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1.
International Journal of Sustainable Building Technology and Urban Development ; 13(2):184-197, 2022.
Article in English | Scopus | ID: covidwho-1955302

ABSTRACT

After the global pandemic of COVID-19, many people were afraid of an unknown disease without a cure, Travelers’ behavior has changed due to the government’s policy and people’s risk perception. The goal of this study is to analyze the data obtained through the survey and find the mode choice factors that influenced the selection of transportation changed due to COVID-19. The data needed for analysis were collected through a survey on the selection of transportation before and after the outbreak of COVID-19, at the peak time (the third pandemic in Korea from November 2020 to February 2021), and after the peak. In order to analyze the correlation between travel mode choice and individual tendency, bivariate probit model was developed. This study found that (1) due to the spread of COVID-19, private cars and private transportation are reduced, and public transportation is greatly reduced. (2) behavior changes were different depending on the type of work and working conditions. (3) behavior changes were different depending on the perception of public transportation. In conclusion, this study can prevent the spread of COVID-19 and help policy decision according to the travelers’ behavior in a different pandemic situation than before. © International Journal of Sustainable Building Technology and Urban Development.

2.
HemaSphere ; 6(SUPPL 2):16-17, 2022.
Article in English | EMBASE | ID: covidwho-1915867

ABSTRACT

G protein-coupled receptor family C group 5 member D (GPRC5D) has limited expression in healthy human tissue but is highly expressed in malignant plasma cells, making it a promising target for immunotherapy approaches for MM. Talquetamab (JNJ-64407564) is a first-in-class bispecific antibody that binds to both GPRC5D and CD3 receptors to redirect T cells to kill MM cells. Updated and new results of talquetamab at the recommended phase 2 doses (RP2Ds) are reported (NCT03399799). Eligible patients had RRMM or were intolerant to standard therapies. Patients who were previously treated with B-cell maturation antigen (BCMA)-directed therapies were eligible. This analysis focuses on patients who received talquetamab subcutaneously (SC;range: 5.0-800 μg/kg) weekly (QW) or biweekly (Q2W) with step-up dosing. The primary objectives were to identify the RP2D (part 1) and assess talquetamab safety and tolerability at the RP2Ds (part 2). Adverse events (AEs) were graded by CTCAE v4.03;cytokine release syndrome (CRS) was graded per Lee et al 2014 criteria. Responses were investigator-assessed per IMWG criteria. As of July 19, 2021, 95 patients had received SC talquetamab. The original RP2D was 405 μg/kg SC talquetamab QW with step-up doses, and a second RP2D of 800 μg/kg SC talquetamab Q2W with step-up doses was also identified. 30 patients received 405 μg/kg QW (median 61.5 years [range 46-80];63% male;100% triple-class exposed;80% penta-drug exposed;77% triple-class refractory, 20% penta-drug refractory;30% prior BCMA-directed therapy;median follow-up [mF/U]: 7.5 mo [range 0.9-15.2]). 23 patients received 800 μg/kg Q2W (median 60.0 years [range 47-84];48% male;96% triple-class exposed;70% penta-drug exposed;65% triple-class refractory, 22% penta-drug refractory;17% prior BCMA-directed therapy;mF/U: 3.7 mo [range 0.0-12.0]). No treatment discontinuations due to AEs were reported at either RP2Ds. Most common AEs at the 405 μg/kg QW were CRS (73%;1 grade 3 CRS), neutropenia (67%;grade 3/4: 60%), and dysgeusia (60%;grade 2: 29%). Skin-related AEs occurred in 77% of patients and were all grade 1/2 (nail disorders: 30%). Infections occurred in 37% of patients (1 grade 3 COVID-19 pneumonia). Most common AEs at 800 μg/kg Q2W were CRS (78%;all grade 1/2), dry mouth (44%;all grade 1/2), and neutropenia (44%;grade 3/4: 35%). Skin-related AEs occurred in 65% of patients with grade 3 events in 13% (nail disorders: 17%). Infections occurred in 13% of patients (1 grade 3 pneumococcal sepsis). In 30 response-evaluable patients treated at 405 μg/kg QW, the overall response rate (ORR) was 70% (very good partial response or better [≥VGPR]: 57%). In 17 response-evaluable patients treated at 800 μg/ kg Q2W, the ORR was 71% (≥VGPR: 53%). Responses were durable and deepened over time with both RP2Ds (Figure). Median duration of response (DOR) was not reached at either RP2D;6-month DOR rate was 67% (95% CI: 41-84) at 405 μg/kg QW. Serum trough levels of talquetamab were comparable at both RP2Ds. Pharmacodynamic data at both RP2Ds showed peripheral T cell activation and induction of cytokines. SC talquetamab is well tolerated and highly effective at both RP2Ds. Preliminary data suggest that less frequent, higher doses of SC talquetamab do not negatively impact the safety profile. Further evaluation of talquetamab as monotherapy (phase 2;NCT04634552) and in combination with other therapies in patients with RRMM is underway. (Figure Presented) .

