION: The rapid antigen detection tests (RADTs) for SARS-CoV-2 infection could contribute to the clinical and public health strategies for managing COVID-19. This umbrella review aimed to explore the accuracy and sensitivity of RADTs for SARS-CoV-2 by assessing the incidence of false positivity associated with them. AREAS COVERED: Meta-analyses and systematic reviews on the sensitivity and specificity of commercially available RADTs with data on false-positive results were identified by searching the PubMed, EMBASE, Cochrane Library, and Web of Science databases from inception to March 31, 2022. All meta-analyses and systematic reviews on the sensitivity and specificity of rapid antigen tests were included. Data on the author and year, included studies, index tests, sample size, false negatives, false positives, and study quality based on AMSTAR 2 (Assessing the Methodological Quality of Systematic Reviews) rating were extracted from the included meta-analyses and systematic reviews. EXPERT OPINION: We identified 12 meta-analyses and systematic review that presented data on the false-positive results in RADTs. The false positivity rates in the included studies ranged from 0.0% - 4.0%. This study summarizes the available evidence on the incidence of false positivity in RADTs and shows it is less than 4.0%. Therefore, our findings imply that RADTs can be an appropriate, economic, and rapid detection method for mass screening of COVID-19.

11.
J Med Virol ; 2022.
Article in English | PubMed | ID: covidwho-1802451

ABSTRACT

Influenza-like illness (ILI) varies in intensity year by year, generally keeping a stable pattern except for great changes of its epidemic issue. Of the most impacting factors, urbanization has been suggested as shaping the intensity of influenza epidemics. Besides, growing evidence indicates the non-pharmaceutical interventions (NPIs) to severe acute respiratory syndrome coronavirus 2 offer great advantages in controlling infectious diseases. The present study aimed to evaluate the impact of urbanization and NPIs on the dynamic of ILI in Tongzhou, Beijing, during January 2013 to March 2021. ILI epidemiological surveillance data in Tongzhou district were obtained from Beijing Influenza Surveillance Network and separated into three periods of urbanization and four intervals of coronavirus disease 2019 pandemic. Standardized average incidence rates of ILI in each separate stages were calculated and compared by using Wilson method and time series model of seasonal ARIMA. Influenza seasonal outbreaks showed similar epidemic size and intensity before urbanization during 2013-2016. Increased ILI activity was found during the process of Tongzhou's urbanization during 2017-2019, with the rate difference of 2.48 (95% CI 2.44, 2.52) and the rate ratio of 1.75 (95% CI 1.74, 1.76) of ILI incidence between pre-urbanization and urbanization periods. ILI activity abruptly decreased from the beginning of 2020 and kept at the bottom level almost in every epidemic interval. The top decrease in ILI activity by NPIs was shown in 5-14 years group in 2020-2021 influenza season, as 92.2% (95% CI 78.3%, 95.2%). The results indicated that both urbanization and NPIs interrupted the epidemic pattern of ILI. We should pay more attention to public health when facing increasing population density, human contact, population mobility and migration in the process of urbanization. NPIs and influenza vaccination should be implemented as necessary measures to protect people from common infectious diseases like ILI. This article is protected by copyright. All rights reserved.

