[Clinical characteristics and short-term prognosis of 22 cases with SARS-CoV-2 infection associated acute encephalopathy].

Objective: To investigate the clinical features and short-term prognosis of patients with SARS-CoV-2 infection associated acute encephalopathy (AE). Methods: Retrospective cohort study. The clinical data, radiological features and short-term follow-up of 22 cases diagnosed with SARS-CoV-2 infection associated AE in the Department of Neurology, Beijing Children's Hospital from December 2022 to January 2023 were retrospectively analyzed. The patients were divided into cytokine storm group, excitotoxic brain damage group and unclassified encephalopathy group according to the the clinicopathological features and the imaging features. The clinical characteristics of each group were analyzed descriptively. Patients were divided into good prognosis group (≤2 scores) and poor prognosis group (>2 scores) based on the modified Rankin scale (mRS) score of the last follow-up. Fisher exact test or Mann-Whitney U test was used to compare the two groups. Results: A total of 22 cases (12 females, 10 males) were included. The age of onset was 3.3 (1.7, 8.6) years. There were 11 cases (50%) with abnormal medical history, and 4 cases with abnormal family history. All the enrolled patients had fever as the initial clinical symptom, and 21 cases (95%) developed neurological symptoms within 24 hours after fever. The onset of neurological symptoms included convulsions (17 cases) and disturbance of consciousness (5 cases). There were 22 cases of encephalopathy, 20 cases of convulsions, 14 cases of speech disorders, 8 cases of involuntary movements and 3 cases of ataxia during the course of the disease. Clinical classification included 3 cases in the cytokine storm group, all with acute necrotizing encephalopathy (ANE); 9 cases in the excitotoxicity group, 8 cases with acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) and 1 case with hemiconvulsion-hemiplegia syndrome; and 10 cases of unclassified encephalopathy. Laboratory studies revealed elevated glutathione transaminase in 9 cases, elevated glutamic alanine transaminase in 4 cases, elevated blood glucose in 3 cases, and elevated D-dimer in 3 cases. Serum ferritin was elevated in 3 of 5 cases, serum and cerebrospinal fluid (CSF) neurofilament light chain protein was elevated in 5 of 9 cases, serum cytokines were elevated in 7 of 18 cases, and CSF cytokines were elevated in 7 of 8 cases. Cranial imaging abnormalities were noted in 18 cases, including bilateral symmetric lesions in 3 ANE cases and "bright tree appearance" in 8 AESD cases. All 22 cases received symptomatic treatment and immunotherapy (intravenous immunoglobulin or glucocorticosteroids), and 1 ANE patient received tocilizumab. The follow-up time was 50 (43, 53) d, and 10 patients had a good prognosis and 12 patients had a poor prognosis. No statistically significant differences were found between the two groups in terms of epidemiology, clinical manifestations, biochemical indices, and duration of illness to initiate immunotherapy (all P>0.05). Conclusions: SARS-CoV-2 infection is also a major cause of AE. AESD and ANE are the common AE syndromes. Therefore, it is crucial to identify AE patients with fever, convulsions, and impaired consciousness, and apply aggressive therapy as early as possible.

Logistics System Risk Analysis Using FMEA-AHP Methodology: During and after the COVID-19 pandemic

The COVID-19 pandemic broke out, and the global logistics industry suffered severe losses, therefore, the FMEA-AHP (Failure Mode and Effects Analysis-Analytic Hierarchy Process) method is proposed to analyze the failure reasons of the logistics system in the COVID-19 pandemic. In this article, we have made an improvement on the basis of the traditional FMEA method: The AHP is integrated into the FMEA algorithm (referred to as RPWN (risk priority weighted number) in this article). In this algorithm, the AHP is to determine the weights of risk indicators. Meanwhile, in this article, we also consider about the new logistics failures, such as the failure modes and failure reasons of the logistics system under the COVID-19 pandemic. 12 failures have been identified, and corresponding preventive and corrective measures have been suggested to cut off the path of failure propagation and reduce the impact of failures. © 2022 ACM.