3.
Value in Health ; 25(7):S587, 2022.
Article in English | EMBASE | ID: covidwho-1914762

ABSTRACT

Objectives: The US is amid a national opioid crisis before and during the COVID-19 pandemic. The Food and Drug Administration has approved methadone, buprenorphine, and naltrexone as medications for opioid use disorder (MOUD). This study examined the real-world dispensing of MOUD. Methods: All dispensing pharmacies, clinics, or other dispensers of Schedule II-V controlled substances in California report to the Controlled Substance Utilization Review and Evaluation System (CURES) on the day of prescriptions refills. Leveraging the data of buprenorphine (schedule III) and methadone (Schedule II) prescriptions from Mar 2019-Mar 2021 employing California’s deidentified CURES database, this study examined real-world dispensing of methadone and buprenorphine before (03/19/2019-03/18/2020) and during the pandemic (03/19/2020-03/18/2021). We did not review naltrexone dispensing, which is not a controlled substance. Results: In Mar 2019-Mar 2021, 182,367 patients≥18 in California obtained 875,051 buprenorphine and methadone prescriptions: Before the pandemic, there were 482,965 MOUD prescriptions dispensed to 116,644 patients;since the pandemic, 97,887 patients received 392,086 prescriptions, of which 32,164 patients(as “non-naïve” patients) started their MOUD before Mar 2020. On average, patients refilled their prescriptions 4.1 times/year before the pandemic and 4.0 times/year since the pandemic. The MOUD non-naïve patients (n=32,164) received 8.1 prescriptions/year before Mar 2020 and 7.4 refills/year afterward. The MOUD medications most widely prescribed in Mar 2019-Mar 2021 were buprenorphine (473,206 (98.0%) and 383,297 (97.8%), respectively, before and after the pandemic), which included 802,936 counts of buprenorphine alone and 53,567 combination medications of buprenorphine and naloxone. The number of methadone prescriptions declined from 9,759 before Mar 2020 to 8,789 during the pandemic. Conclusions: Buprenorphine is the leading MOUD prescribed for patients in California. The decline in MOUD dispensing for non-naïve patients may indicate restricted access to medication-assisted treatment under the pandemic. Policymakers should maintain or modify the policy strategies to help support medication access.

4.
IEEE ACCESS ; 10:62282-62291, 2022.
Article in English | Web of Science | ID: covidwho-1909181

ABSTRACT

In this study, a survival analysis of the time to death caused by coronavirus disease 2019 is presented. The analysis of a dataset from the East Asian region with a focus on data from the Philippines revealed that the hazard of time to death was associated with the symptoms and background variables of patients. Machine learning algorithms, i.e., dimensionality reduction and boosting, were used along with conventional Cox regression. Machine learning algorithms solved the diverging problem observed when using traditional Cox regression and improved performance by maximizing the concordance index (C-index). Logistic principal component analysis for dimensionality reduction was significantly efficient in addressing the collinearity problem. In addition, to address the nonlinear pattern, a higher C-index was achieved using extreme gradient boosting (XGBoost). The results of the analysis showed that the symptoms were statistically significant for the hazard rate. Among the symptoms, respiratory and pneumonia symptoms resulted in the highest hazard level, which can help in the preliminary identification of high-risk patients. Among various background variables, the influence of age, chronic disease, and their interaction were identified as significant. The use of XGBoost revealed that the hazards were minimized during middle age and increased for younger and older people without any chronic diseases, with only the elderly having a higher risk of chronic disease. These results imply that patients with respiratory and pneumonia symptoms or older patients should be given medical attention.

