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1.
Gastroenterology ; 162(7):S-1082, 2022.
Article in English | EMBASE | ID: covidwho-1967407

ABSTRACT

Background: Real-world population-based safety data about the COVID-19 mRNA vaccine is lacking in patients with various immunocompromised conditions, including inflammatory bowel disease (IBD). Aim: To determine the incidence rates of unplanned IBD-related hospital admission and all-cause emergency attendance following BNT162B2 vaccination in IBD patients. Methods: Through the Government commissioned, territory-wide active COVID19 safety surveillance, we linked population-level vaccination records and health outcome data, between March 10 (1st day of vaccination program) and September 30, 2021, to assess the association between two-dose of BNT162b2 and unplanned IBD-related hospitalization and all-cause emergency attendance. We used inverse probability treatment weightingbased cohort study design to balance the baseline characteristics between vaccinated and unvaccinated IBD patients. Poisson regression model was fitted to estimate the adjusted incidence rate ratio (IRR) of unplanned IBD hospital admission and 28-day emergency room attendance following the vaccination, using the unvaccinated group as the reference. Results: Among more than 4.1 million citizens with successful vaccine and health record-linkage, we identified 941 IBD patients (age: 46.0 ± 15.0 years, male: 64.2%) who completed twodose of BNT162b2 and 1196 age-sex matched unvaccinated IBD patients as control (age: 49.3 ± 18.3 years, male: 58.9%). After inverse propensity weighting, all baseline demographic and clinical characteristics were well balanced (standard mean difference < 0.1;Table 1). During a median follow-up of 59-60 days (181.2 person-years for BNT162b2 group;253.6 person-years for the unvaccinated group), there was no significant difference in the risk of unplanned IBD-related hospital admission [3.31 versus 5.13 per 100 person-years, IRR: 0.75 (0.38, 1.47)] and 28-day all-cause emergency room attendance [39.1 vs 47.5 per 100 person-years, IRR: 1.08 (0.76-1.53)] between BNT162b2 recipients and unvaccinated individuals. Series of stratified analyses, including patients with Crohn’s disease (N= 378) or ulcerative colitis (N=553), who received immunosuppressants (N=454) or biologics (N= 192), all showed that receiving two-dose of BNT162b2 vaccine was not associated with a higher risk of unplanned IBD-admission and 28-day emergency attendance when compared to their counterparts without vaccination (Figure 1). Conclusion: Results from this populationbased study showed no increase in risk of unplanned IBD-related hospitalization and allcause emergency attendance following two-dose of BNT162b2 Covid-19 vaccination in patients with IBD. This observation potentially reassures the medium-term safety of mRNA vaccine in patients with IBD, although there is still possible self-selection bias in receiving the vaccine. (Table Presented) (Figure Presented)

2.
5th International Conference on Traffic Engineering and Transportation System, ICTETS 2021 ; 12058, 2021.
Article in English | Scopus | ID: covidwho-1962043

ABSTRACT

The prediction of bus passenger volume is the fundamental research content of bus transfer optimization. In order to get more accurate passenger volume data and improve the utilization efficiency of urban traffic resources, according to randomness, time-varying and uncertainty of public transport passenger volume in Beijing, combined with the current new coronavirus pneumonia epidemic, this paper collected the relevant data of Beijing in the past 40 years, and predicted and analyzed them from four dimensions of public transport, urban scale and residents' economic level, taxi and sudden health events by BP neural network and regression analysis. The results show that BP neural network has good prediction results, and BP neural network is suitable for large sample size, which needs to fit or predict complex nonlinear relationships. © 2021 SPIE

