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1.
Medical Journal of Peking Union Medical College Hospital ; 13(1):9-12, 2022.
Article in Chinese | Scopus | ID: covidwho-1876157

ABSTRACT

COVID-19 highlights the lack of interdisciplinary medical talents. The international history of medical education shows the urgent need of high-level interdisciplinary medical talents. Anchoring the goal to develop a global center of talents and highland of innovation, this article takes medical education of Zhejiang University as an example, focusing on and exploring the training mode of high-level interdisciplinary medical talents in the new era. It includes: Firstly, optimizing the training mode of eight-year program for medical doctors with non-medical bachelor degree followed with complete education for a medical doctorate that innovates the curriculum system of clinical medicine;secondly, creating the training system of postdoctor of clinical medicine and integrating medical resources that include high-quality talents and health care system, in order to build a high-quality teaching staff with a interdisciplinarity background and innovative bases. It not only strengthens the residents' competency and frontier creativity, but also ensures the sustainable development of interdisciplinary medical talents. The reform of training mode, curriculum system, teaching staff and clinical teaching bases all contribute to the goal of building a country with interdisciplinary talents that serve the frontier of science and technology in the world, the major needs of the country and people's health in the new era. © 2022, Peking Union Medical College Hospital. All rights reserved.

2.
Progress in Chemistry ; 34(1):207-226, 2022.
Article in English | Web of Science | ID: covidwho-1870090

ABSTRACT

The novel coronavirus pneumonia epidemic (COVID over line 19) brings a serious threat to the development of human society and the health of human beings. Due to the stability of the severe acute respiratory syndrome coronavirus 2 ( SARS over line CoV over line 2) in urban sewage, which has become one of the virus pollution sources, it has been a focus how to eliminate the existing virus in water. SARS over line CoV over line 2 structurally consists of RNA chains and protein capsids, and thus can be inactivated via reactive oxygen species ( ROS) attack. Moreover, block of biochemical metabolism and destruction of virus structure are also effective inactivation methods for SARS over line CoV over line 2 inactivation. Nanomaterials exhibit surface and interface effects, specific microstructure and excellent physicochemical properties, implying their high application potential in SARS over line CoV over line 2 inactivation. In this study, we overall review application of nanotechnologies for SARS over line CoV over line 2 inactivation, including photocatalysis, heterogeneous catalytic oxidation, ion toxicity induced inactivation, and structural effects inactivation method. Furthermore, based on the structural composition, as well as survival and transmission characteristics of SARS over line CoV over line 2 in water environment, the application potential of various nanotechnologies for SARS over line CoV over line 2 inactivation are deeply discussed. This study can provide a theoretical basis and practical reference for the application of nanotechnology for the SARS over line CoV over line 2 inactivation and the secondary transmission interruption in water.

3.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-337476

ABSTRACT

The COVID-19 pandemic has impacted communities far and wide and put tremendous pressure on healthcare systems of countries across the globe. Understanding and monitoring the major influences on COVID-19 prevalence is essential to inform policy making and device appropriate packages of non-pharmaceutical interventions (NPIs). This study evaluates community level influences on COVID-19 incidence in England and their variations over time with specific focus on understanding the impact of working in so called high-risk industries such as care homes and warehouses. Analysis at community level allows accounting for interrelations between socioeconomic and demographic profile, land use, and mobility patterns including residents’ self-selection and spatial sorting (where residents choose their residential locations based on their travel attitudes and preferences or social structure and inequality);this also helps understand the impact of policy interventions on distinct communities and areas given potential variations in their mobility, vaccination rates, behavioural responses, and health inequalities. Moreover, community level analysis can feed into more detailed epidemiological and individual models through tailoring and directing policy questions for further investigation. We have assembled a large set of static (socioeconomic and demographic profile and land use characteristics) and dynamic (mobility indicators, COVID-19 cases and COVID-19 vaccination uptake in real time) data for small area statistical geographies (Lower Layer Super Output Areas, LSOA) in England making the dataset, arguably, the most comprehensive set assembled in the UK for community level analysis of COVID-19 infection. The data are integrated from a wider range of sources including telecommunications companies, test and trace data, national travel survey, Census and Mid-Year estimates. To tackle methodological challenges specifically accounting for highly interrelated influences, we have augmented different statistical and machine learning techniques. We have adopted a two-stage modelling framework: a) Latent Cluster Analysis (LCA) to classify the country into distinct land use and travel patterns, and b) multivariate linear regression to evaluate influences at each distinct travel cluster. We have also segmented our data into different time periods based on changes in policies and evolvement in the course of pandemic (such as the emergence of a new variant of the virus). By segmenting and comparing influences across spaces and time, we examine more homogeneous behaviour and uniform distribution of infection risks which in turn increase the potential to make causal inferences and help understand variations across communities and over time. Our findings suggest that there exist significant spatial variations in risk influences with some being more consistent and persistent over time. Specifically, the analysis of industrial sectors shows that communities of workers in care homes and warehouses and to a lesser extent textile and ready meal industries tend to carry a higher risk of infection across all spatial clusters and over the whole period we modelled in this study. This demonstrates the key role that workplace risk has to play in COVID-19 risk of outbreak after accounting for the characteristics of workers’ residential area (including socioeconomic and demographic profile and land use features), vaccination rate, and mobility patterns.

