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1.
Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University ; 56(5):43-53, 2022.
Article in Chinese | Scopus | ID: covidwho-1876106

ABSTRACT

To study the spreading mechanism and risk and predict the spreading trend of COVID-19, and provide supports for the government to formulate prevention and control policies, a new nonlinear dynamic model, i.e., the susceptible-low risk-exposed-infectious-removed (SLEIR) model is proposed, and the population with protection measures is regarded as a low-risk group and included into this model. The basic reproduction number, equilibrium, stability and bifurcation are analyzed to reveal the spreading mechanism, and the data on COVID-19 in India is used for least-squares fitting of model parameters and some initial values. The fitted parameters are used to predict the spreading trend in India. Predicting results show that the average relative errors of the epidemic prediction are 4.107% and 2.805% from March to April and from April to May, respectively. For the latest epidemic prediction of India in October, the average relative error is 3.266%. These simulations indicate that the proposed model can accurately predict COVID-19 spreading in India, is more suitable for analyzing its spreading in India with higher prediction accuracy compared with the traditional SEIR model, and can provide technical support for the government of India to select prevention and control measures. © 2022, Editorial Office of Journal of Xi'an Jiaotong University. All right reserved.

2.
Embase; 2021.
Preprint in English | EMBASE | ID: ppcovidwho-336024

ABSTRACT

Background: Continued SARS-CoV-2 infections and COVID-19-related hospitalizations highlight the need for effective anti-viral treatments in the outpatient setting. In a descriptive interim analysis of the phase 1/2 portion of a double-blind phase 1/2/3 trial in COVID-19 outpatients conducted between June 16, 2020 and September 4, 2020, REGEN-COV® (casirivimab plus imdevimab) antibody combination reduced SARS-CoV-2 viral load versus placebo. Methods: This final phase 1/2 analysis comprises 799 outpatients, including 275 from the previous descriptive analysis (group-1) and 524 from phase 2 (group-2). Patients were randomized (1:1:1) to placebo, REGEN-COV 2400mg, or REGEN-COV 8000mg. Prespecified hierarchical analyses of virologic endpoints were performed in group-2. The proportion of patients with ≥1 COVID-19-related medically attended visit (MAV) through day 29 was assessed in group-1+2. Efficacy was assessed in patients confirmed SARS-CoV-2-positive by baseline nasopharyngeal RT-qPCR. Safety was assessed in all treated patients. Results: Data from 799 outpatients enrolled from June 16, 2020 to September 23, 2020 are reported. Time-weighted average daily reduction in viral load through day 7 was significantly greater in the REGEN-COV combined 2400mg+8000mg group versus placebo in patients with baseline viral load >107 copies/mL (prespecified primary endpoint): -0.68 log10 copies/ml (95% CI, -0.94 to -0.41;P<.0001). This reduction was - 0.73 (P<.0001) and -0.36 (P=.0003) log10 copies/mL in serum antibody-negative patients and in the overall population, respectively. REGEN-COV reduced the proportion of patients with ≥1 COVID-19-related MAV versus placebo (2.8% [12/434] REGEN-COV combined dose group versus 6.5% [15/231] placebo;P=.024;relative risk reduction [RRR]=57%);in patients with ≥1 risk factor for hospitalization, the treatment effect was more pronounced (RRR=71%). Adverse events were similar across groups. Conclusions: In COVID-19 outpatients enrolled prior to the widespread circulation of delta and omicron variants, treatment with REGEN-COV significantly reduced viral load and COVID-19-related MAVs.