An Edge Based Framework for Risk Assessment of Communicable Disease

Along with the development of edge computing and Artificial Intelligence (AI), there has been an explosion of health-care system. As COVID-19 spread globally, the pandemic created significant challenges for the global health system. Therefore, we proposed an edge-based framework for risk assessment of communicable disease called CDM-FL. The CDM-FL consists of two modules, the common data model (CDM) and federated learning (FL). The CDM can process and store multi-source heterogeneous data with standardized semantics and schema. This provides more data for model training using medical data globally. The model is deployed on edge nodes that can measure patients' status locally and with low latency. It also keeps patient privacy from being disclosed that patient are more likely to share their medical data. The results based on real-world data show that CDM-FL can help physicians to evaluate the risk of communicable disease as well as save lives during severe epidemic situations. © 2022 IEEE.

Mask Wearing Detection Algorithm Based on Improved SSD

In recent years, the COVID-19, which involves a highly infectious virus, has spread worldwide.Wearing masks in public areas can reduce the transmission and hence the spread of the virus.Additionally, using computer vision technology to detect mask wearing behavior in public areas is crucial.To prevent and control epidemics, the correct form of wearing face masks must be identified.In an actual environment, the detection of mask wearing is complex and diverse.The scale of a face wearing a mask is different;furthermore, the difference between the correct and wrong forms of wearing a mask is subtle and hence difficult to detect.Therefore, a mask wearing detection algorithm based on an improved Single Shot Multibox Detector(SSD) algorithm is proposed herein.Based on the SSD network, the algorithm introduces a feature fusion network and an attention coordination mechanism, reconstructs the feature extraction network, and enhances the ability of learning and processing detailed information.In addition, the classification prediction score and IoU score of the algorithm are combined, whereas the Quality Focal Loss(QFL) function is used to adjust the weight of positive and negative samples.An experiment is performed on acustom-developed mask wearing test dataset.Experimental results show that the average accuracy of the algorithm is 96.28%, which is 5.62% higher than that of the original algorithm.The improved algorithm offers good accuracy and practicability for mask wearing detection, as well assatisfies the requirements for epidemic prevention and control. © 2022, Editorial Office of Computer Engineering. All rights reserved.

Integrating CRISPR and isothermal amplification reactions in single-tubes for ultrasensitive detection of nucleic acids: the SARS-CoV-2 RNA example

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (CRISPR-Cas) systems have advanced rapidly for the detection of nucleic acids and molecular diagnoses. The sensitivity of techniques directly using CRISPR-Cas systems for target recognition and signal generation is limited by the kinetics of trans-cleavage. Thus, CRISPR-Cas systems have been coupled with isothermal amplification techniques. One strategy for integrating CRISPR-Cas and amplification reactions into a single-tube is to place reagents in separate locations within the tube, maintaining optimum conditions for each reaction. A more challenging strategy is to mix all reagents and allow nucleic acid amplification and CRISPR-based detection to proceed in a homogeneous solution. This desirable approach requires substantial understanding of the compatibility of enzymatic reactions, systematic optimization, and appropriate adjustments of the integrated reactions to ensure high sensitivity. Ultrasensitive techniques have been developed for the detection of SARS-CoV-2 in single-tubes. In this review, we highlight the principle, research needs, and challenges of ultrasensitive single-tube RNA detection using CRISPR technology. We stress the importance of understanding the kinetics of trans-cleavage activity of CRISPR-Cas systems. © 2022 Scientia Sinica Chimica. All rights reserved.

Food loss and waste: A carbon footprint too big to be ignored

Eight to ten percent of total global greenhouse gas emissions are associated with food loss and waste. Tackling the challenges of food loss and sustainable food waste management is key to fulfilling the Paris Agreement. However, among the Nationally Determined Contributions to the Paris Agreement, very few countries make references to food loss and waste. In this work, we reviewed the problem of food loss and waste from a global viewpoint and highlighted the opportunities of managing food loss and waste towards carbon mitigation and beyond. The importance of developing a coherent collaboration among all associated stakeholders was implied. Some recent policy developments and the impacts of COVID-19 pandemic are discussed followed by the summarization of potential solutions to tackling the fool loss and waste challenge.

