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1.
Archives of Biological Sciences ; 73(4):447-455, 2021.
Article in English | Web of Science | ID: covidwho-1613485

ABSTRACT

Inhibition of vascular endothelial growth factor (VEGF) has been widely applied in anti-neovascularization therapies. As a novel anti-VEGF agent, KH902 (conbercept) is designed to restrain pathological angiogenesis. However, the effects of KH902 on retinal hypoxia have not been well studied. In a mouse model of oxygen-induced retinopathy (OIR), we assessed retinal hypoxia at postnatal days 14 (P14) and P17, as well as retinal neovascularization (RNV) at P17. In addition, we evaluated the protein level of VEGF and galectin-1 (Gal-1). Changes of the neuroretinal structure were also examined. Our results indicated that KH902 could remit retinal hypoxia in OIR at P14 and P17, which was an exciting novel finding for KH902 function. Additionally, we confirmed that KH902 markedly reduces RNV. Our results indicated that administration of KH902 downregulated VEGF expression, as well as Gal-1. Damage of neuroretinal structure after KH902 injection was not observed, which was also an encouraging result. Our study suggests that KH902 plays a role in alleviating retinal hypoxia and that it could be used for the treatment of other ncovascular ocular diseases.

2.
Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021 ; 2:886-896, 2021.
Article in English | Scopus | ID: covidwho-1610609

ABSTRACT

Under the pandemic of COVID-19, people experiencing COVID19-related symptoms have a pressing need to consult doctors. Because of the shortage of medical professionals, many people cannot receive online consultations timely. To address this problem, we aim to develop a medical dialog system that can provide COVID19-related consultations. We collected two dialog datasets - CovidDialog - (in English and Chinese respectively) containing conversations between doctors and patients about COVID-19. While the largest of their kind, these two datasets are still relatively small compared with generaldomain dialog datasets. Training complex dialog generation models on small datasets bears high risk of overfitting. To alleviate overfitting, we develop a multi-task learning approach, which regularizes the data-deficient dialog generation task with a masked token prediction task. Experiments on the CovidDialog datasets demonstrate the effectiveness of our approach. We perform both human evaluation and automatic evaluation of dialogs generated by our method. Results show that the generated responses are promising in being doctorlike, relevant to conversation history, clinically informative and correct. © 2021 Association for Computational Linguistics.

3.
Chinese Journal of Disease Control and Prevention ; 25(4):427-431, 2021.
Article in Chinese | Scopus | ID: covidwho-1566858

ABSTRACT

Objective During the COVID-19 epidemic period, we investigated the cognitive level of COVID-19 knowledge of medical staffs in Anhui Province and analyzed the influencing factors of cognitive level of COVID-19 knowledge. Methods From February 12, 2020 to March 4, 2020, a self-made questionnaire was used to evaluate the knowledge of COVID-19 among medical staff in Anhui Province. A total of 15 342 valid questionnaires were obtained. By SPSS 17.0 statistical software, and descriptive analysis, t-test, ANOVA analysis, and multiple linear regression were used to analyze the cognitive level of COVID-19 knowledge of medical staffs and the influencing factors. Results The total score of COVID-19 knowledge of medical staffs in Anhui Province was (6.95±2.67) points, the average score of diagnosis knowledge was (2.58±1.74) points, the average score of treatment knowledge was (1.53±1.03) points, and the score of nosocomial infections knowledge was (2.84±1.01) points. There were significant differences in COVID-19 diagnosis knowledge, nosocomial infections knowledge and total score between doctors and nurses (all P < 0.05). Multivariate linear regression analysis showed that the scores in senior and intermediate professional title groups were higher than those in primary professional title group;the scores in master′s degree group and above and undergraduate education group were higher than those in junior college education group;the knowledge scores in municipal, county-level hospitals, primary medical institutions and private medical institutions were lower than those in provincial hospital group;the scores in patients aged 30~ years and ≥40 years were lower than those in group < 30 years. The scores in senior and intermediate professional title groups were higher than those in junior professional title group;the scores in municipal, county-level hospitals, primary medical institutions and private medical institutions were lower than those in provincial hospitals;the scores of 30~ years old and ≥40 years old were lower than those of < 30 years old group, and the scores of nurses with bachelor′s degree were higher than junior college degree or below (all P < 0.05). Conclusions The score of COVID-19 knowledge of medical staffs in Anhui Province is low, so we should train them COVID-19 knowledge systematically. We should pay attention to the influencing factors like occupation, title, education background, age and hospital rank when selecting and training anti-epidemic medical staffs. © 2021, Publication Centre of Anhui Medical University. All rights reserved.