3.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-335579

ABSTRACT

Background: The impact of chronic health conditions (CHC) on serostatus post-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination is unknown. Methods: We assessed serostatus post-SARS-CoV-2 vaccination among fully vaccinated participants recruited between April 2021 through August 2021 in 18 years and older residents of Jefferson County, Kentucky, USA. Serostatus was determined by measuring SARS-CoV-2 Spike protein specific immunoglobulin (Ig) G (Spike IgG) antibodies via enzyme-linked immunoassay (ELISA) in peripheral blood samples. Results: Of the 5,178 fully vaccinated participants, 51 were seronegative and 5,127 were seropositive. Chronic kidney disease (CKD) (OR=13.49;95% CI: 4.88–37.3;P<0.0001) and autoimmune disease (OR=11.34;95% CI: 5.21–24.69;P<0.0001) showed highest association with negative serostatus in fully vaccinated participants. The absence of any CHC was strongly associated with positive serostatus (OR=0.37;95% CI: 0.19–0.73;P=0.003). The risk of negative serostatus increased in the presence of two CHCs (OR=2.82;95% CI: 1.14–7) to three or more CHCs (OR=4.52;95% CI: 1.68–12.14). Similarly, use of 2 or more CHC related medications was significantly associated with seronegative status (OR=6.08;95%: 2.01–18.35). Conclusions: Presence of any CHC, especially CKD or autoimmune disease, increased the likelihood of seronegative status among individuals who were fully vaccinated to SAR-CoV-2. This risk increased with a concurrent increase in number of comorbidities, especially with multiple medications. Absence of any CHC was protective and increased the likelihood of a positive serological response post-vaccination. These results will help develop appropriate guidelines for booster doses and targeted vaccination programs.

4.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333769

ABSTRACT

Early life SARS-CoV-2 vaccination has the potential to provide lifelong protection and achieve herd immunity. To evaluate SARS-CoV-2 infant vaccination, we immunized two groups of 8 infant rhesus macaques (RMs) at weeks 0 and 4 with stabilized prefusion SARS-CoV-2 S-2P spike (S) protein, either encoded by mRNA encapsulated in lipid nanoparticles (mRNA-LNP) or mixed with 3M-052-SE, a TLR7/8 agonist in a squalene emulsion (Protein+3M-052-SE). Neither vaccine induced adverse effects. High magnitude S-binding IgG and neutralizing infectious dose 50 (ID 50 ) >10 3 were elicited by both vaccines. S-specific T cell responses were dominated by IL-17, IFN- gamma , or TNF- alpha . Antibody and cellular responses were stable through week 22. The S-2P mRNA-LNP and Protein-3M-052-SE vaccines are promising pediatric SARS-CoV-2 vaccine candidates to achieve durable protective immunity. ONE-SENTENCE SUMMARY: SARS-CoV-2 vaccines are well-tolerated and highly immunogenic in infant rhesus macaques.

5.
Global Mental Health ; 2022.
Article in English | EMBASE | ID: covidwho-1768726

ABSTRACT

The COVID-19 pandemic caused significant psychological consequences among the public, especially for people in the epicenter. This study examined the "bull's eye" model by comparing the level of psychological distress and the effect of different stressors in Wuhan (the original epicenter) with that in the surrounding areas in Hubei Province during the pandemic. Data were obtained from a cross-national survey of 10,478 respondents between the ages of 18 and 80 years in Hubei Province during the peak of the pandemic. Results of the ordinary least squares regression models showed that Wuhan residents experienced more psychological distress than those in the surrounding areas. Social and economic problems caused by the pandemic, risk exposure, perceived discrimination, and information-seeking behaviors were positively associated with distress. Social assistance was negatively associated with distress. Findings were consistent with the bull's eye model by revealing both a higher level of psychological distress and a stronger effect of stressors among the Wuhan residents than with those in low-risk areas. Thus, policymakers and psychological workers should provide adequate psychological services in high-risk areas. Lowering risk exposure, reducing discrimination against people in the epicenter, and improving information quality are essential to alleviate their psychological distress.

6.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-331257

ABSTRACT

The number of mutations in the omicron (B1.1.529) BA.1 variant of concern (VOC) led to an unprecedented evasion of vaccine induced immunity. However, despite the remarkable rise in global infections, severe disease and death did not increase proportionally, linked to persistent recognition of BA.1 by T cells and non-neutralizing opsonophagocytic antibodies. Yet, the emergence of a new sublineage, BA.2, that is more transmissible compared to BA.1, despite relatively preserved neutralizing antibody responses, has raised the possibility that BA.2 may evade other vaccine induced responses that may be key to protection against infection and disease. Here we comprehensively profiled the BNT162b2 vaccine induced response to several VOCs including the omicron BA.1 and BA.2, after the primary vaccine series, 8 months following vaccination, and after a boost. While vaccine induced immune responses were compromised against both Omicron sublineages, vaccine induced antibody isotype titers, FcγR3a- and FcγR3breceptor binding levels, and non-neutralizing opsonophagocytic functions were significantly attenuated to the omicron BA.2 Spike compared to the BA.1 lineage. Conversely, FcγR2a and FcγR2b binding was elevated to BA.2 potentially contributing to persistent protection against severity of disease. These data point to an attenuation of particular non-neutralizing antibody properties that may be key to protection against transmission, but the maintenance of others that may continue to confer protection against disease.