Primary analysis of MOUNTAINEER: A phase 2 study of tucatinib and trastuzumab for HER2-positive mCRC

Background: Despite the occurrence of HER2 amplification/overexpression (HER2+) in ~3% to 5% of all patients with metastatic colorectal cancer (mCRC) and up to ~10% of patients with RAS/BRAF wild-type mCRC, there are currently no FDA- or EMA-approved HER2-directed therapies for HER2+ mCRC. Patients with mCRC who progress on early lines of chemotherapy regimens receive limited clinical benefit from current standard-of-care treatments. Tucatinib is a highly selective, HER2-directed, tyrosine kinase inhibitor. The MOUNTAINEER trial (NCT03043313) was initiated to evaluate the efficacy and safety of the investigational combination of tucatinib with trastuzumab in patients with HER2+ mCRC. Here we present results from the primary analysis of MOUNTAINEER. Methods: MOUNTAINEER is a multi-center, open-label, randomised, phase 2 trial conducted in the US and Europe. Eligible patients had HER2+ (one or more local tests: 3+ immunohistochemistry, 2+ immunohistochemistry with amplification by in situ hybridization, or amplification by next‑generation sequencing of tumor tissue) and RAS wild-type mCRC with progression on or intolerance to fluoropyrimidine, oxaliplatin, irinotecan, and an anti-VEGF antibody. Measurable disease and an ECOG performance status of 0–2 were required. Previous HER2-directed therapies were not permitted. The trial initially consisted of a single cohort (Cohort A) to be treated with tucatinib (300 mg PO BID) and trastuzumab (8 mg/kg IV then 6 mg/kg IV every 3 weeks). The trial was expanded to include patients randomised 4:3 to receive tucatinib + trastuzumab (Cohort B) or tucatinib monotherapy (Cohort C). The primary endpoint is confirmed objective response rate (ORR) per RECIST 1.1 by blinded independent central review (BICR) in Cohorts A+B. Secondary endpoints include duration of response (DOR), progression-free survival (PFS), overall survival (OS), and safety and tolerability. Results: MOUNTAINEER enrolled 117 patients between 08Aug2017 and 22Sept2021. Data cutoff was 28Mar2022. The median age was 56.0 years (range, 24, 77), and baseline characteristics were balanced across cohorts. Eighty-six patients received at least 1 dose of study treatment in Cohorts A+B, and 30 patients received tucatinib monotherapy in Cohort C (total, 116). The overall median duration of follow-up was 16.3 months (IQR, 10.8, 28.2). In Cohorts A+B, the confirmed ORR by BICR was 38.1% (95% CI, 27.7, 49.3). The median DOR was 12.4 months (95% CI, 8.5, 20.5). The median PFS was 8.2 months (95% CI, 4.2, 10.3), and the median OS was 24.1 months (95% CI, 20.3, 36.7). The most common adverse events (AEs) in Cohorts A+B were diarrhoea (64.0%), fatigue (44.2%), nausea (34.9%), and infusion-related reaction (20.9%);the most common AE of grade ≥3 was hypertension (7.0%). Adverse events leading to tucatinib discontinuation in Cohorts A+B occurred in 5.8% of patients and included alanine amino transferase increase (2.3%), COVID-19 pneumonia (1.2%), cholangitis (1.2%), and fatigue (1.2%). No deaths resulted from AEs. Conclusions: In patients with chemotherapy-refractory HER2+ mCRC, tucatinib in combination with trastuzumab was well tolerated with clinically meaningful antitumor activity including durable responses and a median overall survival of 2 years. Tucatinib in combination with trastuzumab has the potential to become a new standard of care for patients with HER2+ mCRC. Clinical trial identification: NCT03043313. Editorial acknowledgement: The authors thank Joseph Giaconia of MMS Holdings, Michigan, USA for providing medical writing support/editorial support, which was funded by Seagen Inc., Bothell, WA, USA in accordance with Good Publication Practice (GPP3) guidelines. Legal entity responsible for the study: Seagen Inc. Funding: Seagen Inc. Disclosures: J. Strickler: Advisory / Consultancy: Seagen, Bayer, Pfizer;Research grant / Funding (institution): Amgen, Roche/Genentech, Seagen. A. Cercek: Advisory / Consultancy: Bayer, Merck, Seagen;Research grant / Funding (institution): Seagen, GSK, Rgenix. T. André: Honoraria (self : Amgen, Astra-Zeneca, Bristol-Myers Squibb, Gritstone Oncology, GlaxoSmithKline, Haliodx, Kaleido Biosciences, Merck & Co., Inc., Pierre Fabre, Sanofi, Servier, Merck & Co., Inc, Servier;Advisory / Consultancy: Astellas Pharma, BMS, Gritstone Oncology, Transgène, Roche/Ventana, Seagen, Merck & Co., Inc, Servier;Research grant / Funding (institution): BMS, Seagen, GSK;Travel / Accommodation / Expenses: BMS, Merck & Co., Inc. K. Ng: Advisory / Consultancy: Seattle Genetics, Bicara Therapeutics, GlaxoSmithKline;Research grant / Funding (institution): Pharmavite, Evergrande Group, Janssen. E. Van Cutsem: Advisory / Consultancy: AbbVie, Array, Astellas, AstraZeneca, Bayer, Beigene, Biocartis, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Daiichi, Halozyme, GSK, Helsinn, Incyte, Ipsen, Janssen Research, Lilly, Merck Sharp & Dohme, Merck KGaA, Mirati, Novartis, Pierre Fabre, Roche, Seattle Genetics, Servier, Sirtex, Terumo, Taiho, TRIGR, Zymeworks;Research grant / Funding (institution): Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Ipsen, Lilly, Merck Sharp & Dohme, Merck KGaA, Novartis, Roche, Servier. C. Wu: Research grant / Funding (institution): Seagen. A. Paulson: Research grant / Funding (institution): Seattle Genetics. J. Hubbard: Research grant / Funding (institution): Seattle Genetics. H. Lenz: Honoraria (self): BMS, Bayer, Roche;Advisory / Consultancy: Bayer, Merck, Roche;Travel / Accommodation / Expenses: BMS, Bayer, Merck KG;Shareholder / Stockholder / Stock options: Fulgent. M. Stecher: Full / Part-time employment: SeaGen. W. Feng: Full / Part-time employment: Seagen. T. Bekaii-Saab: Honoraria (self): Royalties: Uptodate;Advisory / Consultancy: Consulting (to institution): Ipsen, Arcus, Pfizer, Seattle Genetics, Bayer, Genentech, Incyte, Eisai and Merck., Consulting (to self): Stemline, AbbVie, Boehringer Ingelheim, Janssen, Daichii Sankyo, Natera, TreosBio, Celularity, Exact Science, Sobi, Beigene, Kanaph, Astra Zeneca, Deciphera, MJH Life Sciences, Aptitude Health, Illumina and Foundation Medicine, IDMC/DSMB: Fibrogen, Suzhou Kintor, Astra Zeneca, Exelixis, Merck/Eisai, PanCan and 1Globe;Research grant / Funding (institution): Agios, Arys, Arcus, Atreca, Boston Biomedical, Bayer, Eisai, Celgene, Lilly, Ipsen, Clovis, Seattle Genetics, Genentech, Novartis, Mirati, Merus, Abgenomics, Incyte, Pfizer, BMS.;Licensing / Royalties: WO/2018/183488: HUMAN PD1 PEPTIDE VACCINES AND USES THEREOF – Licensed to Imugene, WO/2019/055687: METHODS AND COMPOSITIONS FOR THE TREATMENT OF CANCER CACHEXIA – Licensed to Recursion. All other authors have declared no conflicts of interest.