4.
11th International Conference on Computer Engineering and Networks, CENet2021 ; 808 LNEE:196-202, 2022.
Article in English | Scopus | ID: covidwho-1549397

ABSTRACT

Real-time data processing refers to the process by which the computer collects and processes field data in the actual time when it occurs. At present, there are many drawbacks to the traditional real-time data processing model. For example, developing a real-time processing model requires developers have high technical skills. And the model deployment and task monitoring are very inconvenient. Spark Streaming is currently the most popular real-computing framework. It has good scalability, high throughput, and fault tolerance mechanism.According to the characteristics of epidemic diffusion, this paper designs an epidemic real-time monitoring model based on the Spark Streaming algorithm and develops a visual and interactive real-time epidemic monitoring system for the novel coronavirus pneumonia (COVID-19) epidemic in a timely and effective manner. At last, a epidemic diffusion system is developed and the COVID-19 epidemic diffusion can be simulated as a graphic interface. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

5.
Zhonghua Liu Xing Bing Xue Za Zhi ; 42(10): 1757-1762, 2021 Oct 10.
Article in Chinese | MEDLINE | ID: covidwho-1534275

ABSTRACT

Objective: To analyze the epidemiological characteristics of close contacts of COVID-19 cases and infection-related risk factors in Beijing and provide evidences for COVID-19 prevention and control. Methods: A total of 20 681 close contacts of COVID-19 cases, who had exposures during January 6, 2020 to February 15, 2021, were traced in Beijing. The information about their demographic characteristics, exposure history, and quarantine outcomes were collected and analyzed with descriptive statistics. The logistic regression analysis was used to identify the risk factors for COVID-19. Results: The infection rate SARS-CoV-2 in close contacts was 2.16% (447/20 681). The age M(P25, P75) was 35 (27, 49) years. The majority of the close contacts were aged 20-59 years, accounting for 81.77% (16 912/20 681). Centralized isolation was the major type of medical observation, accounting for 82.15% (16 989/20 681). Among the exposure types, working and studying in the same room (16.06%, 3 322/20 681), sharing same transport vehicle (12.88%, 2 664/20 681), performing diagnosis and treatment nursing (7.80%,1 612/20 681), and living together (7.23%,1 495/20 681), accounting for 43.96% (9 093/20 681). The index cases included staff (19.34%, 3 999/20 681), the unemployed (17.34%, 3 586/20 681), people engaged in business service (13.85%, 2 864/20 681), people engaged in food service (10.77%, 2 228/20 681), their close contacts accounted for 61.30% (12 677/20 681). Multivariate logistic regression analysis showed that compared with other types of exposure, the risk factors for infection were having meal together (OR=3.96, 95%CI: 2.30-6.83) and living together (OR=6.41, 95%CI:4.48-9.17); Compared with the other occupations, the index case being engaged in food service (OR=3.06, 95%CI:1.29-7.25) and teacher (OR=4.94, 95%CI:1.43-17.08) were risk factors for the infection. Conclusions: The main environmental exposure types of SARS-CoV-2 infection in close contacts were having meal together and living together. Contact with the index case being engaged in food service and teacher increased the risk for COVID-19. Comprehensive prevention and control measures such as centralized isolation and vaccination should be continued.


Subject(s)
COVID-19 , Beijing , Contact Tracing , Humans , Risk Factors , SARS-CoV-2
6.
2021 IEEE International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology, CEI 2021 ; : 344-347, 2021.
Article in English | Scopus | ID: covidwho-1522557

ABSTRACT

The current pandemic of COVID-19 has brought certain difficulties to the detection and diagnosis. With the continuous development of medical imaging technology, chest radiograph has become a common examination method for detecting lung diseases. Reasonable use of new coronary pneumonia chest radiographs and machine learning related algorithms to achieve efficient, accurate and automatic identification of covid-19 is extremely important. Based on the detection of four types of COVID-19, this paper proposes a method for the detection and classification of COVID-19 based on the YOLOv5 model. Experimental results show that our algorithm has the best performance compared with other deep learning algorithms. Specifically, the map@0.5 index of the prediction result of our algorithm model is 0.605, which is 32.096% and 18.627% larger than the Fast RCNN algorithm and the Efficient Net model respectively. © 2021 IEEE.

