Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 31
Filter
1.
2022 International Joint Conference on Neural Networks, IJCNN 2022 ; JOUR, 2022-July.
Article in English | Scopus | ID: covidwho-2097620

ABSTRACT

COVID-19 has become a worldwide epidemic. Prediction of COVID-19 is an effective way to control its spread. Recently, some research efforts have made great progress on this task. However, these works rarely combine both the temporal and spatial domains for case number prediction. Moreover, most of them are only suitable for short-term prediction tasks, which cannot achieve good long-term predicting effects. Therefore, we use a method that combines human-mobility factors and time-series factors - the Spatio-temporal convolutional network (G-TCN) to deal with these problems. Firstly, we use data on the mobility of people between regions to generate graphs of regional relationships. Secondly, to process the spatial information at each moment, we apply multi-layer graph convolutional neural networks (GCNs) to aggregate multi-layer neighborhood information. And we input the information obtained by GCNs at different moments into temporal convolutional networks (TCNs), which are used to process the time-series information. Finally, we tested the proposed G-TCN method using datasets from four countries. The experimental results show that G-TCN has lower prediction errors than other comparison methods and can better fit the trend of COVID-19 development. © 2022 IEEE.

2.
Statistica Sinica ; JOUR:2199-2216, 32.
Article in English | Web of Science | ID: covidwho-2082522

ABSTRACT

We consider a novel partially linear additive functional regression model in which both a functional predictor and some scalar predictors appear. The functional part has a semiparametric continuously additive form, while the scalar predictors appear in the linear part. The functional part has the optimal convergence rate, and the asymptotic normality of the nonfunctional part is also shown. Simulations and an empirical analysis of a Covid-19 data set demonstrate the performance of the proposed estimator.

3.
Research Companion to Construction Economics ; : 445-465, 2022.
Article in English | Scopus | ID: covidwho-2040234

ABSTRACT

Economic globalisation, trade liberalisation, advanced technology, and fast transportation all have catalysed the globalisation of construction. This chapter aims to provide a picture of the global construction market. It starts by clarifying some of the concepts and terms, and then empirically describes the historical development and status quo of the market from a global perspective. Global construction has developed into a massive market, a considerable portion of which is undertaken by contractors who 'follow the money' to new continents for growth or to minimise the risk of individual markets. The chapter concludes by considering the future of the global construction market, which is now facing great uncertainty triggered by the rising populism, increasing xenophobia, and distrust of globalisation, which are further exacerbated by the COVID-19 pandemic. There must be a 'new normal', but no one knows what it will look like, and how it will affect the global construction market. © George Ofori 2022.

4.
Asia-Pacific Journal of Clinical Oncology ; 18:10, 2022.
Article in English | EMBASE | ID: covidwho-2032333

ABSTRACT

Objectives: The novel coronavirus (COVID-19) is still recurring so far. Considering that a great number of patients do examination in the same room and thus are exposed to high risks of cross infection, we should promote the epidemic prevention in the radiology department to prevent cross infection and another outbreak. Therefore, this article aims to share the experience and protocols of the radiology department of our hospital so as to help more hospitals and their radiology medical staff in epidemic prevention. Methods: We firstly collected three major epidemic prevention policies formulated by the radiology department since the outbreak, and then drew the schematic diagrams of patients' treatment routes under each measure, including the infection control team, the reconfiguration of the radiology department and the Examination procedures for patients with COVID-19. After three stages, we finally provide a specific machine for patients with COVID-19 to examine. Results: From January 18, 2020, our hospital has received 113 patients with COVID-19, among which 112 patients were discharged and 1 were dead. The total number of outpatients with fever-CT examinations was 2870, that of inpatients were 477. The number of DR exposures was 87, that of US examinations were 207, and that of MRI examinations was 148. No medical workers in the radiology department were diagnosed with COVID-19. Conclusions: Imaging examination has been an indispensable diagnostic method for COVID-19 since the outbreak. As the global epidemic situation is still unstable at present, radiology departments need to constantly improve the corresponding epidemic prevention and control measures, and formulate effective inspection plans for the patients with COVID-19, which can help patients and staff protect themselves against a high risk of COVID-19.