7.
Journal of Virology ; 96(1):11, 2022.
Article in English | Web of Science | ID: covidwho-1756184

ABSTRACT

Over the past 20 years, the severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and SARS-CoV-2 emerged, causing severe human respiratory diseases throughout the globe. Developing broad-spectrum drugs would be invaluable in responding to new, emerging coronaviruses and to address unmet urgent clinical needs. Main protease (Mpro;also known as 3CL(pro)) has a major role in the coronavirus life cycle and is one of the most important targets for anti-coronavirus agents. We show that a natural product, noncovalent inhibitor, shikonin, is a pan-main protease inhibitor of SARS-CoV-2, SARS-CoV, MERS-CoV, human coronavirus (HCoV)-HKU1, HCoV-NL63, and HCoV-229E with micromolar half maximal inhibitory concentration (IC50) values. Structures of the main protease of different coronavirus genus, SARS-CoV from the betacoronavirus genus and HCoV-NL63 from the alphacoronavirus genus, were determined by X-ray crystallography and revealed that the inhibitor interacts with key active site residues in a unique mode. The structure of the main protease inhibitor complex presents an opportunity to discover a novel series of broad-spectrum inhibitors. These data provide substantial evidence that shikonin and its derivatives may be effective against most coronaviruses as well as emerging coronaviruses of the future. Given the importance of the main protease for coronavirus therapeutic indication, insights from these studies should accelerate the development and design of safer and more effective antiviral agents. IMPORTANCE The current pandemic has created an urgent need for broad-spectrum inhibitors of SARS-CoV-2. The main protease is relatively conservative compared to the spike protein and, thus, is one of the most promising targets in developing anticoronavirus agents. We solved the crystal structures of the main protease of SARSCoV and HCoV-NL63 that bound to shikonin. The structures provide important insights, have broad implications for understanding the structural basis underlying enzyme activity, and can facilitate rational design of broad-spectrum anti-coronavirus ligands as new therapeutic agents.

8.
Annals of Emergency Medicine ; 78(4):S21, 2021.
Article in English | EMBASE | ID: covidwho-1734164

ABSTRACT

Study Objectives: emergency department (ED) health care workers (HCW) have experienced extensive mental health burdens in the fight against COVID-19. This study measured depressive symptoms in ED HCW in Brooklyn, New York, at the peak 2020 COVID-19 pandemic. Methods: An email-distributed survey of ED HCW at Maimonides Medical Center was conducted September 8–December 31, 2020, with reference period March-May 2020. Depressive symptoms were measured by the 10- item depressive symptom scale, Centers for Epidemiologic Studies-Depression (CES-D). CES-D items were summed, with a possible total score of 0-30. A CES-D score >10 was deemed clinically relevant. Our main predictor was HCW status, which was dichotomized as clinical (MD/DO, nurses, ED technicians) vs non-clinical. Covariates included sex, age, race, SARS-CoV-2 testing status (not tested vs +test vs -test), social support (range: 0->=4 people to talk to), number of COVID-related home problems (range: 0-9), mental health care disruption during COVID-19 (yes/no), 3-item Loneliness Brief Survey (LBF) score (range: 3-9), and survey date. General linear regression and logistic regression analysis were used to predict CES-D score (β- coefficient, p-value) and clinically relevant depressive symptoms (Odds Ratio (OR), 95% Confidence Interval (95% CI)), respectively. A p-value<0.05 was considered significant. Results: Among 222 HCW respondents, the mean age was 38.2±10.8y;and 59.4% were White, 52.5% were male, 80.1% were clinical HCW (38.5% MD/DO, 29.7% nurses, 31.8% ED technicians), and 61.6% tested for SARS-CoV-2. The mean CES-D score was 11.8±8.2. A clinically relevant depressive symptom burden was reported by 51.6% of HCW-55.4% of clinical HCW vs 36.4% of non-clinical HCW (p=0.024). There was no difference in the odds of clinically relevant depressive symptoms by type of clinical HCW (MD/DO, nurses, ED technicians) compared to non-clinical HCW;and no difference in mean CES-D score by clinical vs non-clinical HCW status. Increasing CES-D scores were also observed with increasing age (β=0.12, p=0.01), number of COVID-19-related home problems (β=0.99, p=0.035), and LBF score (β= 2.17, p<0.0001). A clinically-relevant depressive symptom burden was also observed with increasing age (OR 1.07, 95% CI 1.03-1.11), among those who reported increasing COVID-19-related home problems (OR 1.46, 95% CI 1.01-2.11), and LBF score (OR 2.08, 95% CI 1.63-2.65). Conclusions: Over half of clinical HCW experienced a clinically relevant depressive symptom burden during the peak of the COVID-19 pandemic. Age, number of COVID-19-related home problems, and loneliness were also associated with higher depressive symptom burden. To deepen our understanding of mental health outcomes, create effective interventions, and promote mental health-related policy changes, such as expanding insurance coverage for mental health care, temporal associations between mental health outcomes and associated factors must continue to be investigated.

