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1.
Brief Bioinform ; 2021 Feb 16.
Article in English | MEDLINE | ID: covidwho-1082896

ABSTRACT

Human coronaviruses (CoVs) can cause respiratory infection epidemics that sometimes expand into globally relevant pandemics. All human CoVs have sister strains isolated from animal hosts and seem to have an animal origin, yet the process of host jumping is largely unknown. RNA interference (RNAi) is an ancient mechanism in many eukaryotes to defend against viral infections through the hybridization of host endogenous small RNAs (miRNAs) with target sites in invading RNAs. Here, we developed a method to identify potential RNAi-sensitive sites in the viral genome and discovered that human-adapted coronavirus strains had deleted some of their sites targeted by miRNAs in human lungs when compared to their close zoonic relatives. We further confirmed using a phylogenetic analysis that the loss of RNAi-sensitive target sites could be a major driver of the host-jumping process, and adaptive mutations that lead to the loss-of-target might be as simple as point mutation. Up-to-date genomic data of severe acute respiratory syndrome coronavirus 2 and Middle-East respiratory syndromes-CoV strains demonstrate that the stress from host miRNA milieus sustained even after their epidemics in humans. Thus, this study illustrates a new mechanism about coronavirus to explain its host-jumping process and provides a novel avenue for pathogenesis research, epidemiological modeling, and development of drugs and vaccines against coronavirus, taking into consideration these findings.

2.
ACS Appl Mater Interfaces ; 13(7): 7966-7976, 2021 Feb 24.
Article in English | MEDLINE | ID: covidwho-1075146

ABSTRACT

Nowadays, there is an increasing demand for more accessible routine diagnostics for patients with respect to high accuracy, ease of use, and low cost. However, the quantitative and high accuracy bioassays in large hospitals and laboratories usually require trained technicians and equipment that is both bulky and expensive. In addition, the multistep bioassays and long turnaround time could severely affect the disease surveillance and control especially in pandemics such as influenza and COVID-19. In view of this, a portable, quantitative bioassay device will be valuable in regions with scarce medical resources and help relieve burden on local healthcare systems. Herein, we introduce the MagiCoil diagnostic device, an inexpensive, portable, quantitative, and rapid bioassay platform based on the magnetic particle spectrometer (MPS) technique. MPS detects the dynamic magnetic responses of magnetic nanoparticles (MNPs) and uses the harmonics from oscillating MNPs as metrics for sensitive and quantitative bioassays. This device does not require trained technicians to operate and employs a fully automatic, one-step, and wash-free assay with a user friendly smartphone interface. Using a streptavidin-biotin binding system as a model, we show that the detection limit of the current portable device for streptavidin is 64 nM (equal to 5.12 pmole). In addition, this MPS technique is very versatile and allows for the detection of different diseases just by changing the surface modifications on MNPs. Although MPS-based bioassays show high sensitivities as reported in many literatures, at the current stage, this portable device faces insufficient sensitivity and needs further improvements. It is foreseen that this kind of portable device can transform the multistep, laboratory-based bioassays to one-step field testing in nonclinical settings such as schools, homes, offices, etc.