5.
35th Conference on Neural Information Processing Systems, NeurIPS 2021 ; 20:16346-16357, 2021.
Article in English | Scopus | ID: covidwho-1898354

ABSTRACT

Molecular representation learning is the first yet vital step in combining deep learning and molecular science. To push the boundaries of molecular representation learning, we present PhysChem, a novel neural architecture that learns molecular representations via fusing physical and chemical information of molecules. PhysChem is composed of a physicist network (PhysNet) and a chemist network (ChemNet). PhysNet is a neural physical engine that learns molecular conformations through simulating molecular dynamics with parameterized forces;ChemNet implements geometry-aware deep message-passing to learn chemical/biomedical properties of molecules. Two networks specialize in their own tasks and cooperate by providing expertise to each other. By fusing physical and chemical information, PhysChem achieved state-of-the-art performances on MoleculeNet, a standard molecular machine learning benchmark. The effectiveness of PhysChem was further corroborated on cutting-edge datasets of SARS-CoV-2. © 2021 Neural information processing systems foundation. All rights reserved.

6.
Human Communication Research ; : 27, 2022.
Article in English | Web of Science | ID: covidwho-1868325

ABSTRACT

Social bots, or algorithmic agents that amplify certain viewpoints and interact with selected actors on social media, may influence online discussion, news attention, or even public opinion through coordinated action. Previous research has documented the presence of bot activities and developed detection algorithms. Yet, how social bots influence attention dynamics of the hybrid media system remains understudied. Leveraging a large collection of both tweets (N = 1,657,551) and news stories (N = 50,356) about the early COVID-19 pandemic, we employed bot detection techniques, structural topic modeling, and time series analysis to characterize the temporal associations between the topics Twitter bots tend to amplify and subsequent news coverage across the partisan spectrum. We found that bots represented 8.98% of total accounts, selectively promoted certain topics and predicted coverage aligned with partisan narratives. Our macro-level longitudinal description highlights the role of bots as algorithmic communicators and invites future research to explain micro-level causal mechanisms.

7.
Modern Pathology ; 35(SUPPL 2):289-290, 2022.
Article in English | EMBASE | ID: covidwho-1857588

ABSTRACT

Background: COVID-19 is a contagious disease caused by SARS-CoV-2. Clinically, this disease can range from having mild to more severe symptoms including death due to disease. Our aim in this study is to determine if there are any significant differences in the BAL cell count differentials between COVID-19 (+) and COVID-19 (-) patients, including a comparison of patients who recovered from the disease and those who died due to disease. Design: A retrospective computer search (EPIC Beaker) was performed on BALs from 1/20/20 to 6/6/21. Patients were included if they had a (+) COVID-19 test and BAL performed. For a comparison group we included BAL specimens from COVID-19 (-) lung transplant patients. 59 patients met this criteria: 10 COVID-19 (-) and 49 COVID-19 (+) (24 COVID-19 recovered and 25 COVID-19 deceased). The control group had 5 male and 5 female patients, mean age of 37. The COVID-19 (+) group had 37 male and 12 female patients with mean age of 60. For each BAL specimen, 3 cytospin slides were prepared (2 PAP and 1 MGG) and analyzed for differential cell count performed by a cytotechnologist. BAL specimens were also sent to microbiology and other infectious agents were noted if applicable. A p-value with t-test unequal variances was performed to compare any significant differences in the cell count between groups. Results: Mean cell count percentages in the COVID-19 (+) and COVID-19 (-) is as seen in Table 1. In comparing the BAL cell counts of COVID-19 (+) versus COVID-19 (-) groups, there was a significant difference between the mean neutrophil cell count (pvalue 0.04). No significant difference was found in the mean percentages of macrophages, lymphocytes, or eosinophils. In the COVID-19 recovered versus deceased groups, there was no significant difference found between the groups. Of the 10 COVID (-) patients, 1 patient was positive for Candida spp. infection on microbiology studies. Of the 49 COVID (+) patients, 11 cases were positive for one or more fungal organisms [Candida spp (8);Aspergillus species (3);and Saprochaete Capitata (1)]. Conclusions: A significant difference was seen in the neutrophil cell count between COVID-19 (+) and COVID-19 (-) patients, which is as expected given the infection. There was no significant difference in the COVID-19 (+) recovered vs COVID-19 (+) deceased groups. The range of symptoms seen in COVID-19 (+) patients cannot be explained by differences in the inflammatory cell count of patients in our study.