9.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-311782

ABSTRACT

Background: Mental health symptoms in Emergency Department healthcare workers were measured in Brooklyn, New York, a COVID-19 epicenter.Methods: An email-distributed survey of Emergency Department healthcare workers was conducted September–December, 2020. Primary outcomes included symptoms of depression, psychological distress, perceived stress, and post-traumatic stress disorder (PTSD). Primary predictors included gender, age, race, healthcare worker status, SARS-CoV-2 testing, number of people to talk to, COVID-19-related home problems, mental health care interruption during COVID-19, loneliness, and survey date. Multivariable-adjusted linear regression analyses predicted continuous scores (b-coefficient, p-value). Multivariable-adjusted logistic regression analyses modelled likelihoods of clinically-relevant symptom burdens (Odds Ratio (OR) 95%Confidence Interval (95%CI)).Findings: Of 774 healthcare workers, 247 (31.9%) responded (mean age, 38.2±10.8 years;59.4% White;52.5% men;80.1% clinical;61.6% SARS-CoV-2 tested). Clinically-relevant symptom burdens were observed for psychological distress (35.8% clinical vs 13.8% non-clinical healthcare workers (p=0.019);and suggested for depression (53.9% clinical vs 35.7% non-clinical, p=0.072);perceived stress (63.6% clinical vs 44.8% non-clinical, p=0.053);and PTSD (18.2% clinical vs 3.6% non-clinical, p=0.064). Higher odds of clinically-relevant depression, perceived stress, and PTSD symptoms were observed for clinical vs non-clinical healthcare workers (ORs>1.0, 95%CI>1.00 lower limit). Increasing age, number of COVID-19-related home problems and people to talk to, loneliness and mental health care interruption were adversely associated with mental health (p<0.05);being male and SARS-CoV-2 testing were beneficial.Interpretation: COVID-19-related mental health burden was amplified among Emergency Department healthcare workers in Brooklyn.Funding: Maimonides Research Foundation;the NIH/National Heart, Lung and Blood Institute/National Institute on Aging, 3U01 HL146202 02S2.Declaration of Interest: None to declare. Ethical Approval: This protocol was approved by the Maimonides Medical Center institutional review board, and deemed exempt because the survey was anonymous and did not contain personal identifiers.

10.
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.

11.
12th International Conference on E-business, Management and Economics, ICEME 2021 ; : 409-414, 2021.
Article in English | Scopus | ID: covidwho-1574358