4.
Embase; 2020.
Preprint in English | EMBASE | ID: ppcovidwho-337379

ABSTRACT

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

5.
Journal of the American College of Cardiology ; 79(9):2118-2118, 2022.
Article in English | Web of Science | ID: covidwho-1848364
6.
Journal of the American College of Cardiology ; 79(9):2506-2506, 2022.
Article in English | Web of Science | ID: covidwho-1848363
7.
Free Neuropathology ; 2, 2021.
Article in English | Scopus | ID: covidwho-1847894

ABSTRACT

Cases of acute disseminated encephalomyelitis (ADEM) and its hyperacute form, acute hemorrhagic leu-koencephalitis (AHLE), have been reported in coronavirus disease 2019 (COVID-19) patients as rare, but most severe neurological complications. However, histopathologic evaluations of ADEM/AHLE pathology in COVID patients are extremely limited, so far having only been reported in a few adult autopsy cases. Here we compare the findings with an ADEM-like pathology in a pediatric patient taken through a biopsy procedure. Understanding the neuropathology may shed informative light on the autoimmune process affecting COVID-19 patients and provide critical information to guide the clinical management. © 2021 The author(s).

8.
Journal of Beijing Institute of Technology (English Edition) ; 31(2):140-151, 2022.
Article in English | Scopus | ID: covidwho-1847859

ABSTRACT

The stockpiling, delivery, and provision of emergency material were in the public gaze of millions of people when the coronavirus disease 2019 (COVID-19) broke out. Civil-military integration emergency logistics silently opened up the "second battlefield" of anti-epidemic, and established a lifeline under that emergency situation. Research on the construction of civil-military integrated logistics system plays an extremely important role and occupies a significant position in ensuring social stability and security as well as the stable development of social economy in China. The modern economy driven by the Internet, Internet of Things, and big data demonstrates a rapid growing trend calling for efficient, fast, and convenient logistics. It is urgent to upgrade or build an intelligent logistics system with intelligent technology and unmanned technology as the core to meet the international and domestic market demand. As mentioned above, this paper analyzes and expounds the construction problem and practical significance of civil-military integration emergency logistics system based on unmanned technology, and puts forward the strategy of constructing civil-military integration emergency logistics system with unmanned technology under the new system. © 2022 Journal of Beijing Institute of Technology

9.
SAGE Open ; 12(2), 2022.
Article in English | Scopus | ID: covidwho-1833213

ABSTRACT

Adopting the theory of planned behavior framework, this online experiment investigated the effects of social endorsement cues, message source, and responsibility attribution on young adults’ perceptions of COVID-19 vaccination and intentions to get vaccinated. Four major findings were identified. First, social endorsement cues positively affect attitude, subjective norms, and vaccination intentions. Second, individuals perceive an expert source as the most credible, but a media outlet source results in the most positive subjective norms. Third, responsibility attributions do not generate significant effects on the dependent variables. Finally, social endorsement cues and message source both have some interaction effects with perceived susceptibility to COVID-19 on message outcomes. © The Author(s) 2022.

