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1.
Applied Ecology and Environmental Research ; JOUR: 4633-4644,
Article in English | Web of Science | ID: covidwho-2082713

ABSTRACT

The coronavirus disease 2019 (COVID-19) is spreading around the world, and Taiwan is no exception. Faced with the outbreak of the epidemic, the Taiwan government immediately ordered a policy of banning indoor dining. The main purpose of the present research is to extend a Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) theoretical framework to explore acceptance of sustained utilization behavior of telemedicine in the post-COVID-19 era. An online survey was administered in Taiwan during the COVID-19 pandemic from February 22 to April 6, 2022, and a total of 359 responses were collected by convenience sampling method, and partial least square (PLS) analysis was deployed to examine the hypothesized relationships. The results showed that the sustained utilization behavior of telemedicine had independent significant associations with behavioral intentions;the behavioral intention had independent significant associations with subjective norms, attitudes, perceived behavioral control, perceived usefulness, and perceived ease of use. Moreover, perceived usefulness had independent significant associations with perceived ease of use. This study provides theoretical and practical insights into the psychological and behavioral processes of public use of telemedicine during the post-COVID-19 pandemic, thereby helping policymakers better understand the important developmental implications of telemedicine.

2.
NEJM Catal Innov Care Deliv ; 3(3), 2022.
Article in English | PubMed Central | ID: covidwho-2077191

ABSTRACT

A multidisciplinary team of physicians, physicists, and optical engineers conceived, deployed, and scaled up an operational, financial, and educational solution to address the limited supply of a critical component of safety during the Covid-19 pandemic at 21 hospitals in low- and middle-income countries.

4.
2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 ; : 317-318, 2022.
Article in English | Scopus | ID: covidwho-2051987

ABSTRACT

The movement restrictions of coronavirus had a significant impact on consumer behavior. The rise of cross-border e-commerce has also increased the risks in logistics activities. This work identified the critical threat of cross-border logistics. Additionally, artificial intelligence over Internet of Things (AIoT) technology was found to reduce logistics risk in this work beneficially. © 2022 IEEE.

5.
Fushe Yanjiu yu Fushe Gongyi Xuebao/Journal of Radiation Research and Radiation Processing ; 39(1), 2021.
Article in Chinese | Scopus | ID: covidwho-2040415

ABSTRACT

The outbreak of COVID-19 has led to a sharp increase in the demand for disposable medical protective clothing in the short term. In order to shorten the marketing cycle, a large number of domestic disposable medical protective clothing products have been sterilized by electron beam irradiation, which is more efficient than ethylene oxide sterilization. However, the performance of such clothing must adhere to strict requirements and the process parameters of this sterilization method still lack systematic data support. In order to ensure the reliability of electron beam sterilization of disposable medical protective clothing, research on a corresponding process was carried out. Typical disposable medical protective clothing available on the market made of polypropylene (PP) and coated with polyethylene (PE) was selected as the material studied. An appropriate method was selected to establish the corresponding sterilization dose with reference to the standard methods—“Disposable medical protective clothing irradiation sterilization emergency specification (temporary)”and“ISO 11137-2:2013 Sterilization of health care products—Radiation—Part 2: Establishing the sterilization dose.”The change in material properties after irradiation sterilization with different absorbed doses was studied. Based on the obtained parameters, an algorithm for the average absorbed dose on irradiation by an irradiation electron linac was proposed. Results showed that absorbed doses of 20.3 kGy and 31.5 kGy allowed the products to achieve sterility assurance levels of 10−3 and 10−6, respectively. The material performance of the products after irradiation at 25.0 kGy, 30.0 kGy and 35.0 kGy were able to meet national standard requirements such as elongation at break, breaking strength, impermeability, and filtration efficiency. Thus, a satisfactory electron beam irradiation sterilization process for medical disposable protective clothing has been established. © 2021 The authors.

