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1.
Physics of Fluids ; 34(11), 2022.
Article in English | Web of Science | ID: covidwho-2133926

ABSTRACT

The SARS-CoV-2 Omicron variant is more highly transmissible and causes a higher mortality rate compared to the other eleven variants despite the high vaccination rate. The Omicron variant also establishes a local infection at the extrathoracic airway level. For better health risk assessment of the infected patients, it is essential to understand the transport behavior and the toxicity of the Omicron variant droplet deposition in the extrathoracic airways, which is missing in the literature. Therefore, this study aims to develop a numerical model for the Omicron droplet transport to the extrathoracic airways and to analyze that transport behavior. The finite volume method and ANSYS Fluent 2020 R2 solver were used for the numerical simulation. The Lagrangian approach, the discrete phase model, and the species transport model were employed to simulate the Omicron droplet transport and deposition. Different breathing rates, the mouth and nose inhalation methods were employed to analyze the viral toxicity at the airway wall. The results from this study indicated that there was a 33% of pressure drop for a flow rate at 30 l/min, while there was only a 3.5% of pressure drop for a 7.5 l/min. The nose inhalation of SARS-CoV-2 Omicron droplets is significantly more harmful than through the mouth due to a high deposition rate at the extrathoracic airways and high toxicity in the nasal cavities. The findings of this study would potentially improve knowledge of the health risk assessment of Omicron-infected patients. Published under a nonexclusive license by AIP Publishing.

2.
Zhonghua Er Ke Za Zhi ; 60(11): 1163-1167, 2022 Nov 02.
Article in Chinese | MEDLINE | ID: covidwho-2099938

ABSTRACT

Objective: To summarize the management and short-term outcomes of neonates delivered by mothers infected with SARS-CoV-2 Omicron variant. Methods: A retrospective study was performed on 158 neonates born to mothers infected with SARS-CoV-2 Omicron variant admitted to the isolation ward of Children's Hospital of Fudan University from March 15th, 2022 to May 30th, 2022. The postnatal infection control measures for these neonates, and their clinical characteristics and short-term outcomes were analyzed. They were divided into maternal symptomatic group and maternal asymptomatic group according to whether their mothers had SARS-CoV-2 symptoms. The clinical outcomes were compared between the 2 groups using Rank sum test and Chi-square test. Results: All neonates were under strict infection control measures at birth and after birth. Of the 158 neonates, 75 (47.5%) were male. The gestational age was (38+3±1+3) weeks and the birth weight was (3 201±463)g. Of the neonates included, ten were preterm (6.3%) and the minimum gestational age was 30+1 weeks. Six neonates (3.8%) had respiratory difficulty and 4 of them were premature and required mechanical ventilation. All 158 neonates were tested negative for SARS-COV-2 nucleic acid by daily nasal swabs for the first 7 days. A total of 156 mothers (2 cases of twin pregnancy) infected with SARS-CoV-2 Omicron variant, the time from confirmed SARS-CoV-2 infection to delivery was 7 (3, 12) days. Among them, 88 cases (56.4%) showed clinical symptoms, but none needed intensive care treatment. The peripheral white blood cell count of the neonates in maternal symptomatic group was significantly higher than that in maternal symptomatic group (23.0 (18.7, 28.0) × 109 vs. 19.6 (15.4, 36.6) × 109/L, Z=2.44, P<0.05). Conclusions: Neonates of mothers infected with SARS-CoV-2 Omicron variant during third trimester have benign short-term outcomes, without intrauterine infection through vertical transmission. Strict infection control measures at birth and after birth can effectively protect these neonates from SARS-CoV-2 infection.