12.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333702

ABSTRACT

Viral proteins localize within subcellular compartments to subvert host machinery and promote pathogenesis. To study SARS-CoV-2 biology, we generated an atlas of 2422 human proteins vicinal to 17 SARS-CoV-2 viral proteins using proximity proteomics. This identified viral proteins at specific intracellular locations, such as association of accessary proteins with intracellular membranes, and projected SARS-CoV-2 impacts on innate immune signaling, ER-Golgi transport, and protein translation. It identified viral protein adjacency to specific host proteins whose regulatory variants are linked to COVID-19 severity, including the TRIM4 interferon signaling regulator which was found proximal to the SARS-CoV-2 M protein. Viral NSP1 protein adjacency to the EIF3 complex was associated with inhibited host protein translation whereas ORF6 localization with MAVS was associated with inhibited RIG-I 2CARD-mediated IFNB1 promoter activation. Quantitative proteomics identified candidate host targets for the NSP5 protease, with specific functional cleavage sequences in host proteins CWC22 and FANCD2. This data resource identifies host factors proximal to viral proteins in living human cells and nominates pathogenic mechanisms employed by SARS-CoV-2. AUTHOR SUMMARY: SARS-CoV-2 is the latest pathogenic coronavirus to emerge as a public health threat. We create a database of proximal host proteins to 17 SARS-CoV-2 viral proteins. We validate that NSP1 is proximal to the EIF3 translation initiation complex and is a potent inhibitor of translation. We also identify ORF6 antagonism of RNA-mediate innate immune signaling. We produce a database of potential host targets of the viral protease NSP5, and create a fluorescence-based assay to screen cleavage of peptide sequences. We believe that this data will be useful for identifying roles for many of the uncharacterized SARS-CoV-2 proteins and provide insights into the pathogenicity of new or emerging coronaviruses.

13.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333616

ABSTRACT

OBJECTIVE: Patients with autoimmune diseases were advised to shield to avoid COVID-19, but information on their prognosis is lacking. We characterised 30-day outcomes and mortality after hospitalisation with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza. DESIGN: Multinational network cohort study. SETTING: Electronic health records data from Columbia University Irving Medical Center (CUIMC) (NYC, United States [US]), Optum [US], Department of Veterans Affairs (VA) (US), Information System for Research in Primary Care-Hospitalisation Linked Data (SIDIAP-H) (Spain), and claims data from IQVIA Open Claims (US) and Health Insurance and Review Assessment (HIRA) (South Korea). PARTICIPANTS: All patients with prevalent autoimmune diseases, diagnosed and/or hospitalised between January and June 2020 with COVID-19, and similar patients hospitalised with influenza in 2017-2018 were included. MAIN OUTCOME MEASURES: 30-day complications during hospitalisation and death. RESULTS: We studied 133,589 patients diagnosed and 48,418 hospitalised with COVID-19 with prevalent autoimmune diseases. The majority of participants were female (60.5% to 65.9%) and aged >=50 years. The most prevalent autoimmune conditions were psoriasis (3.5 to 32.5%), rheumatoid arthritis (3.9 to 18.9%), and vasculitis (3.3 to 17.6%). Amongst hospitalised patients, Type 1 diabetes was the most common autoimmune condition (4.8% to 7.5%) in US databases, rheumatoid arthritis in HIRA (18.9%), and psoriasis in SIDIAP-H (26.4%). Compared to 70,660 hospitalised with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2% to 4.3% versus 6.3% to 24.6%). CONCLUSIONS: Patients with autoimmune diseases had high rates of respiratory complications and 30-day mortality following a hospitalization with COVID-19. Compared to influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality. Future studies should investigate predictors of poor outcomes in COVID-19 patients with autoimmune diseases. WHAT IS ALREADY KNOWN ABOUT THIS TOPIC: Patients with autoimmune conditions may be at increased risk of COVID-19 infection andcomplications. There is a paucity of evidence characterising the outcomes of hospitalised COVID-19 patients with prevalent autoimmune conditions. WHAT THIS STUDY ADDS: Most people with autoimmune diseases who required hospitalisation for COVID-19 were women, aged 50 years or older, and had substantial previous comorbidities.Patients who were hospitalised with COVID-19 and had prevalent autoimmune diseases had higher prevalence of hypertension, chronic kidney disease, heart disease, and Type 2 diabetes as compared to those with prevalent autoimmune diseases who were diagnosed with COVID-19.A variable proportion of 6% to 25% across data sources died within one month of hospitalisation with COVID-19 and prevalent autoimmune diseases.For people with autoimmune diseases, COVID-19 hospitalisation was associated with worse outcomes and 30-day mortality compared to admission with influenza in the 2017-2018 season.