5.
IISE Annual Conference and Expo 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2011282

ABSTRACT

The cancer readmission prediction model classifies patients as high-risk or low-risk for readmittance. Consequently, intervention strategies focus on high-risk patients. Nevertheless, the performance of machine learning models generally degrades over time due to changes in the environment that violates models' assumptions, which include statistical data changes and process changes. This research introduces a framework that improves the sensitivity of the cancer readmission prediction model by identifying new features of cancer readmission, such as Diabetes and Anti-Nausea, which potentially cause the model's sensitivity to drift. The proposed model considers these 20 new factors with the 35 original factors that use the most recent dataset to predict cancer readmissions. Recursive feature elimination was used to identify key features. Some of the most popular classification algorithms, which include logistic regression and adaptive boosting, were used to retrain and classify cancer readmissions. The best algorithm was validated on a new dataset that was collected over 11 months, which covered three different waves of Covid-19. The results suggested K-Nearest Neighbors (KNN) algorithm performs the best among all eight studied algorithms. The KNN model incorporated new dominant features that did not exist in the original Random Forest (RF) model. The KNN model has an improvement of 8.05% in sensitivity compared to the RF model. The presence of Covid-19 does not have a significant impact on the performance of the KNN model. The suggested framework identifies potential admitted patients for intervention actions, helps reduce cancer readmission rates, costs, and improves the quality of care for cancer patients. © 2022 IISE Annual Conference and Expo 2022. All rights reserved.

6.
6th International Conference on E-Commerce, E-Business and E-Government, ICEEG 2022 ; : 423-427, 2022.
Article in English | Scopus | ID: covidwho-1973933

ABSTRACT

During Covid-19, offline business faces cheerless performance, however online e-commerce is booming along with more and more consumer building online shopping behavior considering safety. With the development of e-commerce, shopping livestream become a key driver for online sales. Previous studies found that vivid visibility, interaction, KOL shopping guide etc which are the key characters of shopping livestream will effectively impact purchase behavior through mediating variable-Immersion (Flow). But some studies show opposite result that the mediating effect of immersion is not obvious. Most of studies just focus on the influence to purchase and mediating mechanism of immersion but less studies pay attention the reverse result. That is the meaning and focus of this study. We found that the reason is there is moderating variable-time pressure to impact the mediating effect. We developed a model with four hypotheses. Two independent variable- interaction and entertainment impact impulse purchase intention through mediating variable - Immersion, while time pressure as moderating variable. Result showed that all the hypotheses were successfully established. The main effect of interaction and entertainment on impulse purchase intention was significant, which mediated by immersion. While time pressure as moderating variable effectively adjusted mediating effect. The result and insight can be applied to future business operation. © 2022 ACM.

7.
Global Advances in Health and Medicine ; 11:7, 2022.
Article in English | EMBASE | ID: covidwho-1916574

ABSTRACT

Methods: The study is a retrospective analysis of a virtual acupressure service administered from May to December 2020 at a National Cancer Institute-designated Comprehensive Cancer Center. A semi-standardized virtual acupressure protocol was developed, consisting of 50 min, one-on-one session between the acupuncturist and patient. At the start of each session, the acupuncturist assessed the patient's symptom burden using the Edmonton Symptom Assessment Scale (0-90), for which higher scores represent greater symptom severity. Changes in ESAS scores from baseline to follow-up were evaluated using paired t-test for patients with follow-up within 14 days of baseline. Acupuncturists held weekly group meetings to discuss challenges and ways to improve the delivery of tele-acupressure. Results: A total of 102 virtual acupressure sessions were administered to 32 unique patients. Most patients were females (90.6%) and white (84.4%), the mean age was 55.7 (range=26-82;SD=15.73), and the most common cancer diagnosis was breast (53.1%). Of 32 patients, 13 had follow up in 14 days or less. For these 13 patients, there was a statistically significant reduction in total symptom burden (-4.85±7.6;p=0.04) from baseline to follow-up. Based on the acupuncturists' experiences, various factors were discussed and considered important in implementing virtual acupressure, including effective communications (e.g., both verbal and nonverbal cues), potential technological barriers (e.g., technology literacy), and healing environment (e.g., physical space and/or virtual background appearing on the screen). Background: Oncology acupuncture service was disrupted by COVID-19, and a virtual acupuncturist-guided, patient self-acupressure intervention was implemented. We explore the potential impact of tele-acupressure on patient-reported symptoms and summarize acupuncturists' experiences on the challenges and opportunities of implementing a virtual acupressure service for cancer patients. Conclusion: Virtual acupressure may be a promising therapy for symptom management, especially when in-person acupuncture service may not be feasible, but further research is needed to rigorously evaluate its safety and efficacy among cancer patients.