ABSTRACT

The Centralized Procurement System of Medical Consumables leads to a cliff price reduction of a large number of high-value medical consumables and has long-term impacts on public hospitals that cannot be ignored. Both descriptive statistics and qualitative analysis methods were applied in this study to explore some practical problems caused by the CPSMC from the perspective of economics. The conclusions of this study are as follows: 1) China's per capita health expenditure, per capita healthcare expenditure, and basic medical insurance fund expenditure have been growing rapidly since 2010. It is a general trend to seek a more sustainable way of medical consumables procurement. 2) The percentage of medical materials income in the medical income of public hospitals is increasing year by year. The promotion of zero makeup for consumables and the Centralized Procurement System (CPS) may have negative impacts on the profitability of some public hospitals. 3) The Chinese doctors in public hospitals have been underpaid for a long time. Due to the superposition of the COVID-19 epidemic and the CPS, the salary of some doctors are also facing a significant decline in a short term. 4) Doctors cannot get reasonable income compensation in the long-term heavy medical work, which may lead to negative impacts such as the decline of work enthusiasm and the changes of medical types and medical processes. The conclusions of this paper will help decision-making departments and relevant groups to deepen the comprehensive understanding and judgment of the impacts of the CPS, improve the corresponding compensation mechanism and regulatory system, and promote a sustainable and healthy development of the CPS. © 2021 ACM.

14.
J Endocrinol Invest ; 45(4): 859-864, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1540318

ABSTRACT

PURPOSE: Erectile dysfunction and COVID-19 share similar risk factors, including vascular disruption of integrity, cytokine release, cardiovascular disease, diabetes and obesity. The aim of this study was to investigate the association between erectile dysfunction and COVID-19 patients. METHODS: Odds ratio for erectile dysfunction in patients with a history of COVID-19 with and without comorbidities were calculated using a patients' registry platform i2b2. ICD-10 diagnoses codes were accessed for queries and data were analyzed using logistic regression. RESULTS: Patients with COVID-19 were 3.3 times more likely to have erectile dysfunction with 95% CI (2.8, 3.8). The association became stronger with odds ratio 4.8 (95% CI (4.1, 5.7)) after adjusting for age groups. The odds ratio remained the same after adjusting for smoking status with 3.5 (95% CI (3.0, 4.1)). After adjusting for race, COVID-19 patients were 2.6 (95% CI (2.2, 3.1)) times more likely to have erectile dysfunction. The odds ratio were 1.6, 1.8, 1.9 and 2.3 after adjusting for respiratory disease, obesity, circulatory disease and diabetes, respectively. CONCLUSION: COVID-19 and erectile dysfunction are strongly associated even after adjustment for known risk factors and demographics.


Subject(s)
COVID-19/epidemiology , Erectile Dysfunction/epidemiology , Adult , Aged , COVID-19/complications , Comorbidity , Erectile Dysfunction/etiology , Humans , Male , Middle Aged , Odds Ratio , Prevalence , Risk Factors
15.
Journal of Communications and Networks ; 23(5):314-325, 2021.
Article in English | Web of Science | ID: covidwho-1524836

ABSTRACT

The coronavirus pandemic has been declared a world health emergency by the World Health Organization, which has raised the importance of an accurate epidemiological model to predict the evolution of COVID-19. In this paper, we propose mean field evolutionary dynamics (MFEDs), inspired by optimal transport theory and mean field games on graphs, to model the evolution of COVID-19. In the MFEDs, we derive the payoff functions for different individual states from the commonly used replicator dynamics (RDs) and employ them to govern the evolution of epidemics. We also compare epidemic modeling based on MFEDs with that based on RDs through numerical experiments. Moreover, we show the efficiency of the proposed MFED-based model by fitting it to the COVID-19 statistics of Wuhan, China. Finally, we analyze the effects of one-time social distancing as well as the seasonality of COVID19 through the post-pandemic period.

