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ACM Transactions on Computing for Healthcare ; 3(4), 2022.
Artigo em Inglês | Scopus | ID: covidwho-2214020

RESUMO

During pandemics, effective interventions require monitoring the problem at different scales and understanding the various tradeoffs between efficacy, privacy, and economic burden. To address these challenges, we propose a framework where we perform Bayesian change-point analysis on aggregate behavior markers extracted from mobile sensing data collected during the COVID-19 pandemic. Results generated by 598 participants for up to four months reveal rich insights: We observe an increase in smartphone usage around February 10th, followed by an increase in email usage around February 27th and, finally, a large reduction in participant's mobility around March 13th. These behavior changes overlapped with important news events and government directives such as the naming of COVID-19, a spike in the number of reported cases in Europe, and the declaration of national emergency by President Trump. We also show that our detected change points align with changes in large scale external sources, including number of COVID-19 tweets, COVID-19 search traffic, and a large-scale foot traffic data collected by SafeGraph, providing further validation of our method. Our results show promise towards the feasibility of using mobile sensing to understand communities' responses to public health interventions. © 2022 Copyright held by the owner/author(s).

3.
Multiple Sclerosis Journal ; 28(3 Supplement):892-893, 2022.
Artigo em Inglês | EMBASE | ID: covidwho-2138816

RESUMO

Background: The administration of oral cladribine reduces relapses and slows accumulation of disability, however it is currently unknown how previous treatment with high efficacy disease modifying therapies (DMTs) may affect expanded disability status scale (EDSS).Real-world outcomes data for cladribine is limited. Real-world data provides safety and effectiveness data that is not provided through randomised controlled trials. Objective(s): To explore two-year EDSS change after initiation of oral cladribine and characterise lymphocyte profile and immunoglobulin levels, to evaluate short term safety profiles and the number that need to be retreated in years 3 and 4. Method(s): In a cohort of 180 patients with MS from a single centre in Australia, lymphocyte subsets and IgG levels were measured at baseline, 12,18, 24-month time points after starting therapy with cladribine. EDSS change, and number of patients with relapse and lesion count were also captured at these time intervals. Safety data was reviewed. Patients were clinically reviewed each 6 months and if retreated further laboratory tests were conducted. The impact of COVID19 affected some clinical assessment timing. Result(s): Of the total cohort treated with cladribine, 46 patients were naive to therapy, 12 patients switched to cladribine with a treatment gap of >2 years, and the most common immediate prior DMTs were fingolimod (n=33), B cell therapy (n=38, natalizumab (n=30), and others (n=21). Mean Baseline EDSS was 4, Year 1, 3.9 and year 2 was 4.1. 85% were stable or improved and 15% had a higher EDSS. From baseline to year 2, 79% were stable or improved and 21% had worsened. CD4 cell count fell slightly, while CD8 and CD19 cell counts and IgG count remained stable from baseline, 12-month and 24-month intervals. Relapse rate fell over the 2 years to 11%. Grade 4 lymphopenia occurred in 1% of patients at the 24-month interval. 9 of 131 patients completing year 3 were given a third dose in their third year and 4 of 54 received a third dose in their 4th year. Conclusion(s): Data from this cohort shows the majority of patients' EDSS scores improved or stabilised over 12-24 months, with an increasing proportion in deteriorating at 24 months. IgG levels remained stable. 10% of patients received a third dose, 6% in their 3rd year and 4% in their 4th year.

4.
6th IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2021 ; : 46-57, 2021.
Artigo em Inglês | Scopus | ID: covidwho-1759014

RESUMO

In most countries around the world, various public policies and guidelines, such as social distancing and stay-at-home orders, have been put in place to slow down the spreading of COVID-19. Relying on traditional surveys to assess policy impacts on community level behavior changes may lead to biased results, and limit fine-grained understanding of human behavior dynamics over time. We propose to leverage mobile sensing to capture people's behavior footprints amid the COVID-19 pandemic, and understand their collective behavior changes with respect to existing policies. Specifically, we propose to extract a rich set of behavioral markers from raw mobile sensing data, including mobility, social interactions, physical activities, and health states, and apply them in a generalized behavior change analysis framework to measure and detect community level behavior changes in an epidemic context. We present how to combine change point detection algorithm and interrupted time series analysis to automatically detect three different measurements of behavior changes (e.g., level, trend, and variance changes), and provide insights supported by statistical inference. A case study using a dataset that we collected from a large mobile sensing study conducted in the United States is shown to demonstrate the proposed framework and method. © 2021 IEEE.