3.
Rev Neurosci ; 2021 Feb 01.
Article in English | MEDLINE | ID: covidwho-1069661

ABSTRACT

The coronavirus disease 2019 is still continuing and may affect stroke emergency care. We aim to investigate the impact of pandemic on stroke treatment in tertiary stroke centers in western China, and to quantitatively evaluate the worldwide influence with a meta-analysis. The original part was conducted in three tertiary stroke centers in Sichuan province. We compared emergency visits and efficiency of stroke treatment pre-, early, peak and late pandemic. Single-center analysis was further conducted in the largest local hospital and one hospital located close to the epicenter respectively. Relevant studies were searched in PubMed, Ovid Embase and Cochrane Library for English publications from December 2019 to July 2020 for systematic review. Fixed-and random-effect meta-analysis was performed to calculate the overall rates. Totally current original study showed fewer time of hospital admission and significantly higher rates of mechanical thrombectomy during the early and peak epidemic periods, compared with pre-epidemic time. The largest local hospital had significantly higher mechanical thrombectomy rates during the whole crisis and less daily admission during early and peak epidemic periods. The hospital located close to the epicenter presented higher proportions of intravenous thrombolysis since outbreak, and more favorable outcomes after reperfusion therapies than later (all P values <0.05). In meta-analysis, studies reported differences in reperfusion therapies and stroke severity but pooled results were non-significant. Overall, comprehensive measures should be implemented to keep hospital's capacity to deliver high-quality stroke emergency care during the global pandemic. Some key messages were provided for medical practice in the crisis.

4.
PLoS One ; 16(2): e0246328, 2021.
Article in English | MEDLINE | ID: covidwho-1067424

ABSTRACT

To investigate if the anxiety associated with coronavirus disease 2019 (COVID-19) is a promoting factor to tinnitus. A retrospective research design collected from 188 tinnitus patients, was used to compare the clinical characteristics of tinnitus between the patients in 2020 under pandemic pressure and those from the matching period in 2019. While anxiety was quantified using the Zung's Self-rating Anxiety Scale (SAS), tinnitus severity was evaluated using the Tinnitus Handicap Inventory (THI) questionnaire and the test of tinnitus loudness (TL). The assessments were repeated after the sound therapy plus educational counselling (STEC) for 38 patients in 2020 and 58 patients in 2019 and compared with EC alone therapy for 42 patients in 2020 and 17 patients in 2019. A large increase in anxiety was evident in 2020 in both case rate and SAS. The treatment of both methods was less effective in 2020. SAS, THI and TL were all deteriorated after the EC alone treatment in 2020, while an improvement was seen in 2019. This suggests that EC alone could not counteract the stress by COVID-19 at all, and the stress, if not managed well, can significantly increase the severity of tinnitus and associated anxiety. By using the EC subgroup in virtual control, we conclude that anxiety can serve as a promoting factor to tinnitus. We believe that this is the first study report that confirm the causative/promotive role of anxiety on tinnitus during COVID-19 pandemic.


Subject(s)
Anxiety/complications , Tinnitus/complications , Aged , Female , Humans , Male , Middle Aged , Retrospective Studies , Severity of Illness Index , Sound , Surveys and Questionnaires , Tinnitus/diagnosis , Tinnitus/therapy
5.
IEEE J Biomed Health Inform ; PP2021 Jan 15.
Article in English | MEDLINE | ID: covidwho-1054463

ABSTRACT

Medical image processing is one of the most important topics in the field of the Internet of Medical Things (IoMT). Recently, deep learning methods have carried out state-of-the-art performances on medical imaging tasks. However, conventional deep learning has two major drawbacks: 1) insufficient training data and 2) the domain mismatch between the training data and the testing data. In this paper, we propose a novel transfer learning framework for medical image classification. Moreover, we apply our method to a recent issue (Coronavirus Diagnose). Several studies indicate that lung Computed Tomography (CT) images can be used for a fast and accurate COVID-19 diagnosis. However, well-labeled training data sets cannot be easily accessed due to the novelty of the disease and the privacy policies. The proposed method has two components: Reduced-size Unet Segmentation model and Distant Feature Fusion (DFF) classification model. This study is related to a not well-investigated but important transfer learning problem, termed Distant Domain Transfer Learning (DDTL). In this study, we develop a DDTL model for COVID-19 diagnose using unlabeled Office-31, Caltech-256, and chest X-ray image data sets as the source data, and a small set of labeled COVID-19 lung CT as the target data. The main contributions of this study are: 1) the proposed method benefits from unlabeled data in distant domains which can be easily accessed, 2) it can effectively handle the distribution shift between the training data and the testing data, 3) it has achieved 96% classification accuracy, which is 13% higher classification accuracy than "non-transfer" algorithms, and 8% higher than existing transfer and distant transfer algorithms.