8.
Drug Evaluation Research ; 45(1):37-47, 2022.
Article in Chinese | Scopus | ID: covidwho-1912085

ABSTRACT

Objective Based on text mining technology and biomedical database, data mining and analysis of coronavirus disease 2019 (COVID-19) were carried out, and COVID-19 and its main symptoms related to fever, cough and respiratory disorders were explored. Methods The common targets of COVID-19 and its main symptoms cough, fever and respiratory disorder were obtained by GenCLiP 3 website, Gene ontology in metascape database (GO) and pathway enrichment analysis, then STRING database and Cytoscape software were used to construct the protein interaction network of common targets, the core genes were screened and obtained. DGIdb database and Symmap database were used to predict the therapeutic drugs of traditional Chinese and Western medicine for the core genes. Results A total of 28 gene targets of COVID-19 and its main symptoms were obtained, including 16 core genes such as IL2, IL1B and CCL2. Through the screening of DGIdb database, 28 chemicals interacting with 16 key targets were obtained, including thalidomide, leflunomide and cyclosporine et al. And 70 kinds of Chinese meteria medica including Polygonum cuspidatum, Astragalus membranaceus and aloe. Conclusion The pathological mechanism of COVID-19 and its main symptoms may be related to 28 common genes such as CD4, KNG1 and VEGFA, which may participate in the pathological process of COVID-19 by mediating TNF, IL-17 and other signal pathways. Potentially effective drugs may play a role in the treatment of COVID-19 through action related target pathway. © 2022 Tianjin Press of Chinese Herbal Medicines. All Rights Reserved.

9.
Journal of China Tourism Research ; 2022.
Article in English | Scopus | ID: covidwho-1900971

ABSTRACT

Health information technology has been widely implemented to ensure travel safety in the current normalization stage of COVID-19. However, levels of public trust and acceptance toward health QR codes are low in many countries, impeding tourism recovery after the outbreak. Thus, this study aims to explore the psychological mechanisms underpinning tourist trust, confidence, and behaviors toward traveling with health QR codes. Using a quota sampling, 1089 respondents were collected across mainland China. Results identify that tourists’ trust in health QR codes is affected by knowledge, perceived efficacy, privacy risk, and security. People’s trust in digital health applications can boost travel confidence and increase acceptance of tracing technology and travel intention after the pandemic. Practical implications for developing policies and strategies to encourage travel are provided. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

10.
Frontiers in Physics ; 10:15, 2022.
Article in English | English Web of Science | ID: covidwho-1883946

ABSTRACT

Coronavirus disease 2019 (COVID-19) has exposed the public safety issues. Obtaining inter-individual contact and transmission in the underground spaces is an important issue for simulating and mitigating the spread of the pandemic. Taking the underground shopping streets as an example, this study aimed to verify commercial facilities' influence on the spatiotemporal distribution of inter-individual contact in the underground space. Based on actual surveillance data, machine learning techniques are adopted to obtain utilizers' dynamics in underground pedestrian system and shops. Firstly, an entropy maximization approach is adopted to estimate pedestrians' origin-destination (OD) information. Commercial utilization behaviors at different shops are modeled based on utilizers' entering frequency and staying duration, which are obtained by re-identifying individuals' disappearances and appearances at storefronts. Based on observed results, a simulation method is proposed to estimate utilizers' spatiotemporal contact by recreating their space-time paths in the underground system. Inter-individual contact events and exposure duration are obtained in view of their space-time vectors in passages and shops. A social contact network is established to describe the contact relations between all individuals in the whole system. The exposure duration and weighted clustering coefficients were defined as indicators to measure the contact degree of individual and the social contact network. The simulation results show that the individual and contact graph indicators are similar across time, while the spatial distribution of inter-individual contact within shops and passages are time-varying. Through simulation experiments, the study verified the effects of self-protection and commercial type adjustment measures.