Subject(s)
COVID-19 , Pregnancy Complications, Infectious , Female , Humans , Infant , Infant, Newborn , Male , Pregnancy , Mothers , Pregnancy Complications, Infectious/diagnosis , Pregnancy Complications, Infectious/prevention & control , Retrospective Studies , SARS-CoV-2
4.
25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022 ; 13431 LNCS:506-516, 2022.
Article in English | Scopus | ID: covidwho-2059725

ABSTRACT

Detailed modeling of the airway tree from CT scan is important for 3D navigation involved in endobronchial intervention including for those patients infected with the novel coronavirus. Deep learning methods have the potential for automatic airway segmentation but require large annotated datasets for training, which is difficult for a small patient population and rare cases. Due to the unique attributes of noisy COVID-19 CTs (e.g., ground-glass opacity and consolidation), vanilla 3D Convolutional Neural Networks (CNNs) trained on clean CTs are difficult to be generalized to noisy CTs. In this work, a Collaborative Feature Disentanglement and Augmentation framework (CFDA) is proposed to harness the intrinsic topological knowledge of the airway tree from clean CTs incorporated with unique bias features extracted from the noisy CTs. Firstly, we utilize the clean CT scans and a small amount of labeled noisy CT scans to jointly acquire a bias-discriminative encoder. Feature-level augmentation is then designed to perform feature sharing and augmentation, which diversifies the training samples and increases the generalization ability. Detailed evaluation results on patient datasets demonstrated considerable improvements in the CFDA network. It has been shown that the proposed method achieves superior segmentation performance of airway in COVID-19 CTs against other state-of-the-art transfer learning methods. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

5.
Journal of Systems Science and Information ; 10(4):309-337, 2022.
Article in English | Scopus | ID: covidwho-2030520

ABSTRACT

The aim of this paper is first to establish a general prediction framework for turning (period) term structures in COVID-19 epidemic related to the implementation of emergency risk management in the practice, which allows us to conduct the reliable estimation for the peak period based on the new concept of “Turning Period” (instead of the traditional one with the focus on “Turning Point”) for infectious disease spreading such as the COVID-19 epidemic appeared early in year 2020. By a fact that emergency risk management is necessarily to implement emergency plans quickly, the identification of the Turning Period is a key element to emergency planning as it needs to provide a time line for effective actions and solutions to combat a pandemic by reducing as much unexpected risk as soon as possible. As applications, the paper also discusses how this “Turning Term (Period) Structure” is used to predict the peak phase for COVID-19 epidemic in Wuhan from January/2020 to early March/2020. Our study shows that the predication framework established in this paper is capable to provide the trajectory of COVID-19 cases dynamics for a few weeks starting from Feb.10/2020 to early March/2020, from which we successfully predicted that the turning period of COVID-19 epidemic in Wuhan would arrive within one week after Feb.14/2020, as verified by the true observation in the practice. The method established in this paper for the prediction of “Turning Term (Period) Structures” by applying COVID-19 epidemic in China happened early 2020 seems timely and accurate, providing adequate time for the government, hospitals, essential industry sectors and services to meet peak demands and to prepare aftermath planning, and associated criteria for the Turning Term Structure of COVID-19 epidemic is expected to be a useful and powerful tool to implement the so-called “dynamic zero-COVID-19 policy” ongoing basis in the practice. © 2022, Science Press (China). All rights reserved.

6.
The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLIII-B4-2022:195-202, 2022.
Article in English | ProQuest Central | ID: covidwho-1876035

ABSTRACT

The COVID-19 epidemic has posed a grave threat to human life. The stay-at-home quarantine is an effective method of minimizing physical contact and the risk of COVID-19 transmission. However, the supply of living materials (such as meat, vegetables, grain, and oil) has become a great challenge as residents' activities have been restricted. In this paper, we present a spatial analysis framework for the supply of living materials during COVID-19 outbreak by coupling an infectious disease model with geographic information system (GIS). First, a virus spreading spatial simulation model is developed by combining cellular automata (CA) and Susceptible-Exposed-Infected-Recovered-Death (SEIRD) to estimate COVID-19's spreading under various scenarios. Second, the demand and supply of living materials in the impacted residents are calculated. Finally, the imbalance of the supply and demand of the living materials is assessed. We conduct experiments in Shenzhen. The experimental results show that localities with supply-demand mismatches are primarily concentrated in the southwest of Bao'an District, the southern of Longhua District, and Longgang District. Additionally, the spatial distribution of the mismatch level between supply and demand for living materials in Shenzhen exhibits a significant agglomeration effect, manifested as "low-low" and "high-high" agglomeration. The spatial agglomeration effect of material mismatch has increased with the spread of the epidemic. These results support the prevention and control of the COVID-19 spreading.