3.
IEEE Internet of Things Journal ; : 1-1, 2022.
Article in English | Scopus | ID: covidwho-1961406

ABSTRACT

Distributed Spatial Cloaking () enables users to enjoy precise Location-Based Service (LBS) with location privacy-preserving. An incentive mechanism is necessary to encourage users to cooperate. However, due to the inappropriate design of incentive mechanisms, the existing works cause low user benefits and fail to encourage users, ruining the expected incentive effect. Moreover, introducing a third party to manage users’information also causes the existing works to disclose users’privacy and be unpractical. To address these issues, we propose a utility-awaRe incEntive mechanism based diStributed spATial cloaking (RESAT). By the idea of utility theory and optimization theory, RESAT devises basic and extended incentive mechanisms. The two mechanisms for assuming that all users are honest and that malicious users provide unreasonable locations. RESAT proposes an incentive mechanism-based cloaking cooperation without a third party, incorporating the developed mechanisms based on the blind signature. Theoretical analysis indicates that RESAT achieves incentive compatibility and is secure. Extensive experiments on the real dataset show that compared with the existing works, RESAT enables 1 time more users to cooperate at best while eliminating the malicious behaviors that provide unreasonable locations. The required construction time delay is limited. IEEE

4.
Indian Journal of Pharmaceutical Sciences ; 84(3):617-630, 2022.
Article in English | EMBASE | ID: covidwho-1957666

ABSTRACT

Drug repositioning may be a promising way to find potential therapies against coronavirus disease 2019. Although chloroquine and hydroxychloroquine showed controversial results against the coronavirus disease 2019 disease, the potential common and diverging mechanisms of action are not reported and need to be dissected for better understanding them. An integrated strategy was proposed to systematically decipher the common and diverging aspects of mechanism of chloroquine and hydroxychloroquine against coronavirus disease 2019-disease network based on network pharmacology and in silico molecular docking. Potential targets of the two drugs and coronavirus disease 2019 related genes were collected from online public databases. Target function enrichment analysis, tissue enrichment maps and molecular docking analysis were carried out to facilitate the systematic understanding of common and diverging mechanisms of the two drugs. Our results showed that 51 chloroquine targets and 47 hydroxychloroquine targets were associated with coronavirus disease 2019. The core targets include tumor necrosis factor, glyceraldehyde 3-phosphate dehydrogenase, lymphocyte-specific protein-tyrosine kinase, beta-2 microglobulin, nuclear receptor coactivator 1, peroxisome proliferator-activated receptor gamma and glutathione disulfide reductase. Both chloroquine and hydroxychloroquine had good binding affinity towards tumor necrosis factor (affinity=-8.6 and -8.4 kcal/mol, respectively) and glyceraldehyde 3-phosphate dehydrogenase (-7.5 and -7.5 kcal/mol). Chloroquine and hydroxychloroquine both had good affinity with angiotensin-converting enzyme 2, 3-chymotrypsin-like protease and transmembrane serine protease 2. However, hydroxychloroquine manifested better binding affinity with the three proteins comparing with that of chloroquine. Chloroquine and hydroxychloroquine could have potential to inhibit over-activated immunity and inflammation. The potential tissue-specific regulation of the two drugs against severe acute respiratory syndrome coronavirus 2 infection may related with the lung, liver, brain, placenta, kidney, blood, eye, etc. In conclusion, our data systematically demonstrated chloroquine and hydroxychloroquine may have potential regulatory effects on coronavirus disease 2019 disease network, which may affect multiple organs, protein targets and pathways. Routine measurements of the chloroquine and hydroxychloroquine blood concentrations and tailored therapy regimen may be essential. But, further rigorous and high quality randomized controlled clinical trials are warranted to validate the antiviral effects of chloroquine and hydroxychloroquine against severe acute respiratory syndrome coronavirus 2. Our proposed strategy could facilitate the drug repurposing efforts for coronavirus disease 2019 treatment.