11.
Ruan Jian Xue Bao/Journal of Software ; 33(3):931-949, 2022.
Article in Chinese | Scopus | ID: covidwho-1776690

ABSTRACT

In recent years, promoting the synergy and intelligence of social governance, and improving the social governance system of co-construction, co-governance and sharing are important development directions for the country. As a production factor, data plays an increasingly critical role in social governance. How to realize the secure query, collaborative management, and intelligent analysis of multi-party massive data is the key issue to improve the effectiveness of social governance. In major public events such as the prevention and control of the COVID-19, distributed social governance faces low computing efficiency, poor multi-party credible coordination, and difficult decision-making for complex tasks. In response to the above challenges, this study proposes on big data based distributed social governance intelligent system based on secure multi-party computing, blockchain technology, and precise intelligence theory. The proposed system can support various applications of social governance that provide decision-making support for the improvement of social governance in the new era. © Copyright 2022, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

13.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-329107

ABSTRACT

Background: Immunity after SARS-CoV-2 infection or vaccination has been threatened by recently emerged SARS-CoV-2 variants. A systematic summary of the landscape of neutralizing antibodies against emerging variants is needed. Methods: We systematically searched PubMed, Embase, Web of Science, and 3 pre-print servers for studies that evaluated neutralizing antibodies titers induced by previous infection or vaccination against SARS-CoV-2 variants and comprehensively collected individual data. We calculated lineage-specific GMTs across different study participants and types of neutralization assays. Findings: We identified 56 studies, including 2,483 individuals and 8,590 neutralization tests, meeting the eligibility criteria. Compared with lineage B, we estimate a 1.5-fold (95% CI: 1.0-2.2) reduction in neutralization against the B.1.1.7, 8.7-fold (95% CI: 6.5-11.7) reduction against B.1.351 and 5.0-fold (95% CI: 4.0-6.2) reduction against P.1. The estimated neutralization reductions for B.1.351 compared to lineage B were 240.2-fold (95% CI: 124.0-465.6) reduction for non-replicating vector platform, 4.6-fold (95% CI: 4.0-5.2) reduction for RNA platform, and 1.6-fold (95% CI: 1.2-2.1) reduction for protein subunit platform. The neutralizing antibodies induced by administration of inactivated vaccines and mRNA vaccines against lineage P.1 were also remarkably reduced by an average of 5.9-fold (95% CI: 3.7-9.3) and 1.5-fold (95% CI: 1.2-1.9). Interpretation: Our findings indicate that the antibody response established by natural infection or vaccination might be able to effectively neutralize B.1.1.7, but neutralizing titers against B.1.351 and P.1 suffered large reductions. Standardized protocols for neutralization assays, as well as updating immune-based prevention and treatment, are needed. Funding: Chinese National Science Fund for Distinguished Young Scholars. Research in context: Evidence before this study: Several newly emerged SARS-CoV-2 variants have raised significant concerns globally, and there is concern that SARS-CoV-2 variants can evade immune responses that are based on the prototype strain. It is not known to what extent do emerging SARS-CoV-2 variants escape the immune response induced by previous infection or vaccination. However, existing studies of neutralizing potency against SARS-CoV-2 variants are based on limited numbers of samples and lack comparability between different laboratory methods. Furthermore, there are no studies providing whole picture of neutralizing antibodies induced by prior infections or vaccination against emerging variants. Therefore, we systematically reviewed and quantitively synthesized evidence on the degree to which antibodies from previous SARS-CoV-2 infection or vaccination effectively neutralize variants. Added value of this study: In this study, 56 studies, including 2,483 individuals and 8,590 neutralization tests, were identified. Antibodies from natural infection or vaccination are likely to effectively neutralize B.1.1.7, but neutralizing titers against B.1.351 and P.1 suffered large reductions. Lineage B.1.351 escaped natural-infection-mediated neutralization the most, with GMT of 79.2 (95% CI: 68.5-91.6), while neutralizing antibody titers against the B.1.1.7 variant were largely preserved (254.6, 95% CI: 214.1-302.8). Compared with lineage B, we estimate a 1.5-fold (95% CI: 1.0-2.2) reduction in neutralization against the B.1.1.7, 8.7-fold (95% CI: 6.5-11.7) reduction against B.1.351 and 5.0-fold (95% CI: 4.0-6.2) reduction against P.1. The neutralizing antibody response after vaccinating with non-replicating vector vaccines against lineage B.1.351 was worse than responses elicited by vaccines on other platforms, with levels lower than that of individuals who were previously infected. The neutralizing antibodies induced by administration of inactivated vaccines and mRNA vaccines against lineage P.1 were also remarkably reduced by an average of 5.9-fold (95% CI: 3.7-9.3) and 1.5-fold (95% CI: 1.2-1.9). Implications of all the available evidence: Our findings indicate that antibodies from natural infection of the parent lineage of SARS-CoV-2 or vaccination may be less able to neutralize some emerging variants, and antibody-based therapies may need to be updated. Furthermore, standardized protocols for neutralizing antibody testing against SARS-CoV-2 are needed to reduce lab-to-lab variations, thus facilitating comparability and interpretability across studies.