7.
Yaoxue Xuebao ; 57(2):446-452, 2022.
Article in Chinese | EMBASE | ID: covidwho-1780346

ABSTRACT

As one of the "Three Drugs Three Prescriptions" anti-COVID-19 traditional Chinese medicine, Jinhua Qinggan granules (JHQG) has been proved to have clear clinical effects. With complex medicinal flavors and ingredients, there is no systematic research report on chemical composition in vivo or in vitro. An ultrahigh pressure liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-QTOF/MS) method was developed in this study to identify the components of the anti-COVID-19 traditional Chinese medicine JHQG granules. Analyze the collected rat plasma samples after administration and explore the exposed components in rats within 8 hours after intragastric administration. Preliminary pharmacokinetic analysis was then performed on this basis. Through UPLC-QTOF/MS analysis and verification by standard products, a total of 77 chemical components in JHQG formula have been identified, among which 22 compounds were highly exposed in vivo, mainly derived from three medicinal materials of honeysuckle, scutellaria and forsythia. Through the assessment of the blood drug concentration by the compartment model, 6 PK parameters of 4 high-exposure chemical components have been obtained, clarifying the metabolic characteristics of the main exposed components in JHQG briefly. The method is simple, efficient, sensitive and accurate and provides research basis to the clarification of the pharmacodynamics material basis and mechanism of JHQG, which has certain reference significance for the basics and applications research of the traditional Chinese medicine prescriptions in fighting the SARS-CoV-2.

9.
Open Forum Infectious Diseases ; 8(SUPPL 1):S71-S72, 2021.
Article in English | EMBASE | ID: covidwho-1746785

ABSTRACT

Background. Despite antifungal therapy and surgical debridement, overall mortality of invasive mucormycosis is >40%. Currently the world is witnessing an explosion in mucormycosis in India among COVID-19 patients with an official count of 28,252 cases as of 06/07/2021. Thus, novel therapeutic modalities are needed. We previously reported on a mouse monoclonal antibody (C2) targeting CotH invasins being protective against mucormycosis. Here, we humanized C2 MAb and assessed its efficacy in vitro and in vivo. Methods. The C2 (IgG1) paratopes of the heavy chain and light chain were grafted on the most suitable human IgG1 with back mutations in the paratopes needed to restore binding of humanized clones to CotH3 (by biolayer interferometry using Gator). Clones were compared to C2 in their ability to prevent Rhizopus delemar-induced injury to A549 alveolar epithelial and primary human endothelial cells and for enhancing human neutrophil killing of the fungus in vitro. C2 and the humanized clones were also compared for their ability to protect neutropenic mice from mucormycosis induced by R. delemar or Mucor cicrinelloides with and without antifungal therapy. Results. Three humanized clones showed 10-fold enhanced binding affinity to CotH3 protein (~5 nM for humanized vs. ~50 nM for C2). One humanized clone (VX01) doubled the ability of neutrophils to kill R. delemar and resulted in ~50% reduction in host cell damage. A single low dose of VX01 (30 μg) given 24 h post infection resulted in comparable survival of 60-70% in mice infected intratracheally with either R. delemar or M. cicrinelloides vs. placebo mice (0% survival, P < 0.02). Importantly, VX01 acted synergistically in protecting mice when combined with liposomal amphotericin B or posaconazole in a severe model of mucormycosis with treatment starting 48 h post infection (~70% survival for combination vs. 0-20% survival for monotherapy and reduced lung fungal burden by 1.5 log, P< 0.001). GLP-tissue cross reactivity studies of VX01 showed favorable safety profiles. Conclusion. VX01 shows enhanced binding to CotH3 protein and maintained the protective features of C2 MAb against murine mucormycosis. Clinical testing of combination therapy of VX01 + antifungals is warranted. VX01 is currently in manufacturing.