10.
2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022 ; : 1328-1331, 2022.
Article in English | Scopus | ID: covidwho-1831757

ABSTRACT

Sina Weibo, as a platform for netizens to express their opinions, generates a large amount of public opinion data and constantly generates new topics. How to detect new and hot topics on Weibo is a meaningful studied issue. Document Clustering is a widely studied problem in Text Categorization. K-means is one of the most famous unsupervised learning algorithms, partitions a given dataset into disjoint clusters following a simple and easy way. But the traditional K-means algorithm assigns initial centroids randomly, which cannot guarantee to choose the maximum dissimilar documents as the centroids for the clusters. A modified K-means algorithm is proposed, which uses Jaccard distance measure for assigning the most dissimilar k documents as centroids, and uses Word2vec as the Chinese text vectorization model. The experimental results demonstrate that the proposed K-means algorithm improves the clustering performance, and is able to detect new and hot topics based on Weibo COVID-19 data. © 2022 IEEE.

11.
Bull Exp Biol Med ; 172(6): 721-724, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1820942

ABSTRACT

This study was intended to define T lymphocyte subsets in different clinical groups of COVID-19-infected patients to explore the interaction between T cell-mediated immune response and the severity of COVID-19 course. Lymphopenia in patients with severe COVID-19 was found. In patients with severe COVID-19 course, the absolute counts of CD3+, CD4+, and CD8+ T lymphocytes at admission were lower than on day 14 after discharge. Further analysis showed that the older were the patients with COVID-19, the more likely they developed severe infection. The results confirmed the significance of T lymphocytes in the clearance of the COVID-19.


Subject(s)
COVID-19 , CD8-Positive T-Lymphocytes , Humans , Lymphocyte Count , Lymphocyte Subsets , T-Lymphocyte Subsets
12.
Zhonghua Kou Qiang Yi Xue Za Zhi ; 57(5): 455-461, 2022 May 09.
Article in Chinese | MEDLINE | ID: covidwho-1818247

ABSTRACT

Today, there is greater awareness on the association between oral diseases and respiration diseases after the outbreak of COVID-19. However, confusion regarding the oral health management and medical risk prevention for patients with chronic airway diseases has been remained among dental clinicians. Therefore, the dental experts of the Fifth General Dentistry Special Committee, Chinese Stomatological Association, combined with the experts of respiratory and critical care medicine, undertook the formation of consensus on the oral health management of patients with chronic airway diseases in order to help dental clinicians to evaluate medical risks and make better treatment decision in clinical practice. In the present consensus report, the relationship of oral diseases and chronic airway diseases, the oral health management and the treatment recommendations of patients with chronic airway diseases are provided.


Subject(s)
COVID-19 , Oral Medicine , Consensus , Humans , Oral Health
13.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333829

ABSTRACT

BACKGROUND: Mental health issues have been reported after SARS-CoV-2 infection. However, comparison to prevalence in uninfected individuals and contribution from common risk factors (e.g., obesity, comorbidities) have not been examined. We identified how COVID-19 relates to mental health in the large community-based COVID Symptom Study. METHODS: We assessed anxiety and depression symptoms using two validated questionnaires in 413,148 individuals between February and April 2021;26,998 had tested positive for SARS-CoV-2. We adjusted for physical and mental pre-pandemic comorbidities, BMI, age, and sex. FINDINGS: Overall, 26.4% of participants met screening criteria for general anxiety and depression. Anxiety and depression were slightly more prevalent in previously SARS-CoV-2 positive (30.4%) vs. negative (26.1%) individuals. This association was small compared to the effect of an unhealthy BMI and the presence of other comorbidities, and not evident in younger participants (a40 years). Findings were robust to multiple sensitivity analyses. Association between SARS-CoV-2 infection and anxiety and depression was stronger in individuals with recent (<30 days) vs. more distant (>120 days) infection, suggesting a short-term effect. INTERPRETATION: A small association was identified between SARS-CoV-2 infection and anxiety and depression symptoms. The proportion meeting criteria for self-reported anxiety and depression disorders is only slightly higher than pre-pandemic. FUNDING: Zoe Limited, National Institute for Health Research, Chronic Disease Research Foundation, National Institutes of Health, Medical Research Council UK.

