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1.
Journal of Physics a-Mathematical and Theoretical ; 55(22):23, 2022.
Article in English | Web of Science | ID: covidwho-1868229

ABSTRACT

During the COVID pandemic, periods of exponential growth of the disease have been mitigated by containment measures that in different occasions have resulted in a power-law growth of the number of cases. The first observation of such behaviour has been obtained from 2020 late spring data coming from China by Ziff and Ziff in reference Ziff and Ziff (2020 Fractal kinetics of COVID-19 pandemic MedRxiv). After this important observation the power-law scaling (albeit with different exponents) has also been observed in other countries during periods of containment of the spread. Early interpretations of these results suggest that this phenomenon might be due to spatial effects of the spread. Here we show that temporal modulations of infectivity of individuals due to containment measures can also cause power-law growth of the number of cases over time. To this end we propose a stochastic well-mixed susceptible-infected-removed model of epidemic spreading in presence of containment measures resulting in a time dependent infectivity and we explore the statistical properties of the resulting branching process at criticality. We show that at criticality it is possible to observe power-law growth of the number of cases with exponents ranging between one and two. Our asymptotic analytical results are confirmed by extensive Monte Carlo simulations. Although these results do not exclude that spatial effects might be important in modulating the power-law growth of the number of cases at criticality, this work shows that even well-mixed populations may already feature non trivial power-law exponents at criticality.

2.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334871

ABSTRACT

The emerging SARS-CoV-2 variants of concern (VOCs) exhibit enhanced transmission and immune escape, reducing the efficacy and effectiveness of the two FDA-approved mRNA vaccines. Here, we explored various strategies to develop novel mRNAs vaccines to achieve safer and wider coverage of VOCs. Firstly, we constructed a cohort of mRNAs that feature a furin cleavage mutation in the spike (S) protein of predominant VOCs, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2). Not present in the mRNA vaccines currently in use, the mutation abolished the cleavage between the S1 and S2 subunits, potentially enhancing the safety profile of the immunogen. Secondly, we systematically evaluated the induction of neutralizing antibodies (nAb) in vaccinated mice, and discovered that individual VOC mRNAs elicited strong neutralizing activity in a VOC-specific manner. Thirdly, the IgG produced in mice immunized with Beta-Furin and Washington (WA)-Furin mRNAs showed potent cross-reactivity with other VOCs, which was further corroborated by challenging vaccinated mice with the live virus of VOCs. However, neither WA-Furin nor Beta-Furin mRNA elicited strong neutralizing activity against the Omicron variant. Hence, we further developed an Omicron-specific mRNA vaccine that restored protection against the original and the sublineages of Omicron variant. Finally, to broaden the protection spectrum of the new Omicron mRNA vaccine, we tested the concept of bivalent immunogen. Instead of just fusing two RBDs head-to-tail, we for the first time constructed an mRNA-based chimeric immunogen by introducing the RBD of Delta variant into the entire S antigen of Omicron. The resultant chimeric mRNA was capable of inducing potent and broadly acting nAb against Omicron (both BA.1 and BA.2) and Delta, which paves the way to develop new vaccine candidate to target emerging variants in the future.

3.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334805

ABSTRACT

Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2's immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals' plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents' plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants.

4.
Curriculum Development and Online Instruction for the 21st Century ; : 57-68, 2021.
Article in English | Scopus | ID: covidwho-1810543

ABSTRACT

Since December of 2019, every human being is exploring solutions to adapt to the "new normal" in all aspects due to the COVID-19 pandemic, and there is no exception for educators. Apart from the obstacles faced by teachers in the switching of teaching pedagogies from a physical classroom setting to different virtual platforms, there are also foreseeable challenges faced by students which might have been neglected by most studies. Semi-structured interviews have been conducted with students of UK top-up degree programmes studying in Hong Kong to explore insights of the challenges and barriers of online distance education from the students' perspectives. © 2021, IGI Global.