10.
IEEE/CVF International Conference on Computer Vision (ICCVW) ; : 508-512, 2021.
Article in English | Web of Science | ID: covidwho-1704314

ABSTRACT

In this paper, we present a hybrid deep learning framework named CTNet which combines convolutional neural network (CNN) and transformer together for the detection of COVID-19 via 3D chest CT images. It consists of a CNN feature extractor module with SE attention to extract sufficient features from CT scans, together with a transformer model to model the discriminative features of the 3D CT scans. Compared to previous works, CTNet provides an effective and efficient method to perform COVID-19 diagnosis via 3D CT scans with data resampling strategy. Advanced results on a large and public benchmarks, COV19-CT-DB database, was achieved by the proposed CTNet with a macro F1 score of 88.21% on the validation set, which lead ten percentage over the state-of-the-art baseline approach proposed together with the dataset. Notably, the inference speed of the proposed framework is about ten times faster than that of the typical CNN frameworks which make it more promising in actual applications.

11.
Chinese General Practice ; 24(34):4312-4318, 2021.
Article in Chinese | Scopus | ID: covidwho-1600039

ABSTRACT

Background: During the prevention and control of the COVID-19, the setting of fever clinic in primary healthcare institutions is an important experience summary and pilot practice. At present, the pilot sentinel surveillance has been carried out for more than one year, and it is necessary to analyze its operation situation. Objective: To investigate the setting and utilization of fever clinic in primary healthcare institutions, summarize experience and put forward corresponding suggestions. Methods: From 2021-02-22 to 2021-03-02, a multi-stage sampling method was adopted to select primary healthcare institutions(community healthcare centers/township health centers) who participated in the prevention and control of the COVID-19 epidemic to conduct a questionnaire survey(including fever sentinel surveillance clinics set up during epidemic prevention and fever clinics set up before epidemic prevention), cumulative use time, cumulative number of visits, cumulative referral rate, and cumulative number of diagnoses. Results: 718 valid responses from 408 primary healthcare institutions were totally obtained. Among them, 208 institutions(51.0%) set up fever sentinel surveillance clinic during the prevention and control of the COVID-19 epidemic, 91 institutions(22.3%) had set up before the prevention and control of the COVID-19 epidemic, and 109 institutions(26.7%) had not set up. 271 subjects participated in the work of the fever sentinel surveillance clinic. According to the 271 questionnaires: as the end of January 2021, the median cumulative use time of the fever sentinel surveillance clinic is 12(10) months;188 cases(69.4%) of the respondents indicated that the cumulative number of visits was <300, and 45 cases(16.6%) indicated that the cumulative number of visits was >1 000;184(67.9%) respondents indicated that the cumulative referral rate was <3%, and 35(12.9%) respondents indicated that the cumulative referral rate was >70%;238(87.8%) of the respondents indicated that the number of patients who were finally diagnosed with novel coronavirus pneumonia was 0 out of all the patients admitted. The test results of χ2 showed that the cumulative number of visits between the setting of the fever clinic during the prevention and control of the novel coronavirus pneumonia epidemic and the setting of the fever clinic before the epidemic prevention and control is statistically significant(P<0.05);However, there is no statistically significant difference in the cumulative number of visits, the cumulative referral rate, and the cumulative number of diagnoses in fever clinic in different regions(including economic zone, geographical location within the city, and the highest risk level during the epidemic period of the region). The results of Spearman rank correlation analysis showed that the setting time of fever clinics was significantly positively correlated with cumulative use time and cumulative visits(rs values were 0.37, 0.18, P<0.05), and the region(east, central, and western) was significantly positively correlated with cumulative diagnoses(rs=0.13, P<0.05). Conclusion: According to the survey, more than two thirds of primary healthcare institutions in China have set up fever sentinel surveillance clinics/fever clinics, and of which no difference were indicated in the cumulative visit number of febrile patients, cumulative referral rate and cumulative number of confirmed COVID-19 infections based on the different economic zones, geographical locations and regions with different highest risk level. The higher cumulative number of visits to fever clinics than fever sentinel surveillance clinics demonstrated the potential capacity of managing patients with fever during the pandemic of infectious diseases. Copyright © 2021 by the Chinese General Practice.