6.
8th International Conference on Human Aspects of IT for the Aged Population, ITAP 2022 Held as Part of the 24th HCI International Conference, HCII 2022 ; 13330 LNCS:521-540, 2022.
Article in English | Scopus | ID: covidwho-1930324

ABSTRACT

Mobile payment has become increasingly popular worldwide, especially during the COVID-19 pandemic. However, older adults have more difficulties in adapting to mobile payments than others. To understand the reasons behind this phenomenon, we explore cognitive lock-in and its antecedents in adopting WeChat Pay based on the status quo bias theory. We use the PLS-SEM technique with survey data from Chinese older adults over the age of 50. The results show that the cognitive lock-in of older adults is significantly affected by technology anxiety, habit, regret avoidance, and uncertainty costs. Moreover, older adults’ intention to adopt WeChat Pay is positively associated with social influence and self-actualization, while cognitive lock-in is a significant negative determinant. This study can help us better understand the underlying mechanism behind older adults’ adoption of mobile payment from a cognitive lock-in perspective. Furthermore, this study steers the discussion about improving older adults’ digital literacy and optimizing age-appropriate services for mobile payments. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

7.
Chinese Journal of Microbiology and Immunology (China) ; 42(3):161-170, 2022.
Article in Chinese | EMBASE | ID: covidwho-1928715

ABSTRACT

Objective To investigate the immune characteristics of SARS-CoV-2 membrane (M) protein, especially the possibility of inducing antibody-dependent enhancement effect (ADE) .Methods Full-length SARS-CoV-2 M protein was prepared by prokaryotic expression system and purified.BALB/ c mice were immunized subcutaneously three times (on day 1, day 14 and day 21) by purified M protein.Serum samples were collected before immunization and after each immunization.The specificity of immune sera against M protein was identified by Western blot, and the antibody titers were detected by ELISA and neutralization test.In the presence of anti-M protein serum, the proliferation of SARS-CoV-2 in dendritic cells, nature killer cells, T and B cells was detected in vitro.Results The immune sera from BALB/ c mice immunized with purified full-length M protein of SARS-CoV-2 specifically recognized viral M protein.The titer of anti-whole virus antibody in immune sera was about 1 ∶ 400, but the antibody could not neutralize live virus.Moreover, the antibody could not help the virus to infect and proliferate in the various types of immune cells with Fc receptor (FcR).Conclusions Non-neutralizing antibody induced by M protein could not cause ADE through FcR pathway.

8.
Computers & Electrical Engineering ; 102:14, 2022.
Article in English | Web of Science | ID: covidwho-1926336

ABSTRACT

Due to the global influenza pandemic and the increasing health problems of the elderly, healthcare for the elderly has become an important application of Internet of Things(IoT) technology. However, under the condition of smart healthcare, the privacy of the elderly is not well protected. Therefore, to ensure the information security of the elderly, this paper proposes a management method for elderly chronic diseases based on the IoT security environment, establishes a security protection mechanism, and uses the IoT technology to monitor the vital signs of the elderly in real-time. At the same time, the Disease Immune Rehabilitation Algorithm (DIRA) is constructed based on the physiological data collected by the device to identify healthy people and reduce the number of infected people. Through experiments on several generations, the results show that this method can increase the proportion of the immune population to a certain extent and reduce the number of infected people.

9.
Building Simulation ; : 14, 2022.
Article in English | Web of Science | ID: covidwho-1926088

ABSTRACT

Numerous short-term exposure events in public spaces were reported during the COVID-19 pandemic, especially during the spread of Delta and Omicron. However, the currently used exposure risk assessment models and mitigation measures are mostly based on the assumption of steady-state and complete-mixing conditions. The present study investigates the dynamics of airborne transmission in short-term events when a steady state is not reached before the end of the events. Large-eddy simulation (LES) is performed to predict the airborne transmission in short-term events, and three representative physical distances between two occupants are examined. Both time-averaged and phase-averaged exposure indices are used to evaluate the exposure risk. The results present that the exposure index in the short-term events constantly varies over time, especially within the first 1/ACH (air changes per hour) hour of exposure between occupants in close proximity, posing high uncertainty to the spatial and temporal evolutions of the risk of cross-infection. The decoupling analysis of the direct and indirect airborne transmission routes indicates that the direct airborne transmission is the predominated route in short-term events. It suggests also that the general dilution ventilation has a relatively limited efficiency in mitigating the risk of direct airborne transmission, but determines largely the occurrence time of the indirect one. Given the randomness, discreteness, localization, and high-risk characteristics of direct airborne transmission, a localized method that has a direct interference on the respiratory flows would be better than dilution ventilation for short-term events, in terms of both efficiency and cost.