6.
Vital and Health Statistics, Series 2: Data Evaluation and Methods Research ; 2022:1-27, 2022.
Article in English | Scopus | ID: covidwho-1994639

ABSTRACT

Background The National Health and Nutrition Examination Survey (NHANES) produces national estimates that are representative of the total noninstitutionalized civilian U.S. population. The NHANES sample is selected using a complex, four-stage sample design. NHANES sample weights are used by analysts to produce estimates of the health statistics that would have been obtained if the entire sampling frame (the noninstitutionalized civilian U.S. population) had been surveyed. Sampling errors should be calculated for all survey estimates to assess their statistical reliability. Variance approximation procedures are required to provide reasonable, approximately unbiased, and design-consistent variance estimates for complex sample surveys like NHANES. The 2017–March 2020 files represent a unique public-use data release from NHANES. The coronavirus disease 2019 (COVID-19) pandemic required suspension of data collection in March 2020. As a result, the partially completed NHANES 2019–2020 cycle was not nationally representative. Therefore, the 2019–March 2020 data were combined with the data from the 2017–2018 cycle to create the nationally representative 2017–March 2020 prepandemic data files. Objective This report describes the creation of the NHANES 2017–March 2020 prepandemic data files, including the selection of the appropriate NHANES sample design (2015–2018) to create sample weights and variance units for public-use data files. Additionally, the development of a factor applied to the primary sampling units to adjust the 2017–March 2020 data to fit the NHANES 2015–2018 sample design is described. Analyses to assess representativeness of the target population were performed, and a simulation to replicate the impact of interrupted data collection using earlier NHANES cycles was undertaken. Analytic guidance specific to use for prepandemic data files is also included. © 2022, National Center for Health Statistics. All rights reserved.

7.
International Journal of Gerontology ; 16(3):202-206, 2022.
Article in English | Web of Science | ID: covidwho-1988404

ABSTRACT

Introduction: The coronavirus disease 2019 (COVID-19) has brought excessive patients in emergency departments. Several COVID-19 prediction scores have been developed to aid in the patient disposition of emergency physicians. This study aimed to validate different COVID-19 prediction scores. Method: ???DynaMed??? was used to retrieve high-quality COVID-19 prediction scores for the evaluation of in-hospital mortality rate. SEIMC score, 4C-Mortality score, SOARS score, and Veterans Health Administration COVID-19 (VACO) Index were selected. A retrospective, single-center study was done on elderly patients hospitalized for COVID-19 from May 2021 to July 2021 in MacKay Memorial Hospital. Patients who were (I) negative for COVID-19 examination, (II) aged 65 years old, (III) previously infected with COVID-19 and de-isolated (IV) hospital-acquired COVID-19 infection, (V) not admitted for hospitalization, and (VI) with missing of demographic characteristics were excluded. The area under the receiver operating characteristic curves (AUC) was computed to predict the in-hospital mortality rate. Result: Of 66,090 patients who underwent COVID-19 examination in MacKay Memorial Hospital, 133 patients were included in this study, with 26 deceased patients (19.5%). Among included patients, the median age was 74.38 years and 53% patients were male. Of the selected COVID-19 prediction scores, 4C-Mortality Score (AUC = 0.8), SEIMC score (AUC = 0.75), and SOARS score (AUC = 0.72) contained a good prognostic value, with an AUC 0.70. VACO index demonstrated less predictive value (AUC = 0.61). Conclusion: COVID-19 prediction scores were validated, and it was found that 4C-Mortality Score, SEIMC score, and SOARS score performed well in predicting the in-hospital mortality rate of elderly patients with COVID-19, and 4C-Mortality score is best appreciated.

8.
IEEE International Conference on Smart Mobility (ICSM) ; : 27-31, 2022.
Article in English | Web of Science | ID: covidwho-1985495

ABSTRACT

Accidents and emergency situations have been on a constant rise, especially during the COVID-19 pandemic. Typically, the emergency vehicle dispatch and routing problems involve various dynamic factors which make them very different from conventional vehicle routing problems. This paper presents a metaheuristic approach to emergency vehicle dispatch and routing. Dispatching aims at allotting and sending the nearby available vehicle to the location of emergency and routing deals with selecting the ideal route to reach the destination. The objective is to minimize incident response time and the total time travel for the vehicle from the dispatch point to the destination. This usually depends on the emergency service vehicle availability and other dynamic factors such as traffic, number of turns in the route, etc. Three different bio-inspired algorithms, namely, ant colony optimization, adaptive ACO and firefly algorithm are investigated. Performance evaluation shows that firefly algorithm outperforms the other algorithms in terms of cost, number of turns, and run time for the given data set. However, in case of larger datasets and multiple variables if involved, adaptive ACO gives better results but takes longer time.

9.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(7): 1038-1043, 2022 Jul 10.
Article in Chinese | MEDLINE | ID: covidwho-1940573

ABSTRACT

As 2019-nCoV vaccine is widely used in the adult population, children and adolescents have gradually become an important susceptible population to 2019-nCoV due to their low coverage of the vaccine and high contact degree. Understanding the characteristics of 2019-nCoV infection in minors is vital. This paper summarized the progress in the research of 2019-nCoV in minors by using the data from the retrieval of recently published literature. Furthermore, the key characteristics of 2019-nCoV infection in minors, including the susceptibility, transmissibility, prognosis and immune response were analyzed and the progress in child and adolescent vaccine development was introduced.