12.
Ieee Transactions on Computational Social Systems ; : 12, 2021.
Article in English | Web of Science | ID: covidwho-1583773

ABSTRACT

Much work has already been studied on the interrelation between the epidemic spreading and awareness spreading to prevent infections in a social network. By selecting seed users to spread awareness, we can control epidemic spreading. However, selecting seed users with the maximum influential users may not be the best solution in location-based social networks. Therefore, it is challenging to determine users to spread the information (the awareness of prevention) in these networks. The minimized epidemic infection (MEI) problem aims to find a seed set with k seed users such that the infection users can be minimized. In this article, we propose a piecewise function to measure the probability of each user being infected, which considers the distance and time. Then, we propose an algorithm called location-infected-greedy (LIG) to solve the MEI problem by finding the seed nodes that consider the probability of infection, time of check-in, location information, and influence of users. In the meantime, LIG can obtain an upper bound of the data-dependent approximate ratio, and it runs in O(kn(2)), where n is the total number of nodes and k is the number of seed nodes. Finally, extensive contrast experiments on real-world location-based social networks show that our algorithm is efficient and effective.

13.
Joint Conference of 59th Annual Meeting of the Association-for-Computational-Linguistics (ACL) / 11th International Joint Conference on Natural Language Processing (IJCNLP) / 6th Workshop on Representation Learning for NLP (RepL4NLP) ; : 1764-1774, 2021.
Article in English | Web of Science | ID: covidwho-1481682

ABSTRACT

Knowledge bases (KBs) and text often contain complementary knowledge: KBs store structured knowledge that can support longrange reasoning, while text stores more comprehensive and timely knowledge in an unstructured way. Separately embedding the individual knowledge sources into vector spaces has demonstrated tremendous successes in encoding the respective knowledge, but how to jointly embed and reason with both knowledge sources to fully leverage the complementary information is still largely an open problem. We conduct a large-scale, systematic investigation of aligning KB and text embeddings for joint reasoning. We set up a novel evaluation framework with two evaluation tasks, few-shot link prediction and analogical reasoning, and evaluate an array of KB-text embedding alignment methods. We also demonstrate how such alignment can infuse textual information into KB embeddings for more accurate link prediction on emerging entities and events, using COVID-19 as a case study.(1)

14.
3rd MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the 1st MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 ; 12968 LNCS:25-34, 2021.
Article in English | Scopus | ID: covidwho-1469664

ABSTRACT

3D Convolutional Neural Networks (CNNs) have been widely adopted for airway segmentation. The performance of 3D CNNs is greatly influenced by the dataset while the public airway datasets are mainly clean CT scans with coarse annotation, thus difficult to be generalized to noisy CT scans (e.g. COVID-19 CT scans). In this work, we proposed a new dual-stream network to address the variability between the clean domain and noisy domain, which utilizes the clean CT scans and a small amount of labeled noisy CT scans for airway segmentation. We designed two different encoders to extract the transferable clean features and the unique noisy features separately, followed by two independent decoders. Further on, the transferable features are refined by the channel-wise feature recalibration and Signed Distance Map (SDM) regression. The feature recalibration module emphasizes critical features and the SDM pays more attention to the bronchi, which is beneficial to extracting the transferable topological features robust to the coarse labels. Extensive experimental results demonstrated the obvious improvement brought by our proposed method. Compared to other state-of-the-art transfer learning methods, our method accurately segmented more bronchi in the noisy CT scans. © 2021, Springer Nature Switzerland AG.