8.
Mobile Information Systems ; 2022:9, 2022.
Article in English | Web of Science | ID: covidwho-1854464

ABSTRACT

With the rapid development of Internet technology, new media is more and more favored by people and has become an important medium to control online public opinion. Social public opinion caused by new media is also more and more concerned by all walks of life. New media has the characteristics of fast information dissemination, wide dissemination range, and strong arbitrariness of news release. Positive online public voice or negative online public voice will have a very different impact on people's lives. Some negative online public voice may even constitute a social crisis and seriously affect social public security. In order to analyze and predict the development trend of new media network public opinion, this paper presents a design of improved BP neural network model based on genetic algorithm, which is used to analyze public opinion in new media network. Experimental results show that this way has stronger processing ability and higher warning accuracy for online public opinion event index data. It can provide certain theoretical basis and data support for relevant departments to effectively prevent and manage new media network public opinion events.

9.
13th International Conference on E-Education, E-Business, E-Management, and E-Learning, IC4E 2022 ; : 24-29, 2022.
Article in English | Scopus | ID: covidwho-1840626

ABSTRACT

This paper describes the development of an educational artificial intelligence (AI) chatbot prototype to support teachers in developing digital reading lists for their students. The chatbot aims to teach users how to use an educational system-Talis Aspire-effectively by giving them quick answers to questions, offering demonstrations and instructions on how to complete essential tasks on Talis Aspire, advising them how to solve problems and providing solutions for common issues. We have presented the prototype, together with the approach we used to design and develop it by considering the concepts of Recontextualisation' and Quality Function Deployment'. We argue that the use of chatbot technology can not only help tutors develop online education and teaching materials but may also improve the quality of educational services during and after the COVID-19 pandemic. A number of recommendations and further work suggested by domain experts have also been highlighted in this paper in order to improve our prototype further. © 2022 ACM.

10.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334813

ABSTRACT

Cryptococcal meningoencephalitis is an emerging infection shifted from primarily ART- naive to being ART-experienced HIV/AIDS patients, COVID-19 patients and also in immune competent individuals, mainly caused by the human opportunistic pathogen Cryptococcus neoformans, yet mechanisms of the brain or CNS dissemination remain to elucidate, which is the deadest process for the disease. Meanwhile, illustrations of clinically relevant responses in cryptococcosis were limited, as the low availabilities of clinical samples. In this study, macaque and mouse infection models were employed and miRNA-mRNA transcriptomes were performed and combined, which revealed cytoskeleton, a major feather in HIV/AIDS patients, was a centric pathway regulated in both two infection models. Notably, assays of clinical immune cells confirmed an enhanced “Trojan Horse” in HIV/AIDS patients, which can be shut down by cytoskeleton inhibitors. Furthermore, we identified a novel enhancer for macrophage “Trojan Horse”, myocilin, and an enhanced fungal burden was achieved in brains of MYOC transgenic mice. Taking together, this study reveals fundamental roles of cytoskeleton and MYOC in blocking fungal CNS dissemination, which not only helps to understand the high prevalence of cryptococcal meningitis in HIV/AIDS, but also facilitates the development of novel drugs for therapies of meningoencephalitis caused by C. neoformans and other pathogenic microorganisms.

11.
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.