8.
Genomics ; 113(2): 463-473, 2021 Jan 20.
Article in English | MEDLINE | ID: covidwho-1039591

ABSTRACT

In Yangtze River Delta white goat, hypermethylation of CMTM3 leads to a decreased expression level in high quality brush hair. However, the regulation of CMTM3 expression and its function in hair follicle stem cells (HFSCs) remains largely unknown. In this study, we investigated the regulation of CMTM3 expression, function, and molecular mechanism in HFSCs. The re-expression of CMTM3 significantly suppressed the proliferation of HFSCs by inducing G1 cell cycle arrest and promoting apoptosis. Moreover, the downregulation of CMTM3 promoted HFSC proliferation. Treatment with sh_CMTM3 and incubation in a DHT culture medium had the most significant growth-promoting effect. It was hypothesized that transcriptome analysis using RNA sequencing (RNA-seq) in samples would enable the identification of unique protein-coding and non-coding genes that may help uncover the role of CMTM3. Multiple genes and pathways were involved in this process, including 168 common DEGs, such as CXCL8 and E-selectin, which is reportedly involved in multiple regulatory pathways. These results indicated that CMTM3 can function as HFSCs through the induction of a G1 cell cycle arrest and promoted apoptosis by mediating crosstalk between several pathways and transcription factors. Our data is available in the National Center for Biotechnology Information (NCBI) database with the accession number PRJNA657430.

9.
Med Image Anal ; 69: 101975, 2021 Jan 20.
Article in English | MEDLINE | ID: covidwho-1039485

ABSTRACT

The outbreak of COVID-19 around the world has caused great pressure to the health care system, and many efforts have been devoted to artificial intelligence (AI)-based analysis of CT and chest X-ray images to help alleviate the shortage of radiologists and improve the diagnosis efficiency. However, only a few works focus on AI-based lung ultrasound (LUS) analysis in spite of its significant role in COVID-19. In this work, we aim to propose a novel method for severity assessment of COVID-19 patients from LUS and clinical information. Great challenges exist regarding the heterogeneous data, multi-modality information, and highly nonlinear mapping. To overcome these challenges, we first propose a dual-level supervised multiple instance learning module (DSA-MIL) to effectively combine the zone-level representations into patient-level representations. Then a novel modality alignment contrastive learning module (MA-CLR) is presented to combine representations of the two modalities, LUS and clinical information, by matching the two spaces while keeping the discriminative features. To train the nonlinear mapping, a staged representation transfer (SRT) strategy is introduced to maximumly leverage the semantic and discriminative information from the training data. We trained the model with LUS data of 233 patients, and validated it with 80 patients. Our method can effectively combine the two modalities and achieve accuracy of 75.0% for 4-level patient severity assessment, and 87.5% for the binary severe/non-severe identification. Besides, our method also provides interpretation of the severity assessment by grading each of the lung zone (with accuracy of 85.28%) and identifying the pathological patterns of each lung zone. Our method has a great potential in real clinical practice for COVID-19 patients, especially for pregnant women and children, in aspects of progress monitoring, prognosis stratification, and patient management.

10.
Int J Med Sci ; 18(3): 646-651, 2021.
Article in English | MEDLINE | ID: covidwho-1027827

ABSTRACT

Objectives: A significant proportion of discharged COVID-19 patients still have some symptoms. Traditional Chinese medicine (TCM) has played an important role in the treatment of COVID-19, but whether it is helpful for discharged patients is still unknown. The aim of this study was to retrospectively analyze the impacts of TCM treatment on the convalescents of COVID-19. Methods: A total of 372 COVID-19 convalescents from February 21 to May 3 in Shenzhen, China were retrospectively analyzed, 291 of them accepted clinically examined at least once and 191 convalescents accepted TCM. Results: After retrospective analysis of the clinical data of convalescents accepted TCM treatment or not, we found that the white blood cell count, as well as serum interleukin-6 and procalcitonin decreased in TCM group. Serum γ-glutamyl transpeptidase was significantly decreased, while prealbumin and albumin increased in TCM group. Red blood cell, hemoglobin, and platelet count increased in TCM group. The mechanisms of TCM treatment might be the overall regulations, including balanced immune response, improved hematopoiesis and coagulation systems, enhanced functions of liver and heart, increased nutrient intake and lipid metabolism. Conclusions: This study suggested that TCM treatment would be beneficial for discharged COVID-19 patients. However, long-term medical observation and further study with randomized trial should be done to confirm this result. Besides, the potential molecular mechanisms of TCM treatment should be further revealed.