16.
Acta Medica Mediterranea ; 38(1):395-403, 2022.
Article in English | Scopus | ID: covidwho-1699243

ABSTRACT

Purpose: To examine the clinical characteristics of patients with severe and critical coronavirus disease and analyze the risk factors for progression to critical disease and adverse outcomes. Methods: Seventy-four clinical markers were analyzed. Patients were followed up until the clinical endpoint (survival or death). Subgroup analyses of severe/critical patients and survivors/deaths examined the risk factors for disease progression and patient outcomes. Results: Median patient age was 65.5 (54.0-73.0) years;64.5% were male. Thirty-two (51.6%) patients had comorbid hypertension;60 (96.8%), fever;and 5 (8.1%), diarrhea. Median lymphocyte count was significantly lower than the reference range (P<0.05);inflammatory marker levels exceeded normal ranges. The probability of comorbid diabetes was higher in the critical group than in the severe group (35.5% vs. 9.7%;P=0.031). There were 50 survivors and 12 deaths. The critical group's mortality rate was 38.7%. Intra-subgroup comparisons of severe/critical and survivor/death groups indicated patients with multiple comorbidities and elevated total white blood cell count had higher risks of progressing to critical disease (odds ratio [OR] [95% confidence interval (CI)], 2.3 [1.2-4.7], P=0.016;1.2 [1.0-1.4], P=0.017). A high SOFA score, lactic acid elevation, and a D-dimer level >2 ug/mL were risk factors for poor prognosis (OR [95% CI], 2.2 [1.0-4.8], P=0.047;3.9 [1.4-11.0], P=0.008;10.0 [1.2-84.2], P=0.033). Conclusion: Patients with multiple comorbidities and elevated total white blood cell count should be monitored closely. A high SOFA score, elevated lactate levels, and a D-dimer level of >2 ug/mL should also be considered as risk factors. © 2022 A. CARBONE Editore. All rights reserved.

17.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326814

ABSTRACT

The outbreak of SARS-CoV-2 continues to pose a serious threat to human health and social and economic stability. In this study, we established an anti-coronavirus drug screening platform based on the Homogeneous Time Resolved Fluorescence (HTRF) technology and the interaction between the coronavirus S protein and its host receptor ACE2. This platform is a rapid, sensitive, specific, and high throughput system. With this platform, we screened two compound libraries of 2,864 molecules and identified three potential anti-coronavirus compounds: tannic acid (TA), TS-1276 (anthraquinone), and TS-984 (9-Methoxycanthin-6-one). Our in vitro validation experiments indicated that TS-984 strongly inhibits the interaction of the coronavirus S-protein and the human cell ACE2 receptor. This data suggests that TS-984 is a potent blocker of the interaction between the S-protein and ACE2, which might have the potential to be developed into an effective anti-coronavirus drug.