12.
Library Hi Tech ; 2022.
Article in English | Scopus | ID: covidwho-1806856

ABSTRACT

Purpose: This study explored the students' perception of their adoption and acceptance of virtual learning (VL), the factors affecting the adoption of educational technologies and the correlation between their intention, perceived behavioral control and care competence in caring for older adults. Design/methodology/approach: A cross-sectional survey was conducted. Surveys were administered to evaluate the participants who were involved in VL on geriatric care during coronavirus disease 2019 (COVID-19) pandemic. A total of 315 nursing students participated in the survey, and 287 valid questionnaires were collected (response rate: 91.11%). Findings: A total of 287 participants (mean age 21.09, SD 1.44 years;242/287, 84.3% female) were included in the study. The variables of intention to use technologies were positively correlated with care competence (r = 0.59, p < 0.001). The results revealed that the major predictors were perceived ease-of-use (PEOU) (β = 0.28, 95% confidence interval (CI) 0.16–0.40) and perceived usefulness (PU) (β = 0.22, CI 0.09–0.35) which were significantly positive predictors of competence in geriatric care. Research limitations/implications: Nursing students lack in clinical knowledge and situational experience in geriatric care;therefore, their perceptiveness, expressions and reflection on the process of providing care to hospitalized older patients should be increased. These results indicated that students improved in geriatric healthcare after/during the VL program during COVID-19 pandemic. Originality/value: It is hoped that the present study would make an invaluable contribution to existing research on education in general and on the quality of care in geriatric nursing as limited studies have been published so far. © 2022, Pei-Lun Hsieh, Shang-Yu Yang, Wen-Yen Lin and Tien-Chi Huang.

13.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333645

ABSTRACT

The Coronavirus Disease 2019 (COVID-19) pandemic has caused millions of deaths and will continue to exact incalculable tolls worldwide. While great strides have been made toward understanding and combating the mechanisms of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection, relatively little is known about the individual SARS-CoV-2 proteins that contribute to pathogenicity during infection and that cause neurological sequela after viral clearance. We used Drosophila to develop an in vivo model that characterizes mechanisms of SARS-CoV-2 pathogenicity, and found ORF3a adversely affects longevity and motor function by inducing apoptosis and inflammation in the nervous system. Chloroquine alleviated ORF3a induced phenotypes in the CNS, arguing our Drosophila model is amenable to high throughput drug screening. Our work provides novel insights into the pathogenic nature of SARS-CoV-2 in the nervous system that can be used to develop new treatment strategies for post-viral syndrome. HIGHLIGHTS: SARS-CoV-2 ORF3a is pathogenic in the nervous system.ORF3a induces cell death, inflammation, and lysosome dysfunction.Chloroquine protects against ORF3a induced CNS distress and lysosome dysfunction.

14.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333630

ABSTRACT

Circular RNAs (circRNAs) encoded by DNA genomes have been identified across host and pathogen species as parts of the transcriptome. Accumulating evidences indicate that circRNAs play critical roles in autoimmune diseases and viral pathogenesis. Here we report that RNA viruses of the Betacoronavirus genus of Coronaviridae , SARS-CoV-2, SARS-CoV and MERS-CoV, encode a novel type of circRNAs. Through de novo circRNA analyses of publicly available coronavirus-infection related deep RNA-Sequencing data, we identified 351, 224 and 2,764 circRNAs derived from SARS-CoV-2, SARS-CoV and MERS-CoV, respectively, and characterized two major back-splice events shared by these viruses. Coronavirus-derived circRNAs are more abundant and longer compared to host genome-derived circRNAs. Using a systematic strategy to amplify and identify back-splice junction sequences, we experimentally identified over 100 viral circRNAs from SARS-CoV-2 infected Vero E6 cells. This collection of circRNAs provided the first line of evidence for the abundance and diversity of coronavirus-derived circRNAs and suggested possible mechanisms driving circRNA biogenesis from RNA genomes. Our findings highlight circRNAs as an important component of the coronavirus transcriptome. SUMMARY: We report for the first time that abundant and diverse circRNAs are generated by SARS-CoV-2, SARS-CoV and MERS-CoV and represent a novel type of circRNAs that differ from circRNAs encoded by DNA genomes.