10.
Neurology ; 98(18 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1925320

ABSTRACT

Objective: We evaluated clinical outcomes of myasthenia gravis (MG) patients with COVID-19 infection to determine factors associated with poor outcomes. Background: MG is an autoimmune disease affecting the neuromuscular junction. MG patients often manifest dyspnea and dysphagia and have an increased risk of infection due to immunosuppressants use, which may compound the severity of COVID-19 symptoms. A comprehensive understanding of clinical outcomes of MG-COVID patients is crucial in clinical decision making. Design/Methods: We conducted a retrospective cohort study using the Optum® de-identified COVID-19 Electronic Health Record (EHR) data. Primary outcomes include death, hospitalization, intubation, and ICU stay. We analyzed factors that may affect the outcomes such as age, sex, ethnicity, geographic region, month of COVID-19 diagnosis, comorbidities, and MG-specific treatments. Then, we compared these outcomes with non-MG COVID as well as rheumatoid arthritis (RA), systemic lupus (SLE) and multiple sclerosis (MS) with COVID-19 using a modified multivariable Poisson regression model. Results: Our study includes total of 421,086 individuals with COVID-19 among which 377 were MG-COVID. MG was not associated with increased risk of ventilator use or death but was associated with increased risk of hospitalization (aRR=1.28, 95% CI 1.13-1.46, p <0.001) and ICU stay (aRR=1.51, 95% CI 1.16-1.96, p=0.002) when accounting for the covariates in COVID-19. The mortality of the MG-COVID subgroup was 10%, and it was associated with age 75 or older (aRR=9.57, 95% CI 1.56-58.76, p=0.015) and presence of dysphagia (aRR=1.84, 95% CI 1.06- 3.21, p=0.031) but not immunosuppressants use. The MG-COVID had higher adjusted risks of hospitalization and ICU admission compared to the RA-COVID but similar to the SLE- and MS-COVID subgroups. Conclusions: Our study provides insight into how COVID-19 infection affected MG patients. Neurologists may consider these outcomes when providing MG with COVID-19 patients and their families with treatment options, vaccination counseling, and prognosis.

11.
Neurology ; 98(18 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1925309

ABSTRACT

Objective: We are investigating whether COVID-19 infection increases the propensity of developing Guillain-Barré Syndrome (GBS) or affects the clinical outcome of GBS. Background: During the pandemic, there have been many case reports and case series of GBS following COVID-19 infection. The causality of COVID-19 in these cases is not clear. There are conflicting reports regarding the incidence of GBS during the pandemic. In prior literature, clinical and electrophysiologic characteristics of GBS in COVID-19 associated cases did not differ from the previously described natural history. Design/Methods: Longitudinal electronic health record database for Optum, which included more than 4.4 million patients who underwent testing for COVID-19, was queried in May 2021 for ICD-9 and ICD-10 codes for GBS. Clinical information based on billing codes was acquired. GBS cases within 60 days of the first positive PCR test for COVID-19 were further analyzed. We also evaluated the presence of GBS in patients who tested negative for COVID 19 during the same time frame. Results: There were 725,347 patients in the database with COVID-19 diagnosis. We analyzed 844 patients with GBS, 86 of which occurred within 60 days of COVID-19 diagnosis. The incidence of GBS was not increased among the patients with recent COVID 19 diagnosis, compared to the GBS cases without COVID 19 in the same time frame. In our preliminary analysis, COVID-19 associated cases had higher mortality, intubation rates, and need for posthospital rehabilitation at a facility. Conclusions: Our preliminary analysis of this large database did not show any evidence that COVID-19 increases the propensity for developing GBS. However, when associated with COVID-19 infection, the outcomes for GBS seem to be worse. Further ongoing analyses considering covariates of age, comorbidities, and month of COVID-19 diagnosis is planned.