16.
American Journal of Transplantation ; 21(SUPPL 4):299, 2021.
Article in English | EMBASE | ID: covidwho-1494445

ABSTRACT

Purpose: Wearable devices that measure physiological parameters have shown utility for detecting infections such as influenza and recently COVID-19 up to 10 days before clinical symptoms appear. Combining symptom data with wearable biosensor data has proven to increase discrimination between COVID-19 and non-COVID-19 infection compared to using symptom data alone (AUC 0.80 vs. 0.71, p<0.01). Here we study the utility of wearable devices in early detection of SARS-Cov2 and related infections in pediatric solid organ transplant recipients. Early remote detection of infections may guide treatment responses to improve clinical outcomes such as rates of hospitalization. Methods: This is an ongoing prospective cohort study of pediatric solid organ transplant recipients and their non-transplanted household members. We are currently remotely recruiting all participants from multicenter sites and heart, liver and lung transplant patients from a single transplant center. We continuously monitor heart rate (HR), body temperature, oxygen saturation, blood pressure, sleep and respiratory patterns, and electro-dermal activity. We use MyPHD, a HIPAA compliant information architecture that supports EHR integration, for remote patient recruitment, secure data collection, and analyses. We apply two real-time algorithms to the data to identify changes that are associated with COVID-19. The algorithms are based on Resting Heart-Rate-Difference (RHR-Diff) and identify periods of elevated HR based on outlier interval detection, calculating standardized residuals for each HR observation compared to a baseline of clinically validated “healthy days” for each patient. Results: Continuous real-time physiological monitoring of transplant patients may provide syndromic surveillance and inform healthcare management. The primary outcome is time to infection diagnoses, with a particular emphasis on SARS-CoV2 and common post-transplant infections (Influenza, EBV, CMV, and BK virus). The secondary outcomes are to optimize our algorithms for the pediatric transplant setting and to monitor for other complications including cardiometabolic complications and eGFR decline. Conclusions: The potential impact of this study include algorithm-guided early detection of infection signatures coupled with provider clinical-decision-support and return-of-results to manage transplant patient care.

17.
Transp Res Part A Policy Pract ; 153: 151-170, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1415809

ABSTRACT

COVID-19 has raised new challenges for transportation in the post-pandemic era. The social distancing requirement, with the aim of reducing contact risk in public transit, could exacerbate traffic congestion and emissions. We propose a simulation tool to evaluate the trade-offs between traffic congestion, emissions, and policies impacting travel behavior to mitigate the spread of COVID-19 including social distancing and working from home. Open-source agent-based simulation models are used to evaluate the transportation system usage for the case study of New York City. A Post Processing Software for Air Quality (PPS-AQ) estimation is used to evaluate the air quality impacts. Finally, system-wide contact exposure on the subway is estimated from the traffic simulation output. The social distancing requirement in public transit is found to be effective in reducing contact exposure, but it has negative congestion and emission impacts on Manhattan and neighborhoods at transit and commercial hubs. While telework can reduce congestion and emissions citywide, in Manhattan the negative impacts are higher due to behavioral inertia and social distancing. The findings suggest that contact exposure to COVID-19 on subways is relatively low, especially if social distancing practices are followed. The proposed integrated traffic simulation models and air quality estimation model can help policymakers evaluate the impact of policies on traffic congestion and emissions as well as identifying hot spots, both temporally and spatially.

18.
Aerosol and Air Quality Research ; 21(9), 2021.
Article in English | Scopus | ID: covidwho-1399501

ABSTRACT

To study the air quality changes during the Corona Virus Disease 2019 (COVID-19) lockdown in Changchun, we analyzed the changes in pollution of six major pollutants (PM2.5, PM10, SO2, NO2, O3, CO) and correlated them with meteorological parameters, using meteorological data and pollutants concentration data. Regional transport pathways and potential source areas of pollutants were analyzed using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and Potential Source Contribution Function (PSCF). The results showed that the concentrations of PM2.5, PM10, SO2, NO2, CO were 30.5%–53.8% lower in the Level I period and 49.4%–65.0% lower in the Level II period than in the pre-lockdown period, respectively. Conversely, O3 increased 59.6% and 58.1% during Level I and Level II, respectively, compared to the pre-lockdown period. During the 55-day lockdown, daily average concentrations of each pollutant were lower than in previous years on 36-55 days, while O3 was higher on 35 days. The pollutants that decreased in concentration during the lockdown also showed an increase during the Level III period (up to 188.5%). The maximum daily growth rate of PM2.5 during the lockdown period in 2020 was 16.0%, which was higher than this value in the same period of previous years (21.8%, 21.4%, 17.4%). This shows that the change trend of pollutants during the lockdown period is smoother than in previous years. Temperature and O3 were positively correlated before the lockdown and during Level I and weakly negatively correlated during Level II and Level III. Despite the prevalence of northwest winds in winter, a high percentage of trajectories from other directions (up to 36.8%) was observed during the lockdown. Simultaneously, the lockdown reduced the potential source area for PM2.5 (WPSCF ≥ 0.000007), but rebounded after the lockdown was lifted. In conclusion, the lockdown only temporarily reduced the air pollution in Changchun. © 2021, AAGR Aerosol and Air Quality Research. All rights reserved.