5.
Research Quarterly for Exercise and Sport ; 93:A59-A59, 2022.
Article in English | Web of Science | ID: covidwho-1798128
6.
2021 3rd International Conference on E-Business and E-Commerce Engineering, EBEE 2021 ; : 108-118, 2021.
Article in English | Scopus | ID: covidwho-1789024

ABSTRACT

As COVID-19 becoming a global epidemic, owing to the interventions' operation limited efficacy and virus' super transmission ability, the vaccine is considered the most potent method left to cease the COVID-19 effectively. At the beginning of the vaccine distribution policy design, there were many real concerns: vaccine priority, budget control, vaccine inventory limitation, and expected objectives making the problem complex. The research optimised the vaccine distribution policy (VDP) in an explicit form incorporated in an age-stratified SEIR model based on the proposed policy optimisation methodology. The VDP could explain when and how many vaccines to take for each age group. The designed evaluation system consisted of direct policy cost, indirect healthcare cost, and extra financial budget during the pandemic, combined as a weighted sum equalling one to suit flexible scenarios and decision-makers' requirements. A case study with ground truth data in the U.K was implemented, where the optimised VDP could decrease the comprehensive cost and suppress the virus transmission. Furthermore, the sensitivity analysis demonstrated the effect of some critical parameters for optimised VDP. The vaccination priority and policy objectives' weight combination play a significant role in impacting the VDP optimisation. The research could be a framework for flexible vaccination policy design in different scenarios by changing weights, vaccine limitations, and other initial parameter configurations. © 2021 ACM.

7.
Non-conventional in English | National Technical Information Service, Grey literature | ID: grc-753568

ABSTRACT

The funding for study EP170034 was granted to LSU Health Sciences Center (LSUHSC (Shreveport on September 15th, 2018. The study protocol was approved by the U.S. Army Medical Research and Materiel Command (USAMRMC), Office of Research Protections (ORP), Human Research Protection Office (HRPO) on June 7th, 2019. Dr. Hai Sun accepted the job offer from Rutgers University. He resigned from LSUHSC effectively on August 31st and began serving as an Associate Professor in the Department of Neurosurgery at RWJMS at Rutgers University (RU) on September 9th, 2019. The DOD and CDMRP granted the permission to transfer the study from LSUHSC to RWJMS at RU. The transfer was completed in March, 2020. Then the COVID-19 pandemic has resulted the suspension of all research effort in March. Currently RU is undergoing Phase 3 reopening and the current regulation still prohibits any research study involving face-to-face interaction with human subjects. EP170034 falls in this category. In the meantime, the IRB committee at RWJMS at RU has approved our study protocol on July 8, 2020. This continuing review of this study protocol was submitted to the USAMRDC, ORP, and HRPO on July 15, 2020. We are waiting for the permission from RU to resume research studies involving face-to-face interaction with human subjects. We have necessary study infrastructure to begin subject recruitment as soon as the permission is granted.

8.
Open Forum Infectious Diseases ; 8(SUPPL 1):S511, 2021.
Article in English | EMBASE | ID: covidwho-1746365

ABSTRACT

Background. Limited data exists regarding the impact of coronavirus disease 2019 (COVID-19) on people living with human immunodeficiency virus (PLWH). The purpose of the study was to compare the clinical outcomes of patients hospitalized with COVID-19 and HIV versus those without HIV. Methods. This was a retrospective, cohort study of adult patients admitted with confirmed COVID-19 from March 1st to May 30th 2020 at an urban hospital in New York City. Data collected included demographics, past medical history, HIV status, baseline laboratory values, treatment and outcomes such as length of stay, mechanical ventilation, patient disposition at discharge, and in-hospital mortality. Fisher's exact test was used to compare categorical values and a t-test was used to compare continuous values. Results. Out of 983 patients, 6.9% were PLWH and 93.1% were HIV-negative. The average age in both groups was 61 vs. 62 years, respectively. There were more male patients in the PLWH than the non-HIV group (76.8% vs. 58.6%). Majority of PLWH were Black (49.3%). Forty-seven percent of PLWH were mechanically ventilated versus 33.3% of the non-HIV group. The most common comorbidity in both groups was hypertension (82.4% vs. 72.6%). When compared to HIV-negative patients, PLWH had a higher rate of kidney disease (72.1% vs. 53.6%, p=0.0086), chronic obstructive pulmonary disease (41.2% vs. 14.5%, p=0.0001), liver disease (45.6% vs. 11.5%, p=0.0001) and current smoking (14.3% vs. 5.8%, p=0.0103). In PLWH, 70.6% of patients were on an integrase-based regimen. Fifty-three percent of PLWH had a CD4 count of > 200 cells/mm3 and 35.3% had an undetectable viral load (< 20 copies/mL). Unadjusted hospital mortality was 51.4% in PLWH and 36.2% in the non-HIV cohort (p=0.0089). The average length of hospital stay was 9.1 days vs. 8.4 days in PLWH versus the non-HIV group (p=0.4493). More patients were discharged to a nursing home in the non-HIV group vs. PLWH (37.8% vs. 14.3%, p=0.0001). Conclusion. Hospitalized patients with COVID-19 and HIV had a higher in-hospital mortality compared to those without HIV during the first COVID wave in New York City.