12.
21st IEEE International Conference on Software Quality, Reliability and Security (QRS) ; : 192-195, 2021.
Article in English | Web of Science | ID: covidwho-1915994

ABSTRACT

Academic social network sites have become an important channel by which scholars obtain academic information. In the context of the COVID-19 pandemic, the use of academic social question and answer (Q&A) online platforms is a fast and efficient means of gathering information needed to solve research problems relating to the study of COVID-19. The question then is how to provide scholars with high-quality answers. Therefore, this research focuses on studying the characteristics of high-quality answers to COVID-19 questions on academic social Q&A platforms in terms of the answer content. By analyzing 6791 answers to 349 questions about COVID-19 on ResearchGate Q&A, high-quality academic answers on this topic should be rich in content, contain more negative emotions, be fluent in the use of language, and propose conjectures or hypotheses. This research helps to improve the provision of satisfactory academic information services for scholars during public health emergencies.

13.
J Hosp Infect ; 127: 91-100, 2022 Jul 02.
Article in English | MEDLINE | ID: covidwho-1914598

ABSTRACT

BACKGROUND: Aerosol-borne diseases such as COVID-19 may outbreak occasionally in various regions of the world, inevitably resulting in short-term shortage and corresponding reuse of disposable respirators. AIM: To investigate the effective disinfection methods, reusable duration and frequency of N95 respirators. METHODS: Based on the self-built respirator simulation test system, and under combinations of experimental conditions of three N95 respirators × 0-200 nm NaCl aerosols × three simulated breathing flow rates (15, 50 and 85 L/min) × two disinfection methods (dry heating and ultraviolet (UV) radiation), this study continuously measured the changes in filtration efficiency of all respirators during multi-cycles of '8-h simulated donning + disinfection' until the penetration reached ≥5%. FINDINGS: Multi-cycles of dry heating and UV radiation treatments on the reused (i.e., multiple 8-h donning) N95 respirators had a minimal effect (<0.5%) on the respirator filtration efficiency, and even at 85 L/min, all tested N95 respirators were able to maintain filtration efficiencies ≥95% for at least 30 h or four reuse cycles of '8-h donning + disinfection', while a lower breathing flow rate (15 L/min) plus the exhalation valve could further extend the N95 respirator's usability duration up to 140 h or 18 reuse cycles of '8-h donning + disinfection'. As the respirator wearing time extended, aerosol penetration slowly increased in a quadratic function with a negative second-order coefficient, and the penetration increment during each cycle of 8-h donning was less than 0.9%. CONCLUSION: Multi-cycles of N95 respirator reuse in combination with dry heating or UV irradiation disinfection are feasible.

14.
Journal of Environmental and Occupational Medicine ; 38(6):624-630, 2021.
Article in Chinese | Scopus | ID: covidwho-1912212

ABSTRACT

[Background] The epidemic of coronavirus disease 2019 (COVID-19) seriously affects the psychological status of medical staff who directly face the risk of the disease. [Objective] This study investigates the prevalence and related factors of depression, anxiety, and insomnia among medical staff during the COVID-19 pandemic. [Methods] From February 13 to March 1, 2020, a network questionnaire survey was conducted among 482 medical staff selected by convenience sampling. A self-designed questionnaire was used to investigate the basic demographic information and COVID-19-related questions. The Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Insomnia Severity Index (ISI) were used to estimate the prevalence of depression, anxiety, and insomnia among the medical staff. Stepwise multiple linear regression analysis was performed with PHQ-9 score, GAD-7 score, and ISI score as dependent variables. Multivariate logistic regression analysis (forward-conditional method) on depression, anxiety, and insomnia as dependent variables was performed with basic demographic information and COVID-19-related questions as independent variables. [Results] Among the surveyed medical staff, the prevalence rates of depression, anxiety, and insomnia were 14.3%, 11.2%, and 23.2%, respectively. There were no significant differences in the prevalence rates among different age, gender, local risk level, and occupation groups and those aiding Hubei Province or not. The medical staff who directly contacted fever or diagnosed patients had more serious depression (b=1.73, 95%CI: 0.79-2.66) and insomnia (b=2.43, 95%CI: 1.48-3.39) and a higher risk of insomnia (OR=1.89, 95%CI: 1.21-2.96). The medical staff whose current protective measures cannot prevent infection had more serious depression (b=1.72, 95% CI: 0.65-2.80), anxiety (b=1.75, 95% CI: 0.76-2.75), and insomnia (b=1.73, 95% CI: 0.63-2.82), and had a higher risk of depression (OR=1.97, 95% CI: 1.11-3.49), anxiety (OR=3.00, 95%CI: 1.64-5.46), and insomnia (OR=1.79, 95%CI: 1.08-2.96). [Conclusion] During the COVID-19 epidemic, the risks of depression, anxiety, and insomnia among selected medical staff are increased compared with the non-epidemic period. Occupational exposure to high-risk groups and protective measures would significantly affect mental health of medical staff. © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