15.
3rd EAI International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021 ; 388:331-337, 2021.
Article in English | Scopus | ID: covidwho-1446002

ABSTRACT

To investigate the relationship between emotional status and physical activity in adolescents during the epidemic period of Corona Virus Disease 2019. 600 junior and senior high school students from three municipal middle schools were randomly selected as the research objects. The self-evaluation of anxiety and depression and the evaluation of physical activity were carried out in the form of questionnaire survey. A total of 600 questionnaires were put in and 562 were recovered. The scores of SDS and SAS were 49.30 ± 7.02, and 53.42 ± 5.37 respectively. According to different age groups, there was significant difference in SAS among the three groups in different age groups (P <0.05). The total score of PA was (3.24 ± 0.98). According to different age groups, there were significant differences in PA total score, MVPA activities, physical education activities, weekend activities and one week total activities among the three groups (P <0.05). The total score of anxiety was negatively correlated with the total score of PA (r = −0.54, P = 0.024), MVPA (r = −0.38, P = 0.049) and physical education (r = −0.62, P = 0.016), and the total score of one week was negatively correlated (r = −0.44, P = 0.041). During the period of Corona Virus Disease 2019 epidemic, the anxiety level of adolescents increases with age, while the physical activity status decreases gradually, and is negatively correlated with anxiety. It is necessary to strengthen sports activities and protect emotional health in this special period. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

16.
Public Health ; 198: 1-5, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1331158

ABSTRACT

OBJECTIVES: As a unique prevention and control measure, the dispatch of national medical teams to Wuhan has played a key role in protecting Wuhan against COVID-19. This study aimed to quantitatively evaluate the effect of this key measure in reducing infections and fatalities. STUDY DESIGN: A scenario analysis is used in this study, where the forming of scenarios is on the basis of the stages of medical to Wuhan. We divided the evaluation into 4 scenarios: Scenario Ⅰ-no dispatch, Scenario Ⅱ-dispatch of 4599 medical staff, Scenario Ⅲ-dispatch of 16,000 staff, and Scenario Ⅳ-dispatch of 32,000 staff. METHODS: The extended Susceptible-Exposed-Infectious-Recovered-Death model was adopted to quantify the effect of the dispatch of national medical teams to Wuhan on COVID-19 prevention and control. RESULTS: The dispatch dramatically cuts the channels for the transmission of the virus and succeeds in raising the cure rates while reducing the fatality rates. If there were no dispatch at all, a cumulative total of 158,881 confirmed cases, 18,700 fatalities and a fatality rate of 11.77% would have occurred in Wuhan, which are 3.2 times, 4.8 times and 1.5 times the real figures respectively. The dispatch has avoided 108,541 confirmed cases and 14,831 fatalities in this city. CONCLUSIONS: The proven successful measure provides valuable experience and enlightenment to international cooperation on prevention and control of COVID-19, as well as a similar outbreak of new emerging infectious diseases.


Subject(s)
COVID-19 , China/epidemiology , Disease Outbreaks , Humans , SARS-CoV-2
18.
Materials Today Advances ; 11, 2021.
Article in English | Scopus | ID: covidwho-1294072

ABSTRACT

In addition to the pandemic caused by the coronavirus disease 2019, many pathogenic bacteria have also been posing a devastating threat to human health. The overuse of antibiotics leads to the emergence of ‘superbugs’;therefore, it is urgent to develop effective strategies to fight bacteria. Herein, a superparamagnetic nickel (Ni) colloidal nanocrystal clusters (SNCNCs) that can kill and capture bacteria without any camouflage is reported. It binds to amino groups on the surface of bacteria, imparts magnetism to them, and orients them in response to magnetic fields. SNCNCs kill and capture bacteria to avoid inflammation, infection, and organ damage caused by lipopolysaccharide and exotoxin released by bacterial rupture in the remaining bacterial remains in comparison with other antibacterial agents. In this study, in the treatment of traumatic oral ulcers, we found that SNCNCs could kill and capture and remove bacteria from the ulcers to reduce inflammation at the site of the wound. Furthermore, the fibrin gel sprayed on the ulcer was used as a substrate, and the bacteria captured by the SNCNCs moved to the surface of the fibrin gel after a magnetic field was applied. Therefore, the bacteria in the ulcer could be removed with the SNCNCs and fibrin gel magnet, alleviating inflammation caused by bacteria and promoting ulcer healing. This magnetically controlled method of directional movement of bacteria may provide an applicative perspective for the therapy of bacterial infections. © 2021 The Author(s)