9.
2021 IEEE International Conference on Image Processing, ICIP 2021 ; 2021-September:230-234, 2021.
Article in English | Scopus | ID: covidwho-1735804

ABSTRACT

Recently, requirement of city monitoring and maintenance using ICT techniques increases with the help of transportation system. In addition, the spread of COVID-19 has increased the demand for managing pedestrian traffic volume. To contribute to these trends, in this paper, we propose a new pedestrian radar map system in order to estimate pedestrian density on streets and sidewalks. Our system uses e-bikes to collect 360-degree images and visualize pedestrian positions as a radar map. In evaluations, we confirm the accuracies of the radar maps and pedestrian density by using KITTI dataset and by carrying out a field experiment. © 2021 IEEE

11.
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS ; 28(1):242-257, 2022.
Article in Chinese | Scopus | ID: covidwho-1698657

ABSTRACT

COVID-19 has an impact on the global supply chain, which is mainly manifested in the simultaneous interruption of production capacity and demand. To explore the impact of government subsidy strategies on recovery in the context of supply chain interruption, the low-demand products during the epidemic were used as the research object, and the government's choice of subsidies for production capacity and demand interruption as a recovery strategy. The cumulative profit of supply chain members was taken as the recovery index, and system dynamics was used to construct the "manufacturer-distribution center" secondary supply chain. The changes in cumulative profits for different subsidy options were simulate under partial and complete interruption scenarios. The simulation results showed that the choice of government subsidy strategies under different interruption scenarios had different effects on the supply chain recovery effect. In the scenario of partial demand interruption, government subsidies for manufacturers with interrupted production capacity would make the supply chain recovery better. In the scenario of complete demand interruption, government subsidies for distribution centers with interrupted demand would make the supply chain recovery better. © 2022, Editorial Department of CIMS. All right reserved.

12.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326764

ABSTRACT

The SARS-CoV-2 B.1.1.529 variant (Omicron) contains 15 mutations on the receptor-binding domain (RBD). How Omicron would evade RBD neutralizing antibodies (NAbs) requires immediate investigation. Here, we used high-throughput yeast display screening1,2 to determine the RBD escaping mutation profiles for 247 human anti-RBD NAbs and showed that the NAbs could be unsupervised clustered into six epitope groups (A-F), which is highly concordant with knowledge-based structural classifications3-5. Strikingly, various single mutations of Omicron could impair NAbs of different epitope groups. Specifically, NAbs in Group A-D, whose epitope overlap with ACE2-binding motif, are largely escaped by K417N, G446S, E484A, and Q493R. Group E (S309 site)6 and F (CR3022 site)7 NAbs, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but still, a subset of NAbs are escaped by G339D, N440K, and S371L. Furthermore, Omicron pseudovirus neutralization showed that single mutation tolerating NAbs could also be escaped due to multiple synergetic mutations on their epitopes. In total, over 85% of the tested NAbs are escaped by Omicron. Regarding NAb drugs, the neutralization potency of LYCoV016/LY-CoV555, REGN10933/REGN10987, AZD1061/AZD8895, and BRII-196 were greatly reduced by Omicron, while VIR-7831 and DXP-604 still function at reduced efficacy. Together, data suggest Omicron would cause significant humoral immune evasion, while NAbs targeting the sarbecovirus conserved region remain most effective. Our results offer instructions for developing NAb drugs and vaccines against Omicron and future variants.