Subject(s)
/rehabilitation , Convalescence , Drugs, Chinese Herbal/administration & dosage , /blood , Hospitals, Isolation/statistics & numerical data , Humans , Retrospective Studies , Treatment Outcome
11.
J Med Internet Res ; 22(10): e21980, 2020 10 09.
Article in English | MEDLINE | ID: covidwho-1024469

ABSTRACT

BACKGROUND: In the prevention and control of infectious diseases, previous research on the application of big data technology has mainly focused on the early warning and early monitoring of infectious diseases. Although the application of big data technology for COVID-19 warning and monitoring remain important tasks, prevention of the disease's rapid spread and reduction of its impact on society are currently the most pressing challenges for the application of big data technology during the COVID-19 pandemic. After the outbreak of COVID-19 in Wuhan, the Chinese government and nongovernmental organizations actively used big data technology to prevent, contain, and control the spread of COVID-19. OBJECTIVE: The aim of this study is to discuss the application of big data technology to prevent, contain, and control COVID-19 in China; draw lessons; and make recommendations. METHODS: We discuss the data collection methods and key data information that existed in China before the outbreak of COVID-19 and how these data contributed to the prevention and control of COVID-19. Next, we discuss China's new data collection methods and new information assembled after the outbreak of COVID-19. Based on the data and information collected in China, we analyzed the application of big data technology from the perspectives of data sources, data application logic, data application level, and application results. In addition, we analyzed the issues, challenges, and responses encountered by China in the application of big data technology from four perspectives: data access, data use, data sharing, and data protection. Suggestions for improvements are made for data collection, data circulation, data innovation, and data security to help understand China's response to the epidemic and to provide lessons for other countries' prevention and control of COVID-19. RESULTS: In the process of the prevention and control of COVID-19 in China, big data technology has played an important role in personal tracking, surveillance and early warning, tracking of the virus's sources, drug screening, medical treatment, resource allocation, and production recovery. The data used included location and travel data, medical and health data, news media data, government data, online consumption data, data collected by intelligent equipment, and epidemic prevention data. We identified a number of big data problems including low efficiency of data collection, difficulty in guaranteeing data quality, low efficiency of data use, lack of timely data sharing, and data privacy protection issues. To address these problems, we suggest unified data collection standards, innovative use of data, accelerated exchange and circulation of data, and a detailed and rigorous data protection system. CONCLUSIONS: China has used big data technology to prevent and control COVID-19 in a timely manner. To prevent and control infectious diseases, countries must collect, clean, and integrate data from a wide range of sources; use big data technology to analyze a wide range of big data; create platforms for data analyses and sharing; and address privacy issues in the collection and use of big data.


Subject(s)
Big Data , Coronavirus Infections/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Betacoronavirus , China/epidemiology , Computer Security , Coronavirus Infections/epidemiology , Data Collection , Humans , Information Dissemination , Information Storage and Retrieval , Pneumonia, Viral/epidemiology , Privacy
12.
Preprint | SciFinder | ID: ppcovidwho-4915

ABSTRACT

A review on several key scientific issues to be clarified urgently for the new coronavirus (SARS-CoVo-2)