7.
2021 International Symposium on Educational Technology, ISET 2021 ; : 84-88, 2021.
Article in English | Scopus | ID: covidwho-1470343

ABSTRACT

The spread of the COVID-19 pushed K-12 schools to swift their traditional face-to-face in-person classes to online classes. This study examined middle school students' perception of usefulness in online classes, as well as the relationship between perceived usefulness and its key influencing factors. A questionnaire survey was conducted on 350 7th-9th grade students in China who had synchronous online classes during the outbreak of COVID-19. Results showed that students' overall perception of the usefulness of the online class was positive, comparing to the traditional face-to-face class. The relationships of students' perceived social presence, sense of community, and ease of use on their perceived usefulness of the online class were tested by multiple regression. The results indicated that students' perceived social presence and ease of use online learning system were two significant predictors of their perceived usefulness of the online classes. The findings of this study suggest that online learning can be further integrated into the K-12 curriculum and activities after the COVID-19 pandemic to make the K-12 school system more flexible, resilient, and enriching. © 2021 IEEE.

8.
Natural Gas Industry ; 41(8):143-152, 2021.
Article in Chinese | Scopus | ID: covidwho-1448961

ABSTRACT

China's shale gas production in 2020 exceeds 200×108 m³, which creates a miracle in the history of natural gas development in China. The Sichuan Basin has already been and will be the main battlefield of shale gas exploration and development in China. In order to further promote the large-scale efficient development of shale gas in China, under the new situation of global COVID-19 spread and domestic "carbon peak and carbon neutrality" goal, this paper analyzes the progress and challenges of shale gas exploration and development in the Sichuan Basin from four aspects, including resource exploration, gas reservoir engineering, drilling and production engineering and industrial regulation, and puts forward countermeasures and suggestions for achieving large-scale efficient development of shale gas. And the following research results are obtained. First, the large-scale efficient development of shale gas in the Sichuan Basin has to take the sustainable and stable production of middle-shallow shale gas and the large-scale productivity construction of deep shale gas as the base. Second, compared with the shale gas exploration and development in the North America, the Sichuan Basin has its own characteristics in terms of geographical setting, geological condition, drilling and production technology and industrial regulation, which makes it difficult to copy the development mode of large scale, high density and continuous well deployment from the North America, so it is necessary to adopt the strategy of "high production with few wells". On the one hand, continue to apply the geology and engineering integration technology to carry out "integrated research, integrated design, integrated implementation and integrated iteration" in the whole life cycle of shale gas well;and on the other hand, carry out problem-oriented continuous researches from the aspects of geological evaluation, development policy, engineering technology and industrial regulation, so as to improve geological evaluation theory and technology, innovate gas reservoir engineering theory and method, research and develop engineering technology for cost reduction and efficiency improvement, improve shale gas industrial regulation, and form a new pattern of collaborative promotion of technical and non-technical elements. In conclusion, the research results provide important reference and guidance for the large-scale efficient development of shale gas in the Sichuan Basin and even the whole country. © 2021, Natural Gas Industry Journal Agency. All right reserved.

9.
14th International Conference on Blended Learning, ICBL 2021 ; 12830 LNCS:92-102, 2021.
Article in English | Scopus | ID: covidwho-1391731

ABSTRACT

Covid-19 pandemic has triggered the popularity of online instruction, a large-scale college students have been forced to convert in-person learning to online instruction at the first time. In this study, 226 students were selected to find out what are beginners’ perceptions of online learning outcomes and technological barriers, and what are the technological barriers affecting online learning outcomes. The results showed that the beginners had positive attitude on the outcomes of online learning. Belief was the main second-order barrier of online instruction. Training was the main first-order barrier, and access and vision had impact on part of online learning outcomes. © 2021, Springer Nature Switzerland AG.