13.
8th IEEE International Conference on Behavioural and Social Computing, BESC 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1685060

ABSTRACT

COVID-19, a global pandemic, has provided a unique background for examining the commonalities and differences in the rules of public mood change under different cultures. This study used China and the United States as the representative countries of tight and loose cultures, respectively. We constructed an attention index of the pandemic and five emotion indexes of China and the US, respectively, to examine the commonness of human emotional responses to crises and the gradual change law among different types of emotions, and the influence of tight-loose cultures on various kinds of public emotions. The trend data of Baidu Index and Google Trends was collected for a three-step analysis. First, the time series chart of the attention index and public emotion index of the COVID-19 pandemic in the two countries were compared;Second, the Granger causality test was used to analyze the relationship among different types of emotions. Finally, the differences in the proportion of various emotional indexes during the outbreak period between China and the US were compared using the t-test. The results showed that in both countries, fear was the dominant emotion at the beginning of the pandemic, and it was gradually taken over by depression and sadness. We also found that fear and anger can be used to predict sadness and depression in the middle and long term. Moreover, our data showed that the proportion of anger and fear in China was significantly higher than that in the US, while the proportion of sadness in China was significantly lower. The positive emotion index was significantly higher in China than in the US. The results can relatively verify the response to stress at the group level and the psychological characteristics of tight-loose cultures, which to some extent can be used as a general reference for crisis psychological assistance under different cultures. © 2021 IEEE

14.
3rd IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2021 ; : 301-308, 2021.
Article in English | Scopus | ID: covidwho-1672708

ABSTRACT

The purpose of this study is to review pandemics-related publications that help aviation industry cope with pandemics outbreak like COVID-19. Published documents were searched and downloaded from academic libraries including Web of Science for a qualitative analysis. A reference list extracted from governmental publications for decision-makers, researchers, and program executives was provided. Important research clusters were visually generated based on VOSviewer process. Some research clusters were further discussed for a thorough understanding of the existing research perspectives. © 2021 IEEE

15.
Journal of Geo-Information Science ; 23(11):1924-1925, 2021.
Article in Chinese | Scopus | ID: covidwho-1643912

ABSTRACT

The COVID-19 epidemic poses a great threat to public health and people's lives, which has initiated new challenges to the prevention and control system of the epidemic in China. In all efforts for epidemic control and prevention, predicting the risk of epidemic spread is of great practical importance for scientific prevention and control, and precise strategies. To predict the risk of an epidemic rapidly and quantitatively, this paper fused multi-source spatiotemporal data and established a risk prediction model for epidemic transmission by coupling LSTM algorithm and cloud model. Firstly, a simulation model of the spatiotemporal spread of infectious diseases was built based on GIS and LSTM algorithm, which simulated the infectious disease's spatiotemporal transmission process by learning rules in historical epidemic data. At the same time, to improve the simulation accuracy, this paper took 1 km × 1 km for the spatial scale, and days for the temporal scale as the study scale. Secondly, this paper applied the simulated data of infectious cases and the spatiotemporal influence factors on the spread of the epidemic to construct risk evaluation indicators. Finally, the cloud model and adaptive strategies were applied to construct an epidemic risk assessment model. In this way, the epidemic risk assessment at multiple spatial scales was achieved. In the empirical study phase, based on the Beijing COVID-19 epidemic data from 11 June 2020 to 25 June 2020, this paper simulated the process of the spatial evolution of the epidemic from 26 June 2020 to 1 July 2020. To test the advantage of the LSTM model applied to simulate spatiotemporal spread of infectious diseases, four machine learning models were introduced for comparison, including GA-BP Neural Network, Decision Regression Tree, Random Forest, and Support Vector Machine. The results were as follows: ① Compared with other conventional machine learning models, the LSTM model with time-series relationship had higher simulation accuracy (MAE=0.002 61) and better fitting degree (R-Square=0.9455). This showed that the LSTM model considering the temporal relationship between epidemic data was more suitable for epidemic spatial evolution simulation. ② The application results showed that the coupled model can not only fully consider the influence of infection source factors, weather factors, epidemic spread factors and epidemic prevention factors on the spread of transmission risk and reflect the trend of risk evolution, but also quickly quantify regional risk levels. Therefore, the coupled model based on LSTM algorithm and cloud model can effectively predict the transmission risk of epidemic, and also provide a method reference for establishing spatial-temporal transmission models and assessing epidemic risk. 2021, Science Press. All right reserved.