15.
Drug Evaluation Research ; 45(1):186-192, 2022.
Article in Chinese | Scopus | ID: covidwho-1912086

ABSTRACT

Coronavirus disease 2019 (COVID-19) is still spreading worldwide. At present, no specific drug has been developed for the virus. Ulinastatin plays an important role in anti-inflammatory. Clinically, it is mainly used in acute pancreatitis, shock and disseminated intravascular coagulation. It also has the effects of antioxidant stress, anticoagulation and immune regulation, which may be of great significance to reduce the severity and mortality of COVID-19. Combined with the pharmacological effect of ulinastatin and its clinical application in the treatment of COVID-19 complications such as acute respiratory distress syndrome and sepsis lung injury, this paper discusses the feasibility of its application in COVID-19, so as to provide help for the clinical treatment and new drug research and development of this disease. © 2022 Tianjin Press of Chinese Herbal Medicines. All Rights Reserved.

16.
FRONTIERS IN ENVIRONMENTAL SCIENCE ; 10, 2022.
Article in English | Web of Science | ID: covidwho-1911030

ABSTRACT

Changzhou, a typical industrial city located in the center of the Yangtze River Delta (YRD) region, has experienced serious air pollution in winter. However, Changzhou still receives less attention compared with other big cities in YRD. In this study, a four-month PM2.5 sampling campaign was conducted in Changzhou, China from 1 November 2019, to 1 February 2020. The period covers the entire wintertime and includes first week of the Level 1 response stage of the lockdown period due to the outbreak of COVID-19. The mean PM2.5 concentrations were 67.9 +/- 29.0 mu gm(-3), ranging from 17.4 to 157.4 mu gm(-3). Secondary inorganic ions were the most abundant species, accounting for 37 and 50% during the low and high PM2.5 pollution periods, respectively. Nitrogen oxidation ratio (NOR) during the high PM concentration level period was twice the low PM concentration period whereas sulfur oxidation ratio (SOR) showed a less significant increase. This represents that nitrate formation is potentially the predominant factor controlling the occurrence of PM pollution. The analysis of NOR, SOR as functions of relative humidity (RH) and ozone (O-3) concentrations suggest that the sulfate formation was mainly through aqueous-phase reaction, while nitrate formation was driven by both photochemistry and heterogeneous reaction. And, excess ammonium could promote the formation of nitrate during the high PM period, indicating that ammonia gas played a critical role in regulating nitrate. Furthermore, a special period-Chinese New Year overlapping first week of COVID-19 lockdown period, offered a precious window to study the impact of human activity pattern changes on air pollution variation. During the special period, the average PM2.5 mean concentration was 60.4 mu gm(-3), which did not show in a low value as expected. The declines in nitrogen oxide (NOx) emissions led to rapid increases in O-3 and atmospheric oxidizing capacity, as well as sulfate formation. The chemical profiles and compositions obtained during different periods provide a scientific basis for establishing efficient atmospheric governance policies in the future.