18.
Cancer Epidemiology Biomarkers and Prevention ; 31(1 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1677444

ABSTRACT

Background: There is an increasing body of literature that suggests a relationship between modifiable dietary behaviors and alcohol use and liver cancer. We designed and implemented a culturally tailored community-based education program to promote liver cancer prevention. Methods: Through NCI funded U54 TUFCCC/HC Cancer Partnership Community Outreach Core program, using CBPR approach, we engaged community-based organizations and community stakeholders serving underserved African, Asian, and Hispanic American communities in the Philadelphia metropolitan area and New York City. The community-based education incorporated in-person and virtual hybrid education workshops to address COVID-19 pandemic barriers. We conducted preeducation surveys and follow-up assessments at 6 months post-education. Participants' dietary behaviors, alcohol use, and sociodemographic characteristics were examined at both time points. Results: 526 participants were recruited including 92 African Americans, 247 Asian Americans, and 187 Hispanic Americans, with an average age of 59. We found that at 6-month follow-up assessment, participants had average decreased intake of red meat (3.148/6 vs. 2.685/6, p < 0.001), and average increased intake of vegetables (4.484/6 vs. 5.044/6, p < 0.001) and fruits (4.327/6 vs. 4.877/6, p < 0.001), compared to their intake at pre-education assessment. Additionally, average change in beer (-0.252) and spirit (-0.905) consumption substantively decreased from pre-intervention to 6-month follow-up assessment. Conclusion: This community-based education showed significant effects in improving healthy dietary behaviors and reducing alcohol intake among community members through CBPR community engagement from the two metropolitan areas. Future efforts are needed to sustain the positive changes in modifiable lifestyle behaviors and liver cancer prevention in these medically underserved communities.

19.
Frontiers in Built Environment ; 7:11, 2022.
Article in English | Web of Science | ID: covidwho-1674316

ABSTRACT

The built environment closely relates to the development of COVID-19 and post-disaster recovery. Nevertheless, few studies examine its impacts on the recovery stage and corresponding urban development strategies. This study examines the built environment's role in Wuhan's recovery at the city block level through a natural experiment. We first aggregated eight built environmental characteristics (BECs) of 192 city blocks from the perspectives of density, infrastructure supply, and socioeconomic environment;then, the BECs were associated with the recovery rates at the same city blocks, based on the public "COVID-19-free" reports of about 7,100 communities over the recovery stages. The results showed that three BECs, i.e., "number of nearby designated hospitals," "green ratio," and "housing price" had significant associations with Wuhan's recovery when the strict control measures were implemented. At the first time of reporting, more significant associations were also found with "average building age," "neighborhood facility development level," and "facility management level." In contrast, no associations were found for "controlled residential land-use intensity" and "plot ratio" throughout the stages. The findings from Wuhan's recovery pinpointing evidence with implications in future smart and resilient urban development are as follows: the accessibility of hospitals should be comprehensive in general;and the average housing price of a city block can reflect its post-disaster recoverability compared to that of the other blocks.

20.
Respirology ; 26(SUPPL 3):65-66, 2021.
Article in English | EMBASE | ID: covidwho-1583446

ABSTRACT

Background and Aims: Patients with chronic lung disease are highly susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leading to COVID-19. ACE2 is the main receptor for SARS-CoV-2 attachment. Our previous study reported higher ACE2 levels in smokers and COPD patients. Current study investigates if patients with interstitial lung diseases (ILDs) such as IPF and LAM have elevated levels of ACE2, transmembrane peptidase serine 2 (TMPRSS2) and Furin, increasing their risk for SARS-CoV-2 infection. Methods: Surgically resected lung tissue from IPF, LAM patients and normal controls (NC) was immunostained for ACE2, TMPRSS2 and Furin. Percentage ACE2 expression was measured in small airway (SA) epithelium and alveolar areas. Analysis was done using computer-assisted Image- ProPlus 7.0 software. Results: Compared to NC, the percentage ACE2 expression significantly increased in the SA epithelium of IPF (p<0.01), LAM (p<0.001) and in alveolar areas of IPF (p<0.001), LAM (p<0.001). We also observed elevated TMPRSS2 and Furin expression in the same lung tissue areas of IPF and LAM against NC. There was significant positive correlation between smoking history and ACE2 expression in the IPF for SA epithelium (r=0.81, p<0.05) and alveolar areas (r=0.94, p<0.01). Conclusions: This study has investigated the ACE2, TMPRSS2, and Furin in resected lung tissue of IPF and LAM, which suggests that people with ILDs are at higher risk of developing severe COVID-19 infection. To further understand and provide potential therapeutic targets for ILDs, we need to explore other cell types such as type II pneumocytes, alveolar macrophages and endothelial cells.

SELECTION OF CITATIONS
SEARCH DETAIL