10.
Journal of Neurorestoratology ; 9(1):1-12, 2021.
Article in English | Web of Science | ID: covidwho-1389963

ABSTRACT

COVID-19 has been an emerging and rapidly evolving risk to people of the world in 2020. Facing this dangerous situation, many colleagues in Neurorestoratology did their best to avoid infection if themselves and their patients, and continued their work in the research areas described in the 2020 Yearbook of Neurorestoratology. Neurorestorative achievements and progress during 2020 includes recent findings on the pathogenesis of neurological diseases, neurorestorative mechanisms and clinical therapeutic achievements. Therapeutic progress during this year included advances in cell therapies, neurostimulation/neuromodulation, brain-computer interface (BCI), and pharmaceutical neurorestorative therapies, which improved neurological functions and quality of life for patients. Four clinical guidelines or standards of Neurorestoratology were published in 2020. Milestone examples include: 1) a multicenter randomized, double-blind, placebo-controlled study of olfactory ensheathing cell treatment of chronic stroke showed functional improvements;2) patients after transhumeral amputation experienced increased sensory acuity and had improved effectiveness in work and other activities of daily life using a prosthesis;3) a patient with amyotrophic lateral sclerosis used a steady state visual evoked potential (SSVEP) based BCI to achieve accurate and speedy computer input;4) a patient with complete chronic spinal cord injury recovered both motor function and touch sensation with a BCI and restored ability to detect objects by touch and several sensorimotor functions. We hope these achievements motivate and encourage other scientists and physicians to increase neurorestorative research and its therapeutic applications.

11.
35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence ; 35:4821-4829, 2021.
Article in English | Web of Science | ID: covidwho-1381682

ABSTRACT

The COVID-19 pandemic has spread globally for several months. Because its transmissibility and high pathogenicity seriously threaten people's lives, it is crucial to accurately and quickly detect COVID-19 infection. Many recent studies have shown that deep learning (DL) based solutions can help detect COVID-19 based on chest CT scans. However, most existing work focuses on 2D datasets, which may result in low quality models as the real CT scans are 3D images. Besides, the reported results span a broad spectrum on different datasets with a relatively unfair comparison. In this paper, we first use three state-of-the-art 3D models (ResNet3D101, DenseNet3D121, and MC3 18) to establish the baseline performance on three publicly available chest CT scan datasets. Then we propose a differentiable neural architecture search (DNAS) framework to automatically search the 3D DL models for 3D chest CT scans classification and use the Gumbel Softmax technique to improve the search efficiency. We further exploit the Class Activation Mapping (CAM) technique on our models to provide the interpretability of the results. The experimental results show that our searched models (CovidNet3D) outperform the baseline human-designed models on three datasets with tens of times smaller model size and higher accuracy. Furthermore, the results also verify that CAM can be well applied in CovidNet3D for COVID-19 datasets to provide interpretability for medical diagnosis. Code: https://github.com/HKBU-HPML/CovidNet3D.

12.
Frontiers in Environmental Science ; 9, 2021.
Article in English | Scopus | ID: covidwho-1367748

ABSTRACT

COVID-19 is a highly infectious disease and public health hazard that has been wreaking havoc around the world;thus, assessing and simulating the risk of the current pandemic is crucial to its management and prevention. The severe situation of COVID-19 around the world cannot be ignored, and there are signs of a second outbreak;therefore, the accurate assessment and prediction of COVID-19 risks, as well as the prevention and control of COVID-19, will remain the top priority of major public health agencies for the foreseeable future. In this study, the risk of the epidemic in Guangzhou was first assessed through logistic regression (LR) on the basis of Tencent-migration data and urban point of interest (POI) data, and then the regional distribution of high- and low-risk epidemic outbreaks in Guangzhou in February 2021 was predicted. The main factors affecting the distribution of the epidemic were also analyzed by using geographical detectors. The results show that the number of cases mainly exhibited a declining and then increasing trend in 2020, and the high-risk areas were concentrated in areas with resident populations and floating populations. In addition, in February 2021, the “Spring Festival travel rush” in China was predicted to be the peak period of population movement. The epidemic risk value was also predicted to reach its highest level at external transportation stations, such as Baiyun Airport and Guangzhou South Railway Station. The accuracy verification showed that the prediction accuracy exceeded 99%. Finally, the interaction between the resident population and floating population could explain the risk of COVID-19 to the highest degree, which indicates that the effective control of population agglomeration and interaction is conducive to the prevention and control of COVID-19. This study identifies and predicts high-risk areas of the epidemic, which has important practical value for urban public health prevention and control and containment of the second outbreak of COVID-19. © Copyright © 2021 He, Zhou, Wang and Yuan.