14.
Int J Med Sci ; 18(1): 176-186, 2021.
Article in English | MEDLINE | ID: covidwho-1005042

ABSTRACT

Objective: The aim of this study was to observe the liver function recovery of COVID-19 patients after discharge. Patients and Methods: A total of 253 discharged COVID-19 patients in Shenzhen city, China were selected. The clinical characteristics of these patients were assessed. A 2-month follow-up and laboratory hematology test were performed to examine the status of patients' liver function. Results: Patients combined with liver diseases, especially fatty liver, are more likely to progress to severe condition (P<0.05). Patients in severe condition and those with liver diseases have higher rates of liver injuries during hospitalization, characterized by a significant increase in alanine aminotransferase (ALT) and aspartate aminotransferase (AST, P<0.01). The ALT, AST/ALT, gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), total protein (TP), albumin (ALB), and A/G levels showed significant differences in comparison with the control group (P<0.05, and P<0.001); and the outlier ratio of A/G, ALT, GGT and ALP of patients remained abnormal higher within 14 days after discharge (P<0.001). Liver injuries of COVID-19 patients may be related to the epidemiological characteristics, clinical indexes, basic diseases, symptoms, drug treatment during hospitalization and the complications. Indicators of liver function were correlated with cardiac function, renal function, thyroid function, lipid metabolism, glucose metabolism, immune index, leukocyte, erythrocyte, hemoglobin and platelet related indexes. The outlier ratio of TP, ALB and GLB remained extremely low throughout the follow-up period; the outlier ratio of ALT, AST and GGT decreased below 10% from a high level at 40 days after discharged. However, the outlier ratio of A/G, AST/ALT and ALP remained high during the follow-up period. Conclusions: Abnormal liver function might indicate worse recovery of COVID-19 patients. Changes in liver function should be emphasized during long-term follow-up of COVID-19 patients after hospital discharge; the necessity of employing appropriate interventions for liver function repair should be emphasized.


Subject(s)
/complications , Hepatic Insufficiency/virology , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Cross-Sectional Studies , Female , Follow-Up Studies , Humans , Infant , Liver Function Tests , Male , Middle Aged , Recovery of Function , Young Adult
15.
Proteins ; 2020 Nov 24.
Article in English | MEDLINE | ID: covidwho-970216

ABSTRACT

A novel severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2) has emerged as a human pathogen, causing global pandemic and resulting in over 400 000 deaths worldwide. The surface spike protein of SARS-CoV-2 mediates the process of coronavirus entry into human cells by binding angiotensin-converting enzyme 2 (ACE2). Due to the critical role in viral-host interaction and the exposure of spike protein, it has been a focus of most vaccines' developments. However, the structural and biochemical studies of the spike protein are challenging because it is thermodynamically metastable. Here, we develop a new pipeline that automatically identifies mutants that thermodynamically stabilize the spike protein. Our pipeline integrates bioinformatics analysis of conserved residues, motion dynamics from molecular dynamics simulations, and other structural analysis to identify residues that significantly contribute to the thermodynamic stability of the spike protein. We then utilize our previously developed protein design tool, Eris, to predict thermodynamically stabilizing mutations in proteins. We validate the ability of our pipeline to identify protein stabilization mutants through known prefusion spike protein mutants. We finally utilize the pipeline to identify new prefusion spike protein stabilization mutants.