17.
Zhonghua Gan Zang Bing Za Zhi ; 30(5): 554-558, 2022 May 20.
Article in Chinese | MEDLINE | ID: covidwho-1911777

ABSTRACT

The COVID-19 outbreak is a global pandemic that has had caused a profound impact on social stability, economic development and national security, and has further evolved into a major public health crisis. The rapid research and development and efficient deployment of vaccines is one of the effective means to prevent and control the epidemic. This article reviews the primary features of current COVID-19 vaccines, simultaneously focus the clinical features of liver injury post-vaccination and explore its possible pathogenesis.


Subject(s)
COVID-19 , Influenza Vaccines , Influenza, Human , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , Humans , Influenza, Human/epidemiology , Influenza, Human/prevention & control , Liver , Vaccination
18.
23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021 ; : 1245-1252, 2022.
Article in English | Scopus | ID: covidwho-1909206

ABSTRACT

In this work, we study national and state-level COVID-19 pandemic data in the United States with the help of human mobility trend data and auxiliary medical information. We analyze and compare various state-of-the-art time-series prediction techniques. We assess a spatio-temporal graph neural network model which forecasts the pandemic course by utilizing a hybrid deep learning architecture and human mobility data. Nodes in the graph represent the state-level deaths due to COVID-19 at any particular time point, edges represent the human mobility trend and temporal edges correspond to node attributes across time. We also study statistical modeling and machine learning techniques for mortality prediction in the United States. We evaluate these techniques on both state and national level COVID-19 data in the United States and claim that the SARIMAX and GCN-LSTM model generated forecast values using exogenous hospital information variables can enrich the underlying model to improve the prediction accuracy at both levels. Our best machine learning models perform 50% and 60% better than the baseline on an average on the national level and state-level data, respectively, while the statistical models perform 63% and 42% better. © 2021 IEEE.

19.
23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021 ; : 1022-1028, 2022.
Article in English | Scopus | ID: covidwho-1909205

ABSTRACT

Fatigue driving is one of the major contributors to road accidents. Nowadays, COVID-19 is reaching epidemic proportions, which directly leads to the phenomenon of mask-wearing becomes ordinary among drivers. Most of the existing fatigue detection systems are unable to effectively determine the factual fatigue status of a driver that wearing a mask. Therefore, we propose a quick-witted fatigue detection system to counteract the obstruction of masks. The system detects faces by means of a pyramidbox-based approach. Then a modified PFLD-based method will predict the facial landmarks, from which the eye aspect ratio (EAR) is calculated. Ultimately, our self-made FDUM dataset was tested by using the evaluation method that combined PERCLOS and a method for blink frequency based on Gaussian distribution. Our system can achieve 97.06% accuracy in determining the fatigue status of the driver under the mask, which represents an excellent recognition rate of the system. © 2021 IEEE.

20.
Ieee Transactions on Network Science and Engineering ; 9(3):1853-1865, 2022.
Article in English | Web of Science | ID: covidwho-1895933

ABSTRACT

With the development of modern technology, numerous economic losses are incurred by various spreading phenomena. Thus, it is of great significance to identify the initial sources triggering such phenomena. The investigation of source localization in social networks has gained substantial attention and become a popular topic of study. For practical spreading phenomena on social networks, the infection rates are relatively low. Hence, a high uncertainty of spreading trace might be incurred, which further incurs the reduction of localization accuracy obtained through existed source localization methods, especially the observer-based ones. Aiming to solve the source localization problem with a low infection rate, we propose a novel localization algorithm, i.e., path-based source identification (PBSI). First, a small number of nodes are selected and designated as observers. After the propagation process triggered by sources, we can obtain a snapshot. Later, a label is assigned to represent whether a node is infected or not, and observers are supposed to record the paths through which nodes are successfully infected. Based on source centrality theory, observers make the labels flow in the direction recorded during the label iteration process, which ensures the labels of nodes in the direction of the source increase gradually. Extensive experiments indicate that the proposed PBSI can handle source localization problems for both single and multi-source scenarios with better performance than that of state-of-the-art algorithms under different propagation models.

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