13.
2nd International Conference on Digital Health and Medical Analytics, DHA 2020 ; 1412:127-132, 2021.
Article in English | Scopus | ID: covidwho-1361254

ABSTRACT

Hospitals are suffering from a critical challenge induced by the rapid spread of Coronavirus disease 2019 (COVID-19). Not only have patients been marginalized, but many clinicians working in the region-al hospitals have limited access to the specialist consultations and treatment guidelines they need from provincial-level hospitals to manage pneumonia cases caused by COVID-19. Telemedicine has been acknowledged as a breakthrough technology in combating epidemics. This study aims to demonstrate the implementation of Emergency Telemedicine Consultation System (ETCS) since COVID-2019 first emerged in Henan Province, beginning in late December 2019. This system was developed for coronavirus care across 126 connected hospitals, serving as the overarching authoritative source for diagnostic decision making and knowledge sharing for treatment. The information shared could rapidly expand to enable open collaborations with key stakeholders such as government authorities, research institutions and laboratories. The experience from building this system during this crisis can provide insights to guide public health institutions as they implement telemedicine to increase resilience to future epidemic outbreaks. © 2021, Springer Nature Singapore Pte Ltd.

14.
3rd IEEE International Conference on Communications, Information System and Computer Engineering, CISCE 2021 ; : 555-561, 2021.
Article in English | Scopus | ID: covidwho-1345844

ABSTRACT

The paper uses the literature research method to establish a comprehensive service quality evaluation system for China's aviation with 4 services, such as air service, ground service, which are the first-level indicators and 20 specific services as the second-level indicators;and a key service quality evaluation system during the epidemic period with 7 services, such as disinfection service and body temperature monitoring services as the first-level indicators and 23 specific services as second-level indicators. With the help of aviation service data from 2017 to 2020, we dynamically evaluate the service quality of China's aviation under normal conditions and epidemic situation by Analytical Hierarchy Process and Fuzzy Comprehensive Evaluation method. In addition, based on customer satisfaction, a method of Important Quadrant Model was proposed to display the evaluation results and provide service improvements suggestion. The paper establishes a common and personalized indicator system, uses the AHP-FCE method and combines aviation service satisfaction data to dynamically evaluate the quality of aviation services, and improves the scientificity and objectivity of the evaluation. © 2021 IEEE.

15.
2021 International Conference on Management of Data, SIGMOD 2021 ; : 2839-2845, 2021.
Article in English | Scopus | ID: covidwho-1299240

ABSTRACT

Computing technology has enabled massive digital traces of our personal lives to be collected and stored. These datasets play an important role in numerous real-life applications and research analysis, such as contact tracing for COVID 19, but they contain sensitive information about individuals. When managing these datasets, privacy is usually addressed as an afterthought, engineered on top of a database system optimized for performance and usability. This has led to a plethora of unexpected privacy attacks in the news. Specialized privacy-preserving solutions usually require a group of privacy experts and they are not directly transferable to other domains. There is an urgent need for a generally trustworthy database system that offers end-to-end security and privacy guarantees. In this tutorial, we will first describe the security and privacy requirements for database systems in different settings and cover the state-of-the-art tools that achieve these requirements. We will also show challenges in integrating these techniques together and demonstrate the design principles and optimization opportunities for these security and privacy-aware database systems. This is designed to be a three hour tutorial. © 2021 ACM.