14.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333733

ABSTRACT

BACKGROUND: Characterizing the kinetics of the antibody response to SARSCoV2 is of critical importance to developing strategies that may mitigate the public health burden of COVID-19. We sought to determine how circulating antibody levels change over time following natural infection. METHODS/MATERIALS: We conducted a prospective, longitudinal analysis of COVID-19 convalescent plasma (CCP) donors at multiple time points over a 9-month period. At each study visit, subjects either donated plasma or only had study samples drawn. In all cases, anti-SARS-CoV-2 donor testing was performed using semi-quantitative chemiluminescent immunoassays (ChLIA) targeting subunit 1 (S1) of the SARS-CoV-2 spike (S) protein, and an in-house fluorescence reduction neutralization assay (FRNA). RESULTS: From April to November 2020 we enrolled 202 donors, mean age 47.3 +/-14.7 years, 55% female, 75% Caucasian. Most donors reported a mild clinical course (91%, n=171) without hospitalization. One hundred and five (105) (52%) donors presented for repeat visits with a median 42 (12-163) days between visits. The final visit occurred at a median 160 (53-273) days post-symptom resolution. Total anti-SARS-CoV-2 antibodies (Ab), SARS-CoV-2 specific IgG and neutralizing antibodies were detected in 97.5%, 91.1%, and 74% of donors respectively at initial presentation. Neutralizing Ab titers based on FRNA 50 were positively associated with mean IgG levels (p = <0.0001). Mean IgG levels and neutralizing titers were positively associated with COVID-19 severity, increased donor age and BMI (p=0.0006 and p=0.0028, p=0.0083 and p=0.0363, (p=0.0008 and p=0.0018, respectively). Over the course of repeat visits, IgG decreased in 74.1% of donors;FRNA 50 decreased in 44.4% and remained unchanged in 33.3% of repeat donors. A weak negative correlation was observed between total Ab levels and number of days post-symptom recovery (r = 0.09). CONCLUSION: Anti-SARS-CoV-2 antibodies were identified in 97% of convalescent donors at initial presentation. In a cohort that largely did not require hospitalization. IgG and neutralizing antibodies were positively correlated with age, BMI and clinical severity, and persisted for up to 9 months post-recovery from natural infection. On repeat presentation, IgG anti-SARS-CoV-2 levels decreased in 56% of repeat donors. Overall, these data suggest that CP donors possess a wide range of IgG and neutralizing antibody levels that are proportionally distributed across demographics, with the exception of age, BMI and clinical severity.

15.
IAF Symposium on Integrated Applications 2021 at the 72nd International Astronautical Congress, IAC 2021 ; B5, 2021.
Article in English | Scopus | ID: covidwho-1787346

ABSTRACT

With sudden changes in demand for certain goods, strict border control, and movement restrictions, pandemics can cause an immense disruption of the supply chain especially as it pertains to sustenance goods and job security. The most important recommendations on how this disruption can be mitigated by applying Remote Sensing have been outlined. Earth Observation (EO) and ground data can be used to mitigate the effects of pandemics on the interconnected global and local supply chain;with the COVID-19 pandemic as a case study. The scope of effects by COVID-19 includes issues in the supply chain, operational logistics, and goods production. EO data can be used to track goods like foods, medical kits, hand sanitizers, etc. which in turn aids the reallocation of high-demand goods to areas with limited supply. Satellite-based communication channels will be useful for more remote areas. The supply chain deals with adequate production, the food security issues faced by a significant part of the world's population, can be tackled with an integrated approach. An integrated application of Remote Sensing, (IoT), and Machine Learning is proposed for food security. EO can be used for agricultural monitoring using GNSS coupled with available tools to assess and predict produce status. This is useful in disaster management during restrictions of pandemics;machine learning models can be deployed in conjunction with IoT systems to help with farm monitoring watering of crops using weather data, environment monitoring and fertilizer requirement reminders, and triggering of risk management protocols during disasters. Copyright © 2021 by the International Astronautical Federation (IAF). All rights reserved.