14.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333532

ABSTRACT

The emergence and rapid proliferation of the novel coronavirus (SARS-CoV-2) resulted in a global pandemic, with over six million cases and nearly four hundred thousand deaths reported world-wide by the end of May 2020. A rush to find the cures prompted re-evaluation of a range of existing therapeutics vis-a-vis their potential role in treating COVID-19, placing a premium on analytical tools capable of supporting such efforts. Native mass spectrometry (MS) has long been a tool of choice in supporting the mechanistic studies of drug/therapeutic target interactions, but its applications remain limited in the cases that involve systems with a high level of structural heterogeneity. Both SARS-CoV-2 spike protein (S-protein), a critical element of the viral entry to the host cell, and ACE2, its docking site on the host cell surface, are extensively glycosylated, making them challenging targets for native MS. However, supplementing native MS with a gas-phase ion manipulation technique (limited charge reduction) allows meaningful information to be obtained on the non-covalent complexes formed by ACE2 and the receptor-binding domain (RBD) of the S-protein. Using this technique in combination with molecular modeling also allows the role of heparin in destabilizing the ACE2/RBD association to be studied, providing critical information for understanding the molecular mechanism of its interference with the virus docking to the host cell receptor. Both short (pentasaccharide) and relatively long (eicosasaccharide) heparin oligomers form 1:1 complexes with RBD, indicating the presence of a single binding site. This association alters the protein conformation (to maximize the contiguous patch of the positive charge on the RBD surface), resulting in a notable decrease of its ability to associate with ACE2. The destabilizing effect of heparin is more pronounced in the case of the longer chains due to the electrostatic repulsion between the low-p I ACE2 and the heparin segments not accommodated on the RBD surface. In addition to providing important mechanistic information on attenuation of the ACE2/RBD association by heparin, the study demonstrates the yet untapped potential of native MS coupled to gas-phase ion chemistry as a means of facilitating rational repurposing of the existing medicines for treating COVID-19. Abstract figure:

15.
16.
Acta Medica Mediterranea ; 38(2):1099-1102, 2022.
Article in English | EMBASE | ID: covidwho-1798617

ABSTRACT

Objective: In this example, the patient accidentally fell from 8 meters high, causing trauma to the patient’s chest with tracheal laceration and ‘white lung’ in both lungs. The patient lost respiratory function and was using a breathing machine with 100% pure oxygen while still maintaining 80% oxygen saturation. Routine tracheal intubation under general anaesthesia could potentially cause patient death during the operation. The objective was to assess the use of extracorporeal membrane oxygenation (ECMO) in surgery to repair the patient’s tracheal laceration. Methods: The thoracic surgery department applied hybrid surgery combined with ECMO to rescue the patient. With the support of ECMO, the patient’s intraoperative vital signs were stable, blood oxygen saturation was 100% and the surgery for repairing the laceration with fibreoptic bronchoscopy was successfully completed. Results: The patient recovered and was discharged from hospital. Conclusion: ECMO has successfully treated many critically ill COVID-19 patients during the pandemic, but this is the first time in China that ECMO has been applied to patients suffering from multiple critical injuries such as chest trauma and tracheal laceration.