16.
Frontiers of Economics in China ; 15(4):521-540, 2020.
Article in English | Scopus | ID: covidwho-1256709

ABSTRACT

This paper addresses the reactions of domestic helpers to the Wuhan (Hubei Province) lockdown that began on January 23, 2020. We use a novel dataset containing the information of over 40,000 Chinese domestic helpers registered on a leading professional website from November 2019 to June 2020. The results indicate a declining pattern of short-term labor supply of domestic helpers across 11 major Chinese cities, which shows an increase in the expected monthly wage of domestic helpers in these cities. More importantly, using a difference-in-difference (DID) model, this paper provides some evidence on the existence of labor market discrimination against domestic helpers born in Hubei Province due to employers’ fear of infection. © 2020 Higher Education Press Limited Company. All rights reserved.

17.
18.
Cancer Research ; 81(4 SUPPL), 2021.
Article in English | EMBASE | ID: covidwho-1186386

ABSTRACT

Background: Triple-negativebreast cancer (TNBC) has the highest rate of distant metastasis and poorestoverallsurvival among all breast cancer subtypes. Adagloxad simolenin (AS;OBI-822)is a therapeutic vaccine comprisingthe synthetically manufactured tumor-associatedantigen Globo H linked to the carrier protein keyhole limpethemocyanin (KLH).The KLH provides antigenic immune recognition and T-cell responses. AS isco-administered witha saponin-based adjuvant OBI-821 to induce a humoralresponse. A phase 2 trial showed that AS/OBI-821exhibiteda trend for superior progression-free survival vs placebo in patientswhose breast cancers had higher GloboHexpression. Administrationof AS/OBI-821 resulted in IgM and IgG anti-Globo H humoral response and atrendtowards improved PFS in patients with metastatic breast cancer overexpressingGlobo H. We describe therationale and design of GLORIA, an ongoing Phase III,randomized, open-label study to evaluate efficacy, safety, and quality of life(QoL) of AS plus standard of care (SOC) versus SOC alone in patients with high-risk, early-stage TNBC. The primary endpoint is invasive progression-freesurvival;secondary endpoints include overall survival, QoL, breastcancer-freeinterval, distant disease-free survival, safety, and tolerability. Trial Design: A phase 3 trial was initiated inDecember 2018 and had been slowly enrolling until being put on holddue to theCovid-19 pandemic. While the study wason hold the design waschanged from a placebo-control to astandard-of-care control trial based onfeedback from investigators and leading breast cancer advisers, that thenumberof placebo injections was a serious burden on patients. Furthermore, it wasapparent that blinding wasquestionable given the expected and frequent localskin inflammation and low-grade fevers that accompany theAS/OBI-821 vaccineadministration and the absence of these obvious clinical signs and symptoms with the normalsaline placebo control.The main changes to the protocol are as follows:Methods: Eligibility includes patients with TNBC (estrogen receptor/progesterone receptor <5%,and HER2-negative) with nonmetastatic disease and 1) either residual invasive disease of ≥1 cm in breast or ≥1 positiveaxillary node following neoadjuvantchemotherapy;Pathological Stage IIB or III disease treated with adequateadjuvant chemotherapy alone;received ≥4 cycles of standard taxane- and/oranthracycline-basedchemotherapy;randomized within 12 weeks of surgery, adjuvant multi-agent chemotherapy,or radiation therapy.Inaddition, tumors must express Globo H (H-score of ≥15 by central laboratory analysis using a validatedimmunohistochemical assay). Subjects in the AS/OBI-821 group will receive 30 μg of AS in combination with 100 μgofOBI-821.This revised study will start re-enrolling patients as soon as Covid-19 restrictions are lifted with the firstcountry being South Korea with an anticipated start date in Q4/2020.

19.
Chinese Journal of Clinical Infectious Diseases ; 13(1):25-28, 2020.
Article in Chinese | Scopus | ID: covidwho-1143642
20.
Preprint in English | PubMed | ID: ppcovidwho-8164

ABSTRACT

Background: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response [1,2]. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) [3] Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. Methods: We conducted a descriptive cohort study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11 (th) June 2020 and are iteratively updated via GitHub [4]. Findings: We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19 , and 113,627 hospitalized with COVID-19 requiring intensive services . All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts, and are available in an interactive website: https://data.ohdsi.org/Covid19CharacterizationCharybdis/. Interpretation: CHARYBDIS findings provide benchmarks that contribute to our understanding of COVID-19 progression, management and evolution over time. This can enable timely assessment of real-world outcomes of preventative and therapeutic options as they are introduced in clinical practice.

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