16.
Journal of Medical Virology ; 92(11):2785-2791, 2020.
Article | WHO COVID | ID: covidwho-959196

ABSTRACT

Previous studies reported that coronavirus disease 2019 (COVID-19) was likely to result in liver injury However, few studies reported the impacts of COVID-19 on liver function in patients with chronic liver diseases We aimed to describe a case series of COVID-19 patients with chronic hepatitis B virus (HBV) infection Confirmed hospitalized COVID-19 patients from hospitals in 10 cities of Jiangsu province, China, were retrospectively included between 18 January 2020 and 26 February 2020 Demographic information, epidemiologic data, clinical features, and treatment data were extracted from medical records Seven COVID-19 patients with chronic HBV infection were included Six (85 7%) patients were male The patients aged from 33 to 49 years Two patients had HBV-related cirrhosis One patient (14 3%) was positive for serum HBV e-antigen On admission, 1 (14 3%) patient had mildly elevated alanine aminotransferase (ALT) level (> 40 U/L) and 1 (14 3%) had elevated aspartate aminotransferase (AST) level (> 40 U/L) The serum albumin level and platelet counts were decreased in two patients with HBV-related liver cirrhosis Three (42 9%) patients had elevated ALT level and 2 (28 6%) patients had elevated AST level in hospitalization However, the peak ALT and AST level during hospitalization was 51 U/L and 44 U/L, respectively As of 29 February 2020, all patients were discharged No patient was admitted to the intensive care units or developed liver failure during hospitalization The abnormalities of liver function are not uncommon on COVID-19 patients with chronic HBV infection in our case series However, no patient developed severe liver-related complications during hospitalization

17.
Int J Med Sci ; 18(2): 347-355, 2021.
Article in English | MEDLINE | ID: covidwho-961814

ABSTRACT

Objectives: Research on recovering COVID-19 patients could be helpful for containing the pandemic and developing vaccines, but we still do not know much about the clinical features, recovery process, and antibody reactions during the recovery period. Methods: We retrospectively analysed the epidemiological information, discharge summaries, and laboratory results of 324 patients. Results: In all, 15 (8.62%) patients experienced chest distress/breath shortness, where 8 of the 15 were severely ill. This means severely ill patients need an extended amount of time to recover after discharge; next, 20 (11.49%) patients experienced anxiety and 21 (12.07%) had headache/insomnia and a small fraction of them complained of anosmia/ageusia, indicating that these patients need treatment for mental and psychological health issues. Regarding the re-positive patients, their CT and laboratory test results showed no obvious evidence of illness progress or infectivity but a high anti-SARS-CoV-2 antibody expression. Conclusion: Recovered COVID-19 patients need psychological and physiological care and treatment, re-positivity can occur in any person, but juveniles, females, and patients with mild/moderate existing symptoms have higher rates of re-positivity, While there is no evidence that turning re-positive has an impact on their infectivity, but it still alerted us that we need differentiate them in the following managements.


Subject(s)
/epidemiology , Adolescent , Adult , Aged , Aged, 80 and over , Ageusia , /rehabilitation , Child , Child, Preschool , China/epidemiology , Female , Follow-Up Studies , Humans , Infant , Male , Middle Aged , Recurrence , Retrospective Studies , Young Adult
18.
Advances in Climate Change Research ; 2020.
Article | WHO COVID | ID: covidwho-956836

ABSTRACT

Reductions in the transportation sector’s carbon dioxide emissions are increasingly of global concern As one of the first low-carbon pilot and carbon trading pilot cities, and as one of the largest automobile production bases in China, Chongqing has multiple low-carbon transportation policies that are coupled In this study, three policy scenarios are set, including: 1) improving the fuel economy of newly sold gasoline passenger cars to 5 7 l per 100 km by 2020, 2) promoting pure electric private cars to increase the share to 7% of private car sales by 2020, and 3) the policy mix scenario of the above two policies Simulations are undertaken with the Chinese Academy of Sciences general equilibrium (CAS-GE) model, a type of computable GE model, to assess the macro-economic impact and the industrial impact of the three policy scenarios Through the policy impact mechanism analysis and data-mapping process, the micro-economic impact analysis results, including costs and fuel savings, for the two policies from the bottom-up model are taken as the shock variables and inputs for the CAS-GE model The results show that: 1) the two policies will both have a slightly negative impact (−0 09% and −0 30%) on Chongqing’s GDP in 2020;2) the employment rate will decrease by 0 12% and 0 47%, but the inflation rate will be restrained to a certain extent (−0 21% and −0 17%);and 3) the complementarity of the mixed policy can weaken the negative impact of the two policies when implemented separately The mixed policy will reduce the GDP slightly by 0 37%, compared with the cumulative effect of the two policies implemented separately, resulting in cost-effective synergies at the macro-economic impact level;and 4) the COVID-19 pandemic in 2020 has an uncertain impact on the results The method and results can provide a reference for the formulation and adjustment of low-carbon transportation policies in other large cities