Analysis of the Application of Big Data in Banking Sector

Since the State Council of China issued the 'Outline of Action to Promote the Development of Big Data' in 2015, which proposed a top-level design for big data development from a long-term perspective, the related industry had ushered in a rapid way. At present, under the background of accelerating digital transformation and post COVID-19, the social and economic benefits of data assets, especially the value of financial data turn out to be more prominent. In this paper, we analyze four exploration aspects of commercial banks around big data application: constructing enterprise-level big data platforms, strengthening the capability of risk control, innovating financial products and services, optimizing business processes. Meanwhile, giving the typical cases for all of these practices, we illustrate how the bank's decision-making transformed from 'experience-dependent' to 'data-based' that enable banks to improve business performance, assess credit risks and allocate resources scientifically. Generally, we hold the view that big data technology has become an important means for commercial banks to meet the emerging financial demands, respond to the competition of the fintechs and the high-level opening-up trend. At last, this paper suggests banks enhance the core competitiveness through big data deep application with facing challenges such as insufficient implementation of big data strategy, lack of data governance system, imperfect organizational structure as well as scarcity of data mining talents. © 2021 IEEE.

Security and Privacy in E-learning

E-learning has the advantages of flexible and diverse learning methods, and the high-quality teaching resources can be shared without limitation by time and space, it has been developed rapidly. Especially after the outbreak of the COVID-19, World began to widely replace traditional classroom teaching with E-learning methods, it leading to an explosive growth. During the use of E-learning, many security problems and privacy leakages have occurred. In This paper, we have analyzed the four main security threats faced by E-learning, summarized the current main research results and gave corresponding countermeasures and suggestions, which have certain positive significance for improving the security and privacy in E-learning. © 2021, Springer Nature Switzerland AG.