5.
2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020 ; : 746-751, 2020.
Artigo em Inglês | Scopus | ID: covidwho-1405147

RESUMO

Chinese college students had to be educated online in the first several months of 2020 due to the COVID-19. We measured the study-related burnout of college students during that period and compared it with previous related researches. The study found that there was no significant change in the study-related burnout between online education and offline education. However, the new online teaching mode still caused some new problems in the different groups. The overall level of burnout of girls was almost equal to that of boys, and the score girls have in the dimension of emotionally depressing was higher. The burnout level of freshmen was the highest among the four grades which indicated that online education might hinder their understanding of professional knowledge. The burnout level of rural students was higher than that of urban students. In order to effectively reduce the study-related burnout level of college students receiving online education, game-based teaching provides a solution. At the same time, the equipment and network problems of students in rural areas can not be ignored. © 2020 IEEE.

6.
Medical Journal of Chinese People's Liberation Army ; 45(10):1003-1029, 2020.
Artigo em Chinês | Scopus | ID: covidwho-972626

RESUMO

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, coronavirus disease 2019 (COVID-19), affecting more than seventeen million people around the world. Diagnosis and treatment guidelines for clinicians caring for patients are needed. In the early stage, we have issued "A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version)";now there are many direct evidences emerged and may change some of previous recommendations and it is ripe for develop an evidence-based guideline. We formed a working group of clinical experts and methodologists. The steering group members proposed 29 questions that are relevant to the management of COVID-19 covering the following areas: chemoprophylaxis, diagnosis, treatments, and discharge management. We searched the literature for direct evidence on the management of COVID-19, and assessed its certainty generated recommendations using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Recommendations were either strong or weak, or in the form of ungraded consensus-based statement. Finally, we issued 34 statements. Among them, 6 were strong recommendations for, 14 were weak recommendations for, 3 were weak recommendations against and 11 were ungraded consensus-based statement. They covered topics of chemoprophylaxis [including agents and Traditional Chinese Medicine (TCM) agents], diagnosis [including clinical manifestations, reverse transcription-polymerase chain reaction (RT-PCR), respiratory tract specimens, IgM and IgG antibody tests, chest computed tomography, chest X-ray, and CT features of asymptomatic infections], treatments [including lopinavir-ritonavir, umifenovir, favipiravir, interferon, remdesivir, combination of antiviral drugs, hydroxychloroquine/chloroquine, interleukin-6 inhibitors, interleukin-1 inhibitors, glucocorticoid, Qingfei Paidu decoction, Lianhua Qingwen granules/capsules, convalescent plasma, lung transplantation, invasive or noninvasive ventilation, and extracorporeal membrane oxygenation (ECMO)], and discharge management (including discharge criteria and management plan in patients whose RT-PCR retesting shows SARS-CoV-2 positive after discharge). We also created two figures of these recommendations for the implementation purpose. We hope these recommendations can help support healthcare workers caring for COVID-19 patients. © 2020 People's Military Medical Press. All rights reserved.

7.
J Endocrinol Invest ; 44(5): 1031-1040, 2021 May.
Artigo em Inglês | MEDLINE | ID: covidwho-898191

RESUMO

OBJECTIVE: COVID-19 is a new coronavirus infectious disease. We aimed to study the characteristics of thyroid hormone levels in patients with COVID-19 and to explore whether thyroid hormone predicts all-cause mortality of severely or critically ill patients. METHODS: The clinical data of 100 patients with COVID-19, who were admitted to Wuhan Tongji Hospital from February 8 to March 8, 2020, were analyzed in this retrospective study. The patients were followed up for 6-41 days. Patients were grouped into non-severe illness and severe or critical illness, which included survivors and non-survivors. Multivariate Cox proportional hazards analysis was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause mortality in association with continuous and the lower two quartiles of thyroid hormone concentrations in severely or critically ill patients. RESULTS: The means of free T3 (FT3) were 4.40, 3.73 and 2.76 pmol/L in non-severely ill patients, survivors and non-survivors, respectively. The lower (versus upper) two quartiles of FT3 was associated with all-cause mortality HR (95% CI) of 9.23 (2.01, 42.28). The HR (95% CI) for all-cause mortality in association with continuous FT3 concentration was 0.41 (0.21, 0.81). In the multivariate-adjusted models, free T4 (FT4), TSH and FT3/FT4 were not significantly related to all-cause mortality. Patients with FT3 less than 3.10 pmol/L had increased all-cause mortality. CONCLUSION: FT3 concentration was significantly lower in patients with severe COVID-19 than in non-severely ill patients. Reduced FT3 independently predicted all-cause mortality of patients with severe COVID-19.


Assuntos
COVID-19/sangue , Hormônios Tireóideos/sangue , Adulto , Idoso , Idoso de 80 Anos ou mais , COVID-19/mortalidade , Causas de Morte , China/epidemiologia , Comorbidade , Estado Terminal/mortalidade , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Modelos de Riscos Proporcionais , Estudos Retrospectivos , Análise de Sobrevida , Testes de Função Tireóidea , Tri-Iodotironina/sangue
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