17.
Blood ; 138(SUPPL 1):133, 2021.
Article in English | EMBASE | ID: covidwho-1770356

ABSTRACT

Introduction: Peripheral T-cell lymphomas (PTCL) are a heterogeneous group of lymphomas associated with poor outcomes following anthracycline-based chemotherapy, even when consolidative autologous stem cell transplantation (ASCT) is used. CD30 expression is universal in anaplastic large cell lymphoma (ALCL) and is frequently expressed in other PTCL subtypes. Brentuximab vedotin (BV) is a CD30-directed antibody drug conjugate that prolongs progression-free survival (PFS) and overall survival (OS) when combined with cyclophosphamide, doxorubicin, and prednisone (CHP) as compared to CHOP chemotherapy (Horwitz, 2020). Although a majority of pts treated with BV-CHP remained in durable remission (5y PFS 51%), there is room for improvement. Based on retrospective studies that demonstrated improved outcomes in younger pts, the addition of etoposide to CHOP (CHOEP) is commonly used as initial therapy for PTCL. We performed a multicenter phase 2 trial to evaluate the safety and efficacy of adding etoposide to BV-CHP (CHEP-BV) followed by BV consolidation in pts with newly diagnosed CD30-expressing PTCL. Methods: Adults with newly diagnosed CD30+ (≥ 1% of tumor cells by local pathology) PTCL were eligible, including pts with ALK+ ALCL and IPI score ≥ 2, ALK-negative ALCL, PTCL not otherwise specified (NOS), angioimmunoblastic T-cell lymphoma (AITL), adult Tcell leukemia/lymphoma (ATLL), among others. After accrual of 28 pts, the protocol was amended to allow enrollment of 20 additional pts with CD30+ non-ALCL PTCL (with ALCL allowed in Canada). Pts could receive prephase steroids and/or 1 cycle of CHOPequivalent chemotherapy prior to study entry. 6 pts were treated in a safety lead-in cohort and all pts received CHEP-BV at the recommended phase 2 dose: 6 x 21-day cycles of CHP+BV (1.8mg/kg) on d1 and etoposide 100mg/m2 on d1-3. G-CSF prophylaxis was mandatory. Pts in response after CHEP-BV could receive BV consolidation (1.8mg/kg q3w) for up to 10 additional cycles (16 total BV cycles) either after ASCT or CHEP-BV if no ASCT was performed. The co-primary endpoints were safety and the CR rate (Deauville score 1-3) by PET-CT after CHEP-BV assessed by investigators according to the 2014 Lugano classification. Secondary endpoints were PFS and OS. Results: Accrual has completed and 48 pts were enrolled;all were evaluable for toxicity, 46 were evaluable for efficacy. 16 pts had ALCL (13 ALK+, 3 ALK-) and 32 had non-ALCL PTCL subtypes, including 18 with AITL, 11 with PTCL NOS, 2 with T-follicular helper PTCL, and 1 with ATLL. Baseline characteristics are shown in Table. 43 pts completed CHEP-BV, 2 had progressive disease (PD) prior to completion, 1 pt discontinued CHEP-BV early (MD discretion), 1 pt died due to COVID-19, and 1 remains on CHEP-BV. Of 43 pts who completed CHEP-BV, 24 proceeded to ASCT and 19 did not. 33 (74%) pts received BV consolidation (20 after ASCT, 13 directly after CHEP-BV) and completed a median 8 of the planned 10 cycles (range, 1-10). 13 pts completed all cycles of consolidation;19 pts discontinued early-12 due to adverse events (AE), 5 due to PD, and 2 due to patient/physician choice. The most frequent CHEP-BV related AEs (all grades, G) include fatigue (73%), peripheral sensory neuropathy (67%), anemia (62.5%), nausea (56%), neutropenia (50%), lymphopenia (44%), leukopenia (42%), thrombocytopenia (40%), elevated transaminases (33%). The most common G3+ AEs were neutropenia (37.5%), febrile neutropenia (23%), lymphopenia (21%), anemia (19%), thrombocytopenia (19%). There were 5 deaths, 4 due to PD and 1 due to COVID-19 infection during C3 of CHEP-BV. The interim (n=46) ORR and CR rates (after 3 CHEP-BV cycles, except 1 pt after 2) were 96% and 59% (27 CR, 17 PR), respectively. At completion of CHEP-BV (n=46), the ORR was 91% with 80% CR (37 CR, 5 PR, 4 PD). The ORR/CR rates in ALCL (n=16) vs non-ALCL (n=30) pts were 94%/94% vs 90%/73%, respectively. The ORR/CR rates in pts with CD30 expression 1-9% (n=15) vs 10+% (n=31) were 93%/67% and 90%/87%, respectively. The median follow-up in surviving pts is 1 .1 months (range, 0.9-32.5). The overall 18mo PFS and OS were 61% and 89%;18mo PFS by subgroup: ALCL 81%, non-ALCL 49%, CD30 1-9% 48%, CD30 10+% 67%. Landmark 1y PFS from end of CHEP-BV in responding pts (n=41) was 82% in pts who underwent ASCT vs 48% in pts who did not Conclusions: In a cohort of pts with mostly non-ALCL CD30-expressing PTCL, CHEP-BV (+/-ASCT) followed by BV consolidation was tolerable and effective.