16.
Circulation ; 144(SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1634724

ABSTRACT

Introduction: The COVID-19 pandemic presented an unexpected intervention to examine the association between activity and AF in patients enrolled in the TRIM-AF (Targeting Risk Interventions and Metformin for AF) clinical trial, which collects daily activity and AF burden through implanted devices. Hypothesis: We tested the hypotheses that: 1) daily activity reduction during the pandemic, compared to pre-pandemic matched periods, can be detected by implanted devices;and 2) activity reduction was associated with increased daily AF burden. Methods: Daily AF burden (%) and active minutes were obtained from manufacturers for 45 subjects (28 male, 17 female, mean age 69.5 years) enrolled in the TRIM-AF 2x2 randomized clinical trial of metformin and lifestyle/risk factor modification in patients with pacemakers/defibrillators (NCT03603912). We defined pre-pandemic and pandemic matched months for each subject, maintaining constancy of pre-vs post-randomization periods and fit a linear mixed model, including age, sex, and pandemic periods, to compare the pre-and during pandemic periods (Figure A).Results: Mean daily active minutes decreased during the pandemic from 148.6 to 144.4 mins (mixed model p =<1E-10). Mean daily AF burden increased during the pandemic from 6.0 to 8.3 (mixed model p= 3.7E-14). Both mean values were compared to matched pre-pandemic time after adjusting for sex, age, and race. AF burden % was associated with age (median AF burden increased by a factor of 1.06/year of age, mixed model p= 1.38E-02) as expected. AF daily duration percent was negatively correlated with the daily active minutes as seen by the Kendall's rank correlation tau is-0.037 (z =-7.6232, p-value = 2.474e-14). Conclusions: The data suggests that activity decreased and device-detected AF burden increased during the pandemic. Further analyses could compare results to historical trends within these patients.

17.
Gastroenterology ; 160(6):S-850-S-851, 2021.
Article in English | EMBASE | ID: covidwho-1597961

ABSTRACT

INTRODUCTION: Patients with coronavirus disease (COVID -19) and comorbid conditions such as obesity and diabetes are known to have worse disease outcomes. Metabolic syndrome is considered a major risk factor for both fatty liver and COVID-19. Patients with coronavirus may have transaminitis and fatty liver could exacerbate the SARS-CoV-2 cytokine storm. Our study aims to assess the association between the presence of fatty liver on outcomes of COVID-19 infection with acute liver injury. Methods: We conducted a retrospective observational study between March to June 2020. All hospitalized adults with a positive SARS CoV-2 PCR and an abdominal ultrasound (USG) performed during the index admission were included. The indication of the USG was for the evaluation of transaminitis. We extracted demographic data, laboratory parameters, and imaging studies from the electronic medical record. We also reviewed for sonographic features indicative of portal hypertension. We compared COVID-19 patients with and without fatty liver on USG of the abdomen. Results: There were a total of 29 COVID-19 positive patients from which 17 (58%) had fatty liver. There were no significant differences observed between the two groups in terms of demographics, comorbidities, and initial laboratory parameters except ferritin level (1105 vs 600, p = 0.0379) (Table 1). There were no significant differences with regards to other related serological markers (e.g. CRP, LDH, d-dimer). Both groups were comparable for sonographic signs of portal hypertension. A notable proportion of patients in the fatty liver group required mechanical ventilation during their hospital course (47% vs 16.7%, p = 0.1261) and had increased mortality (41.2% vs 16.7%. p = 0.2341) but these findings did not reach statistical significance. There was no difference in the length of stay between both groups. On multivariate analysis (Table 2), there was no association between fatty liver and mortality. Conclusion: We observed that COVID-19 patients with fatty liver disease are prone to worse outcomes, and this is likely independent of underlying metabolic syndrome. Preliminary results of our study did not meet statistical significance, however, data trajectory suggests a possible association that could yield significance as more patients are recruited and the study power increases. Furthermore, ferritin is a marker of immune dysregulation and an acute phase reactant, known to be elevated in severe COVID-19. Hyperferritinemia in our cohort of patients with fatty liver disease further validates a severe COVID-19 course compared to those without fatty liver disease. (Table presented.)