15.
Journal of Third Military Medical University ; 43(20):2241-2249, 2021.
Article in Chinese | Scopus | ID: covidwho-1789737

ABSTRACT

Objective To describe the clinical characteristics of liver and kidney injuries and investigate its effect on the severity and mortality in the COVID-19 patients.Methods A total of 3 548 patients diagnosed with COVID-19 hut without liver and kidney diseases admitted in the Huoshenshan Hospital, Jinyintan Hospital and Taikang Tongji Hospital from February 4, 2020 to April 16, 2020 were recruited in this study.Their clinical data were extracted from medical database, including general information, clinical features, laboratory results and outcomes such as death were collected and analyzed.SPSS statistics 23.0 was used to perform the statistical description and analysis.Results Among the 3 548 patients with COYID-19, 875 (24.7%) cases were severe illness and above and 91 (2.6%) died during hospitalization.The proportions of the patients with higher alanine amiotransferase ( ALT) , aspartate aminotransferase ( AST) and creatinine (Cr) were 14.6% (513/3 548) , 3.4% ( 1 19/3 548) and 2.8% ( 101/3 548), respectively.Compared with the patients with normal ALT, AST and Cr, the patients with elevated ALT did not have a significantly increased risk of severe illness or death ( /-∗>().05) , and the risk of severe illness and death was significantly increased in those with elevated AST and Cr ( P<0.05).The risk of severe disease was 2.32 times (95%CI: 1.73-3.10) and 1 1.40 times ( 95% CI: 2.36-54.98 ) for those with single or both liver and kidney injuries, and the risk of death was 5.21 times (95% CI: 3.10-8.75 ) and 13.53 times (95% CI: 2.76-66.32) for those with normal liver and kidney function, respectively.Logistic regression analysis indicated that after independent factors related to severe illness and death screened out as correction factors, the risk of severe illness and death was 1.612 times (95% CI: 1.17-2.22) and 2.907 times (95% CI: 1.61-5.24) of patients with liver or kidney injuries when compared with those with normal function, respectively.Conclusion The COYID-19 patients with liver and renal injuries have a significantly increased tendency to become severity and mortality, and should undergo early intervention. © 2021 Editorial Office of Journal of Third Military Medical University. All rights reserved.

17.
IEEE Internet of Things Journal ; 2022.
Article in English | Scopus | ID: covidwho-1779143

ABSTRACT

Mobile sensing systems have been widely used as a practical approach to collect behavioral and health-related information from individuals and to provide timely intervention to promote health and well-being, such as mental health and chronic care. As the objectives of mobile sensing could be either personalized medicine for individuals or public health for populations, in this work we review the design of these mobile sensing systems, and propose to categorize the design of these systems in two paradigms –(i) Personal Sensing and (ii) Crowd Sensing paradigms. While both sensing paradigms might incorporate common ubiquitous sensing technologies, such as wearable sensors, mobility monitoring, mobile data offloading, and cloud-based data analytics to collect and process sensing data from individuals, we present two novel taxonomy systems based on the (a) Sensing Objectives (e.g., goals of mHealth sensing systems and how technologies achieve the goals), and (b) the Sensing Systems Design and Implementation (D&I) (e.g., designs of mHealth sensing systems and how technologies are implemented). With respect to the two paradigms and two taxonomy systems, this work systematically reviews this field. Specifically, we first present technical reviews on the mHealth sensing systems in eight common/popular healthcare issues, ranging from depression and anxiety to COVID-19. Through summarizing the mHealth sensing systems, we comprehensively survey the research works using the two taxonomy systems, where we systematically review the Sensing Objectives and Sensing Systems D&I while mapping the related research works onto the life-cycles of mHealth Sensing, i.e., (1) Sensing Task Creation &Participation, (2) Health Surveillance &Data Collection, and (3) Data Analysis &Knowledge Discovery. In addition to summarization, the proposed taxonomy systems also help the potential directions of mobile sensing for health from both personalized medicine and population health perspectives. Finally, we attempt to test and discuss the validity of our scientific approaches to the survey. IEEE