17.
2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1794842

ABSTRACT

COVID-19 pandemic has a devastating impact on human health and well-being. Numerous biological tools have been utilised for COVID detection, but most of the tools are costly, time-extensive and need personnel with domain expertise. Thus, a cost-effective classifier can solve the problem where cough audio signals showed potentiality as an screening classifier for COVID-19 diagnosis. Recent ML approaches on coughbased covid-19 detection need costly deep learning algorithms or sophisticated methods to extract informative features. In this paper, we propose a low-cost and efficient envelope approach, called CovidEnvelope, which can classify COVID-19 positive and negative cases from raw data by avoiding above disadvantages. This automated approach can select correct audio signals (cough) from background noises, generate envelope around the informative audio signal, and finally provide outcomes by computing area enclosed by the envelope. It has been seen that reliable data-sets are also important for achieving high performance. Our approach proves that human verbal confirmation is not a reliable source of information. Finally, the approach reaches highest sensitivity, specificity, accuracy, and AUC of 0.96, 0.92, 0.94, and 0.94 respectively to detect Covid-19 coughs. Our approach outperformed other existing models on data pre-processing and inference times, and achieved accuracy and specificity of 0.91 and 0.99 respectively, to distinguish COVID-19 coughs from other coughs, resulted from respiratory diseases. The automatic approach only takes 1.8 to 3.9 minutes to compute these performances. Overall, our approach is fast and sensitive to diagnose the people living with COVID-19, regardless of having COVID19 related symptoms or not. In this connection, the model can be implemented easily in mobile-devices or web-based applications, and countries with poor health facilities will be highly beneficiary for covid diagnosis and measuring prognostication. © IEEE 2022.

18.
Frontiers in Physics ; 10, 2022.
Article in English | Scopus | ID: covidwho-1789413

ABSTRACT

High sensitivity and quantitative detection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein (S protein) is of great significance for the diagnosis and treatment of coronaviruses. Here, we utilized terahertz time-domain spectroscopy (THz-TDS) integrated with a metamaterial (MM)-based biosensor and biological modification technology to demonstrate a high accuracy and label-free detection of the SARS-CoV-2 S1 protein by comparing the changes of the dielectric environment before and after binding the S1 protein. To confirm the sensing characteristics observed in the experiments and provide a further insight into the sensing mechanisms, we performed numerical simulations through varying the thickness, quantity, position, and refractive index of analyte aggregates. The sensitivity increases with the increase of the number of gaps and the amount of analyte near the gaps, which convincingly proves that the frequency shift and sensing performance are strongly influenced by the field enhancement and near-field coupling at the gap area. Copyright © 2022 Niu, Zhang and Yang.

19.
IEEE Internet of Things Journal ; 2022.
Article in English | Scopus | ID: covidwho-1788751

ABSTRACT

In order to control the first wave of COVID-19 pandemic in 2020, many models have shown effectiveness in predicting the spread of new coronary pneumonia and the different interventions. However, few models can collect large amounts of high-quality real-time data faster under the premise of protecting privacy, considering the impact of SARS-CoV-2(Severe Acute Respiratory Syndrome Coronavirus 2) variant and the mass vaccination program as a new intervention. Therefore, we developed a mobile intelligent application that can collect a large amount of real-time data while protecting privacy, and conducted a feasibility study by defining a new COVID-19 mathematical model SEMCVRD. By simulating different intervention measures, the prediction model of the mobile intelligent application used in the paper simulates the epidemic situation in the UK as an example. The findings are as below: the optimal intervention strategy is to suppress the intervention at P=3 (intervention intensity: the average number of contacts per person per day) before the end of March 2021, then gradually release the intervention intensity at a rate of P+2, and finally release the intensity to P=9 in June 2021. The COVID-19 pandemic will end at the end of June 2021, when the total number of deaths will reach 128,772. This strategy will be able to balance the trade-off between loss of life and economic loss. Compared with the official statistics released by the UK government on 31st May 2021, our model can accurately predict the relative error rate of the total number of cases is less than 6.9%, and the relative error rate of the total number of deaths is less than 1%. Furthermore, the model is also suitable for collecting data from countries/regions around the world. IEEE

20.
2nd IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2022 ; : 1179-1183, 2022.
Article in English | Scopus | ID: covidwho-1788729

ABSTRACT

This experiment analyzed 100,000 epidemic-related microblogs officially provided by the CCF. Using Enhanced Representation through Knowledge Integration (ERNIE), the effect of pre-training model on extracting Chinese semantic information was improved. After that, the deep pyramid network (DPCNN) was merged with ERNIE to save computing costs. Enhanced feature extraction performance for long-distance text. This model was the most effective in the comparison test of six emotional three-category tasks, which improved the accuracy of BERT pre-training model by 7%. © 2022 IEEE.

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