19.
Chinese Journal of Pharmaceutical Biotechnology ; 28(1):88-93, 2021.
Article in Chinese | EMBASE | ID: covidwho-1285617

ABSTRACT

In December 2019, a new type of coronavirus pneumonia (COVID-19) broke out in China and then spread globally, causing serious harm to the lives and health of people around the world.2019-nCoV is an RNA virus that is mainly transmitted through droplets and contact.It is highly infectious, so accurate and timely diagnosis and differential diagnosis are essential for control of infection and treatment of COVID-19.Currently, clinical diagnosis projects of COVID-19 mainly include nucleic acid detection of novel coronavirus, human immunological detection and pulmonary imaging tests.Based on these clinical diagnosis projects, a series of detection methods and techniques have been developed for COVID-19 screening, diagnosis, differential diagnosis, and virus mutation monitoring.This review comprehensively made a summary on the principles, advantages, disadvantages, and clinical applicable scenarios of these diagnosis methods and techniques for COVID-19 and proposes to combine laboratory indicators with clinical symptoms and signs and image tests based on different needs to jointly guarantee accurate and effective diagnosis.

20.
Chinese Journal of General Practitioners ; 20(4):441-445, 2021.
Article in Chinese | Scopus | ID: covidwho-1215497

ABSTRACT

Objective: To understand the coronavirus disease 2019(COVID-19)prevention and control work and the problems and difficulties faced by non-government primary medical institutions in China during the epidemic period. Methods: A survey on the coronavirus disease 2019(COVID-19)prevention and control work of non-government primary medical institutions was conducted on April 14 to 21, 2020 with the self-designed questionnaire. The questionnaire contained three parts: the first part was basic information of medical staff in non-government primary medical institutions, including position and institutional information;the second part was the status quo of non-government primary medical institutions participating in the prevention and control of COVID-19, including the specific work and difficulties faced by the responders during the epidemic period;and the third part was the prevention and control effect of COVID-19 in the responders' institutions, including whether there were confirmed cases and infected medical staff. An online invitation was issued among the members of General Practice Branch of Chinese Non-government Medical Institution Association. The invited participants included the heads, general practitioners and other medical personnel of the non-government primary medical institutions the invited participants voluntarily scanned the online two-dimensional code to fill in. Results: A total of 761 individuals in primary health institutions from 20 provinces, municipalities and autonomous regions in China participated in the survey. There were 290 (38.1%) men and 471 (61.9%) women with age of 40(32, 48) years;83.0% (632/761) had worked for more than 5 years;33.8% (257/761) owned primary professional titles and 33.0% (251/761) owned intermediate titles. Among all participants 28.5% (217/761) were general practitioners, 26.9% (205/761) were institutions/department managers, 14.6% (111/761) were specialists and 40.3% (307/761) were other related personnel. A total of 549 institutions continued to operate during the epidemic period and 96.5% (530/549) participated in the work related to the prevention and control of the epidemic, including prescreening and triage, health consultation, follow-up of suspected patients, donation, quarantine of suspected cases, follow-up of close contacts/discharged patients, diagnosis and treatment of patients with new coronavirus pneumonia. 44.7% (340/761) of respondents participated in the epidemic prevention as front-line staff and directly contacted patients/suspected patients, and 63.1% (480/761) participated in the epidemic prevention work of primary medical institutions, including clinical outpatient service, prescreening triage and screening. The working sites were not limited to the institutions, but also other sites including high-speed railway station. The 97.8% (744/761) responders expressed their willingness to participate in epidemic prevention work under the unified leadership and command of the state. The 63.9% (486/761) of the responders were worried about the lack of protective equipments and measures, and 90.4% (688/761) respondents showed that they needed medical supplies (protective equipment: masks, goggles, protective gowns, etc.). Conclusion: The participation of non-government primary medical institutions and their staff in COVID-19 infection prevention and control is a key component of the epidemic prevention process. © 2021 Chinese Medical Association

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