Research on Accurate Gesture Recognition Algorithm in Complex Environment Based on Machine Vision

To address the issue of cross infection caused by elevator public buttons during COVID-19, a software algorithm based on machine vision for non-contact control of public buttons by gesture recognition is designed. In order to improve the accuracy of gesture recognition, an improved YOLOv4 algorithm is proposed. A Ghost module is designed based on attention mechanism, and the ResBlock module in YOLOv4 is improved to Ghost module. The experimental results show that, in the task of gesture recognition, the detection speed is improved by 14% and the detection accuracy is improved by 0.1% compared with the original model. The improved YOLOv4 algorithm is applied to the non-contact elevator buttons control system based on vision. The experimental results show that the detection accuracy reaches 98%, which meets the requirements of non-contact control for public elevators. © 2021, The Editorial Board of Journal of System Simulation. All right reserved.

ComputeCOVID19+: Accelerating COVID-19 Diagnosis and Monitoring via High-Performance Deep Learning on CT Images

The COVID-19 pandemic has highlighted the importance of diagnosis and monitoring as early and accurately as possible. However, the reverse-transcription polymerase chain reaction (RT-PCR) test results in two issues: (1) protracted turnaround time from sample collection to testing result and (2) compromised test accuracy, as low as 67%, due to when and how the samples are collected, packaged, and delivered to the lab to conduct the RT-PCR test. Thus, we present ComputeCOVID19+, our computed tomography-based framework to improve the testing speed and accuracy of COVID-19 (plus its variants) via a deep learning-based network for CT image enhancement called DDnet, short for DenseNet and Deconvolution network. To demonstrate its speed and accuracy, we evaluate ComputeCOVID19+ across several sources of computed tomography (CT) images and on many heterogeneous platforms, including multi-core CPU, many-core GPU, and even FPGA. Our results show that ComputeCOVID19+ can significantly shorten the turnaround time from days to minutes and improve the testing accuracy to 91%. © 2021 ACM.

Necesscity of Expanding TCM Education in the Post-COVID Era

Traditional Chinese Medicine (TCM), proved remarkable effects in the diagnosis and treatment protocol for Coronavirus Disease 2019 (COVID-19), wins extensive attention in the world. This paper aims to firstly, introduce the overseas mainstream reports on TCM during the COVID-19 period, make clear the basic attitudes of oversea media towards TCM in the presently complicated international circumstances and emphasize the significance of cultural confidence, and secondly, illuminate the positive effects of overseas TCM communication on national image building and soft power enhancement, and offer suggestions to promote TCM education golbally: (1)telling better TCM stories;(2)improving the external communication system of TCM;(3)building academic discourse systems;(4)broadening communication channels by media convergence. © 2021 ACM.

Innovative design of box elevator epidemic prevention function integrating AD and TRIZ

The large number of indirect contact between people in the narrow space of the box elevator has brought hidden dangers to the spread of COVID-19 (Corona Virus Disease 2019). How to inhibit the survival and spread of the virus in the elevator has become an urgent problem to be solved. Therefore, by analyzing the advantages and disadvantages of axiomatic design (AD) and Tteoriya Resheniya Izoblateskikh Zadatch (TRIZ), an innovative design method integrating AD and TRIZ was proposed for different design types, such as breakthrough design, adaptive design and variable parameter design. Firstly, the function requirements of the product were analyzed to determine its design type, and the function requirements was decomposed by the AD theory, and the function-structure tree was constructed by the TRIZ. Then, the coupling judgment of the initial design scheme was carried out, and the TRIZ was used to decouple. After several iterations, the final design scheme was obtained. Taking the public interactive control panel and the enclosed car of the traditional box elevator as the research object, facing the function requirements of preventing virus transmission and eliminating virus, the innovative design method integrating AD and TRIZ was adopted to design the epidemic prevention function module of the box elevator, and the non-public contact interactive control module and the conditional disinfection and sterilization module for the traditional box elevator were designed. The innovative design example made a beneficial attempt to expand from the traditional mechanical structure design to the new human-computer interaction mode design, which verified the feasibility of the innovative design method integrating AD and TRIZ. The research results can provide effective theoretical support for the conceptual innovative design of new functional modules of products. © 2021. All Rights Reserved.