18.
10th International Conference of Educational Innovation through Technology, EITT 2021 ; : 117-122, 2021.
Article in English | Scopus | ID: covidwho-1769575

ABSTRACT

The purpose of this study was to explore elementary school students' perceptions of online learning resources (OLRs) during the COVID-19 pandemic and further examine the factors that influence students' perceptions of OLRs. A total of 396, 269 valid student questionnaires through an open online survey were collected. Data from students' personal characteristics, the facilities of online learning, and students' information literacy were collected to analyze the relationship among these factors and elementary school students' perceptions of OLRs. The results showed that students' personal characteristics, the facilities of online learning, and students' information literacy have significantly affected students' perceptions of OLRs. © 2021 IEEE.

19.
Open Forum Infectious Diseases ; 8(SUPPL 1):S756, 2021.
Article in English | EMBASE | ID: covidwho-1746297

ABSTRACT

Background. Outcomes of COVID-19 have been reported in deceased donor kidney transplant (DDKT) recipients. However, data is limited in patients that underwent recent DDKT. Methods. This single-center retrospective study evaluated the differences in demographics and post-transplant outcomes between those who tested positive and negative for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by polymerase chain reaction, after undergoing recent DDKT. The treatments and outcomes for the SARS-CoV-2-positive patients were assessed. Patients who underwent DDKT from 3/2020 to 8/2020 were included and followed until 9/2020. Results. 201 DDKT recipients were analyzed [14(7%) SARS-CoV-2-positive and 187(93%) negative]. There was no difference in delayed graft function and biopsy-proven rejection between both groups. The patient survival at the end of the study follow-up was lower among SARS-CoV-2-positive patients (Table 1). The median time from DDKT to COVID-19 diagnosis was 45 (range: 8-90) days;5(36%) patients required intensive care unit and 4(29%) required mechanical ventilation;steroids were used in all the patients, therapeutic plasma exchange (TPE) and convalescent plasma (CP) in 7(50%) patients each, remdesivir in 6(43%) and tocilizumab in 1(7%);9(64%) patients recovered, 3(21%) died and two were still requiring mechanical ventilation at the end of the follow-up. Conclusion. Our cohort demonstrated a lower survival rate among SARSCoV-2-positive patients, which highlights the vulnerability of the transplant population. Transplant patients must comply with the CDC recommendations to prevent COVID-19.

20.
2021 Winter Simulation Conference, WSC 2021 ; 2021-December, 2021.
Article in English | Scopus | ID: covidwho-1746008

ABSTRACT

Developing and using the rich data implied by dynamic digital twins and blockchain is relevant to manage both patients and medical resources (e.g., doctors/nurses, ventilators etc.) at the COVID-19 and post COVID period. This paper aims at exploring the blockchain solutions for preparing healthcare systems ready for both efficient operation daily and in pandemic through (1) information integration of patient and medical resource flow from healthcare and medical records;(2) optimizing the deployment of such resources based on hospitals, regions and local pandemic levels switching from normal to the outbreak. The main idea is to develop the concepts of the novel framework for creating an inter-hospital resilient network for pandemic response based on blockchain and dynamic digital twin, which will set up innovative ways to best care for patients, protect NHS staff, and support government scientific decisions to beat COVID-19 now and manage the crisis in the future. © 2021 IEEE.

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