18.
Gastroenterology ; 160(6):S-187-S-188, 2021.
Article in English | EMBASE | ID: covidwho-1596376

ABSTRACT

Introduction: Hyperlipasemia and its clinical significance in patients with COVID-19 (CoronavirusDisease 2019) has not been widely reported. Angiotensin-converting enzyme 2(ACE-2) receptors are expressed in the pancreas and a direct viral cytopathic effect resultingin pancreatic injury with SARS CoV-2 (Severe Acute Respiratory Syndrome Corona Virus-2) infection has been hypothesized. In this study, we present the largest retrospective cohortstudy to date, evaluating the significance of hyperlipasemia in patients with COVID-19.Methods: All hospitalized adults with a positive SARS CoV-2 PCR (Polymerase ChainReaction) test from March 09 to June 30, 2020, and a serum lipase level drawn on admissionwere included in our study. Hyperlipasemia is defined as a lipase level above the upperlimit of normal. Data was extracted from our electronic medical records. Statistical analysiswas performed using the SAS statistical software v. 9.4 (SAS Institute, Cary, NC, USA).Mean and standard deviations were generated for continuous variables. Frequencies andproportions were reported for categorical variables. The Student t test and the Chi-squaretest were performed for the analysis of continuous or categorical variables respectively. Alltests were 2-sided, with a statistical significance set at p < 0.05. The logistic regressionmodel was used to quantify the association between lipase levels and clinical outcomes suchas the need for mechanical ventilation and deathResults: There were a total of 900 COVID-19 positive patients, of which 282 (31.3%) hadhyperlipasemia on admission (Table 1). We compared patients with normal lipase withthose with hyperlipasemia. There were no significant differences observed between the twogroups in terms of demographic, comorbidities, presenting symptoms and widely reportedserological markers known to indicate disease severity in COVID-19. In our multivariableadjustedmodel (table 2), elevated lipase was not significantly associated with the need formechanical ventilation or in-hospital mortality. A majority of our patients had mild elevationin lipase levels. Additionally, individuals who had hyperlipasemia (49 patients 5.4%) exceeding3 times the upper limit of normal (>183 U/L), did not meet the diagnostic criteria foracute pancreatitis.Conclusion: Hyperlipasemia in COVID-19 patients was not associated with poor clinicaloutcomes such as prolonged hospital course, or need for mechanical ventilation, or death.Patients with significantly elevated lipase levels did not meet diagnostic criteria for acutepancreatitis. Our study raises a broad range of possibilities for elevated lipase in patientswith COVID-19, ranging from global hypoxemia, hypoperfusion of pancreas and bowel, inaddition to renal failure. However, hyperlipasemia was not a predictor of disease severityor clinical outcomes in COVID-19 patients.(Table Presented)(Table Presented)

19.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-293591

ABSTRACT

To effectively track and eliminate COVID-19, it is critical to develop tools for rapid and accessible diagnosis of actively infected individuals. Here, we introduce a single-walled carbon nanotube (SWCNT)-based optical sensing approach towards these ends. We construct a nanosensor based on SWCNTs noncovalently functionalized with ACE2, a host protein with high binding affinity for the SARS-CoV-2 spike protein. Presence of the SARS-CoV-2 spike protein elicits a robust, two-fold nanosensor fluorescence increase within 90 min of spike protein exposure. We characterize the nanosensor stability and sensing mechanism, and passivate the nanosensor to preserve sensing response in saliva and viral transport medium. We further demonstrate that these ACE2-SWCNT nanosensors retain sensing capacity in a surface-immobilized format, exhibiting a 73% fluorescence turn-on response within 5 s of exposure to 35 mg/L SARS-CoV-2 virus-like particles. Our data demonstrate that ACE2-SWCNT nanosensors can be developed into an optical tool for rapid SARS-CoV-2 detection. Abstract Figure:

20.
Computers ; 10(11), 2021.
Article in English | Scopus | ID: covidwho-1526807

ABSTRACT

For public safety and physical security, currently more than a billion closed-circuit televi-sion (CCTV) cameras are in use around the world. Proliferation of artificial intelligence (AI) and machine/deep learning (M/DL) technologies have gained significant applications including crowd surveillance. The state-of-the-art distance and area estimation algorithms either need multiple cameras or a reference object as a ground truth. It is an open question to obtain an estimation using a single camera without a scale reference. In this paper, we propose a novel solution called E-SEC, which estimates interpersonal distance between a pair of dynamic human objects, area occupied by a dynamic crowd, and density using a single edge camera. The E-SEC framework comprises edge CCTV cameras responsible for capturing a crowd on video frames leveraging a customized YOLOv3 model for human detection. E-SEC contributes an interpersonal distance estimation algorithm vital for monitoring the social distancing of a crowd, and an area estimation algorithm for dynamically determining an area occupied by a crowd with changing size and position. A unified output module generates the crowd size, interpersonal distances, social distancing violations, area, and density per every frame. Experimental results validate the accuracy and efficiency of E-SEC with a range of different video datasets. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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