Metabolic profiling of bile acids in urine of patients with acute alcohol associated hepatitis

Background: Bile acids (BAs) play an important role in the development of alcohol associated liver disease (ALD) In the current study, the urine BA concentrations in patients with acute alcohol associated hepatitis (AAH) were analyzed by solid-phase extract (SPE) liquid chromatographymass spectrometry (LC-MS), and the urine BA levels were compared between healthy controls and AAH patients with different severity were compared Methods: Baseline urine samples were collected from 28 well-characterized AAH patients (Model for End-Stage Liver Disease [MELD] score: non-severe [MELD<20] and severe [MELD>20]), 3 alcohol use disorder (AUD) patients, and 9 healthy controls (HC) SPE-LCMS analysis identified a total of 29 BAs from urine samples. Urine was used because it is non-invasive and represents an easily accessible biological fluid in this time of COVID-19 restrictions Results: Seventeen BAs of 29 BAs analyzed had significant changes in their abundance levels within the AAH patient cohort Associations of demographic, drinking, and clinical data were analyzed with candidate BAs MELD scores showed positive correlations with certain conjugated BAs and negative correlations with the few unconjugated BAs;taurineconjugated CDCA and MELD showed highest association 6,7-diketolithocholic acid and apocholic acid had nonsignificant abundance changes in the non-severe AAH patients compared to HC but were significantly increased in severe AAH AUROC analysis showed that the differences of these two compounds was sufficiently large to distinguish severe AAH from non-severe AAH (Fig 1) Notably, the abundance levels of glycine-conjugated DCA and glycohyocholic acid were significantly increased, while those of deoxycholic acid and 23-nordeoxycholic acid were markedly decreased, in AAH patients compared to AUD subjects Importantly, we observed that the abundance levels of most conjugated BAs increased by disease stage in a stepwise manner, and some unconjugated BAs decreased in AAH patients who did not survive Conclusion: The abundance changes of specific BAs are closely correlated with the severity of AAH Urine primary BAs were increased in AAH and secondary BAs were decreased in diseases, demonstrating that BAs (individually or as a group) could be potential laboratory biomarkers for detecting early stage of AAH, and may have prognostic values in AAH morbidity.

[Analysis of special ehealth service for corona virus disease 2019 (COVID-19) pneumonia]

OBJECTIVE: To analyze how governments, hospitals and information technology(IT) companies use Internet technology to provide online health services during the early stage of corona virus disease 2019 (COVID-19) epidemic in January 2020 in China, and then provide suggestions and coping strategies for the later stage and post-epidemic time. METHODS: We searched for information on ehealth services related to the outbreak of COVID-19 in China. The sources of information were mainstream search engines such as Baidu and the popular interactive social platforms such as Webchat. The keywords were "Internet+pneumonia", "Internet clinic", "pneumonia online clinic" and so on. The time of information was from January 20 to February 3, 2020. The key information was extracted and encoded by two persons back-to-back. The coding information included: name of organization provider, launching time, location of provider, service items, user, health workers engaging in the service, and so on. The coded information was entered and analyzed with SPSS 24.0 and Excel. RESULTS: There were totally 57 projects launched by local governments, hospitals and IT companies. Most of them were launched from January 24th to 27th, the hospital and government projects services regionally, especially in eastern provinces. In this study, 90.48% of the enterprises and 100.00% of the hospitals had online fever clinic and consultation services for COVID-19, 66.67% of the enterprises and 37.04% of the hospitals serviced derivative health problems. Only a few projects provided tele-medical consultation. There were individual projects that provided online health management for home quarantine people. Physicians were the main force of various projects. In some hospital projects, there were also nurses, pharmacists and professional technicians to provide featured consultation. CONCLUSION: Ehealth is useful and helpful for the health care system to rapidly cope with health demand during instantaneous and post epidemic time. Regional distribution of ehealth is unbalanced. There are institutional and technical feasibilities for the emergency application of Internet technology. However, community health centers seldom provide ehealth or connect with tertiary hospitals with Internet. Therefore, all kinds of providers within healthcare system should promote emergence ehealth. Tele-medical diagnosis and referral should be developed by local governments during COVID-19. The application of "Internet+medical treatment" in community medical institutions and synergy among various institutions should be promoted.