19.
2021 Ieee Virtual Reality and 3d User Interfaces ; : 597-605, 2021.
Article in English | Web of Science | ID: covidwho-1365037

ABSTRACT

Recent developments in computer graphics and hardware technology enable easy access to virtual reality headsets along with integrated eye trackers, leading to mass usage of such devices. The immersive experience provided by virtual reality and the possibility to control environmental factors in virtual setups may soon help to create realistic digital alternatives to conventional classrooms. The importance of such settings has become especially evident during the COVID-19 pandemic, forcing many schools and universities to provide the digital teaching. Researchers foresee that such transformations will continue in the future with virtual worlds becoming an integral part of education. Until now, however, students' behaviors in immersive virtual environments have not been investigated in depth. In this work, we study students' attention by exploiting object-of-interests using eye tracking in different classroom manipulations. More specifically, we varied sitting positions of students, visualization styles of virtual avatars, and hand-raising percentages of peer-learners. Our empirical evidence shows that such manipulations play an important role in students' attention towards virtual peer-learners, instructors, and lecture material. This research may contribute to understanding of how visual attention relates to social dynamics in the virtual classroom, including significant considerations for the design of virtual learning spaces.

20.
Annals of Emergency Medicine ; 78(2):S20, 2021.
Article in English | EMBASE | ID: covidwho-1351478

ABSTRACT

Study Objectives: Emergency department (ED) health care workers (HCW) have experienced extensive mental health burden in the fight against COVID-19. This study measured symptoms of post-traumatic stress disorder (PTSD) in ED HCW in Brooklyn, New York, experienced during the peak of the COVID-19 pandemic. Methods: An email-distributed survey of ED HCW at Maimonides Medical Center was conducted September 8–December 31, 2020, with reference period March–May 2020. Posttraumatic stress symptoms were measured by the PTSD checklist for DSM-5 (PCL-5). A PCL-5 score >32 was deemed clinically relevant. Our main predictor was HCW status, which was dichotomized as clinical (MD/DO, nurses, ED technicians) vs non-clinical. Covariates included sex, age, race, SARS-CoV-2 testing status (not tested vs +test vs -test), social support (range: 0- >4 people to talk to), number of COVID-related home problems (range: 0-9), mental health care disruption during COVID-19 (yes/no), 3-item Loneliness Brief Survey (LBF) score (range: 3-9), and survey date. General linear regression and logistic regression analyses were used to predict PCL-5 score (β-coefficient, p-value) and clinically relevant posttraumatic stress symptoms (odds ratio (OR), 95% confidence interval (95% CI)), respectively. A p-value<0.05 was considered significant. Results: Among 247 HCW respondents, 67.1% were between 25-44 years old, 56.8% were White, 51.4% were male, 79.7% were clinical HCW (30.5% MD/DO, 22.7% nurses, 25.2% ED technicians), and 63.2% had been tested for SARS-CoV-2. The median PCL-5 score was 10. A higher mean PCL-5 score was observed for clinical vs non-clinical HCW (p<0.0001). Lower PCL-5 scores were observed for males (β=-4.31, p=0.05), while higher scores were observed in association with an increased number of COVID-19-related home problems (β=2.13, p=0.04), LBF score (β= 4.09, p<0.0001) and higher number of people to talk to (β=6.97, p=0.04). A clinically relevant PTSD symptom burden was reported by 16.6% of HCW - 18.3% of clinical HCW vs 3.6% of non-clinical HCW (p=0.0048). Higher odds of clinically relevant PTSD symptoms were observed for ED technicians compared to non-clinical HCW (OR 16.16, 95% CI 1.53-170.46). A clinically relevant PTSD symptom burden was also observed among those reporting increasing COVID-19-related home problems (OR 1.69, 95% CI 1.01-2.83) and LBF score (OR 1.83, 95% CI 1.38-2.44). Conclusions: Almost one in five clinical HCW experienced a clinically relevant PTSD symptom burden during the peak of the COVID-19 pandemic. To deepen our understanding of mental health outcomes, create effective interventions, and promote mental health-related policy changes, such as expanding insurance coverage for mental health care and developing more effective wellness programs for HCW, temporal associations between mental health outcomes and associated factors must continue to be investigated.

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