19.
Vaccine ; 39(2): 247-254, 2021 01 08.
Article in English | MEDLINE | ID: covidwho-957470

ABSTRACT

BACKGROUND: Vaccinations are an effective choice to stop disease outbreaks, including COVID-19. There is little research on individuals' COVID-19 vaccination decision-making. OBJECTIVE: We aimed to determine individual preferences for COVID-19 vaccinations in China, and to assess the factors influencing vaccination decision-making to facilitate vaccination coverage. METHODS: A D-efficient discrete choice experiment was conducted across six Chinese provinces selected by the stratified random sampling method. Vaccine choice sets were constructed using seven attributes: vaccine effectiveness, side-effects, accessibility, number of doses, vaccination sites, duration of vaccine protection, and proportion of acquaintances vaccinated. Conditional logit and latent class models were used to identify preferences. RESULTS: Although all seven attributes were proved to significantly influence respondents' vaccination decision, vaccine effectiveness, side-effects and proportion of acquaintances vaccinated were the most important. We also found a higher probability of vaccinating when the vaccine was more effective; risks of serious side effects were small; vaccinations were free and voluntary; the fewer the number of doses; the longer the protection duration; and the higher the proportion of acquaintances vaccinated. Higher local vaccine coverage created altruistic herd incentives to vaccinate rather than free-rider problems. The predicted vaccination uptake of the optimal vaccination scenario in our study was 84.77%. Preference heterogeneity was substantial. Individuals who were older, had a lower education level, lower income, higher trust in the vaccine and higher perceived risk of infection, displayed a higher probability to vaccinate. CONCLUSIONS: Preference heterogeneity among individuals should lead health authorities to address the diversity of expectations about COVID-19 vaccinations. To maximize COVID-19 vaccine uptake, health authorities should promote vaccine effectiveness; pro-actively communicate the absence or presence of vaccine side effects; and ensure rapid and wide media communication about local vaccine coverage.


Subject(s)
/administration & dosage , Decision Making , Pandemics/prevention & control , Vaccination/psychology , Adolescent , Adult , Aged , /psychology , /supply & distribution , China/epidemiology , Choice Behavior , Educational Status , Female , Humans , Immunity, Innate/drug effects , Immunization Schedule , Immunogenicity, Vaccine , Male , Middle Aged , Models, Statistical , Patient Safety , Surveys and Questionnaires , Vaccination/methods , Vaccination Coverage/statistics & numerical data
20.
J Thorac Dis ; 12(10): 5336-5346, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-934699

ABSTRACT

Background: The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system. Methods: A total of 164 patients confirmed COVID-19 were retrospectively enrolled from 6 hospitals. All patients were divided into the mild type (136 cases) and the severe type (28 cases) according to their clinical manifestations. The total CT severity score and quantitative CT features were calculated by AI pneumonia detection and evaluation system with correction by radiologists. The clinical and CT imaging features of different types were analyzed. Results: It was observed that patients in the severe type group were older than the mild type group. Round lesions, Fan-shaped lesions, crazy-paving pattern, fibrosis, "white lung", pleural thickening, pleural indentation, mediastinal lymphadenectasis were more common in the CT images of severe patients than in the mild ones. A higher total lung severity score and scores of each lobe were observed in the severe group, with higher scores in bilateral lower lobes of both groups. Further analysis showed that the volume and number of pneumonia lesions and consolidation lesions in overall lung were higher in the severe group, and showed a wider distribution in the lower lobes of bilateral lung in both groups. Conclusions: Chest CT of patients with severe COVID-19 pneumonia showed more consolidative and progressive lesions. With the assistance of AI, CT could evaluate the clinical severity of COVID-19 pneumonia more precisely and help the early diagnosis and surveillance of the patients.

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