18.
55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 ; 2021-October:1302-1306, 2021.
Article in English | Scopus | ID: covidwho-1779140

ABSTRACT

Dynamic Bayesian Network (DBN) is an useful tool to learn the causal inference and social network of random variables. In this article, we analyze the correlations between the spread of coronavirus (COVID-19) and certain self-reported COVID-19 indicators in the United States, and then adopt DBN model with search and score-based approach to analyze and interpret the causal relationships and social network between these variables by learning the structure of the Directed Acyclic Graph from the model. We explore the change of causality among fifty states during the pandemic of COVID-19 in the year of 2020 and interpret the root cause for changes and trends. We concentrate on five worst states with COVID-19 and then extended our studies to all states by comparing the causal relationships and analyzing the patterns of DAG. © 2021 IEEE.

19.
Open Forum Infectious Diseases ; 8(SUPPL 1):S364, 2021.
Article in English | EMBASE | ID: covidwho-1746471

ABSTRACT

Background. Monoclonal Antibody Therapy (MAbs) has been shown to reduce rates of ED visits and hospitalizations in patients at risk for severe Covid-19 infection in clinical trials. Since November, three Mabs received emergency use authorization: Bamlanivimab (Bam), Bamlanivimab/Etesevimab (Bam/Ete) and Casirivimab/ Imdevimab (Casi/imdevi). We describe here the real-world effectiveness of implementing early MAb therapy in the outpatient setting for individuals with Covid-19 at high risk of progression. Methods. We examined the records of 808 UCLA Health patients with a confirmed positive SARS-CoV2 PCR test who were either referred for outpatient Mab therapy or received Mab treatment in the emergency department (ED) between December 10, 2020, and May 3, 2021. The primary outcome of our analysis was the combined 30-day incidence of emergency department visits, hospitalizations, or death following the date of referral. SARS-CoV2 isolates of hospitalized patients who had received Mabs were sequenced to determine the presence of variants. Results. Of 808 patients, 383 were referred for treatment but did not receive treatment, 109 received Mabs in the ED and 316 patients were treated in an outpatient setting. Composite 30-day mortality, ED visits and hospital admissions were significantly reduced in the combination therapy group (Bam/Ete or Cas/Imd) compared with monotherapy (Bam alone) or no treatment groups (aHR 0.16, 95% CI .038, .67). Significant factors associated with the composite outcome included: history of lung disease (HR 4.46, 95% CI 2.89-6.90), cardiovascular disease (HR 1.87, 95% CI 1.12-3.12), kidney disease (HR 2.04, 95% CI 1.27-3.25), and immunocompromised state (HR 3.24, 95% CI 1.02-10.26) as well as high social vulnerability index (HR 1.87, 95% CI 1.13-3.10). Over one-third of hospitalized patients who had received Mabs were confirmed to have the California variant (B.1.427/29) (Figure 1). Figure 1. Covid-19 MAB Treatment Failure Lineages Conclusion. Our data show that in a real-world setting, combination monoclonal antibody therapy, not monotherapy, significantly reduced ED visits and hospital admissions, likely due to the presence of the California variants. High socioeconomic vulnerability and certain medical conditions increased risk of treatment failure.

20.
Online Learning Journal ; 26(1):203-220, 2022.
Article in English | Scopus | ID: covidwho-1743153

ABSTRACT

Even before COVID-19, literacy graduate coursework was increasingly offered online, replacing the traditional campus-based courses This study investigated how graduate literacy students perceive coursework in an online learning environment. This understanding is important because (a) student perceptions regarding online learning are critical to motivation and learning;and (b) faculty designing courses need to consider student voice in course development. This survey research queried literacy master’s degree candidates their perceptions prior to and after taking online classes, their confidence levels using technology, and about the technological tools that have impacted their learning. Results indicated initial perceptions of online learning changed positively after engagement in coursework, but course design influenced collaboration and engagement. Statistical significance was found in changes in initial perceptions of online learning to a more positive overall feelings toward online learning. The results of this study raise important considerations for implementing online coursework for literacy graduate students. © 2022, The Online Learning Consortium. All rights reserved.

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