Subject(s)
COVID-19 , Adolescent , Adolescent Development , Adult , COVID-19 Vaccines , Child , Humans , Prognosis , SARS-CoV-2
10.
Digital Health ; 8:16, 2022.
Article in English | Web of Science | ID: covidwho-1916883

ABSTRACT

In many regions of the world, with the gradual increase in the supply of COVID-19 vaccines, COVID-19 vaccination has changed from centralized government control to personalized selection. When choosing a location for COVID-19 vaccination, in addition to subjective preferences, objective information (such as the expected waiting time at a COVID-19 vaccination location and the crowdedness and reliability of the vaccination location) also need to be considered. However, it is not convenient for an individual to collect and compare such information. To address this issue, this research applies web content mining to extract the conditions of COVID-19 vaccination locations. Then, a novel asymmetric calibrated fuzzy inverse of column sum and fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje recommendation mechanism is proposed. Finally, an intelligent system is developed to assist a user in selecting a personalized COVID-19 vaccination location. In a regional experiment conducted in Taichung City, Taiwan, the developed intelligent system was applied to assist 20 users in choosing personalized COVID-19 vaccination locations. The successful recommendation rate was 95%.

11.
2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2022 ; : 564-568, 2022.
Article in English | Scopus | ID: covidwho-1901471

ABSTRACT

Agent-based modeling has been widely used in the simulation of global pandemics, which provides useful policy implications and helps contain the pandemic's spread. Through agent-based modeling (ABM), people gain insight into the transmission of the pandemic and develop better policies to contain its spread. This article introduces the existing agent-based models used in the pandemic, such as smallpox, H1N1, and COVID-19, and the conclusions about pandemic forecasting that the scientists have reached through ABM. The introduction also shows the development and improvement of ABM as the computational power increases. It has been concluded from the existing research that implementing contact tracing and lockdown regulations could contribute to the achievement of digital herd immunity and contain the spread of the pandemic. Currently, scientists are dedicated to making a more scalable version of the agent-based model to analyze the transmission of the virus on a global scale. © 2022 IEEE.

12.
Chinese Journal of Experimental Traditional Medical Formulae ; 28(8):116-122, 2022.
Article in Chinese | Scopus | ID: covidwho-1893396

ABSTRACT

The theoretical origin of the combined therapy of lung and intestine can be traced back to the Inner Canon of Huangdi, which explains the physiological and pathological interaction between the lung and the large intestine. In recent years, researchers have investigated the scientific essence of the "lung- intestine axis" theory from many aspects, which enriches the relevant theoretical basis, and applied it to the treatment of COVID-19, acute lung injury, and other lung diseases. The close relation between lung and intestine in many aspects embodies the holistic conception of traditional Chinese medicine and explains the holistic theory of interrelation between organs, which correlate to each other physiologically and pathologically. Intestinal microecological disorders can affect lung immune function and cause respiratory diseases, and respiratory diseases are usually accompanied by gastrointestinal symptoms. Lung diseases can be prevented and treated by regulating intestinal flora. According to histoembryology, the epithelial tissue of the lung and intestine comes from primitive foregut. In immunology, both lung and intestine contain mucosa-associated lymphoid tissue, and the pathological changes of the respiratory tract are also closely related to intestinal microorganisms. The tissue origin of lung and large intestine, the correlation of mucosal immunity, and the synchronization of ecological changes provide a scientific basis for the combined therapy of lung and intestine. Therefore, this paper summarizes the theoretical origin, modern research mechanism, and clinical application of combined therapy of lung and intestine, in order to provide a new direction for its application in clinical and scientific research. © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.

13.
Multiple Sclerosis Journal ; 28(1_SUPPL):87-88, 2022.
Article in English | Web of Science | ID: covidwho-1866099
14.
2022 IEEE International Conference on Smart Mobility, SM 2022 ; : 27-31, 2022.
Article in English | Scopus | ID: covidwho-1846130

ABSTRACT

Accidents and emergency situations have been on a constant rise, especially during the COVID-19 pandemic. Typically, the emergency vehicle dispatch and routing problems involve various dynamic factors which make them very different from conventional vehicle routing problems. This paper presents a metaheuristic approach to emergency vehicle dispatch and routing. Dispatching aims at allotting and sending the nearby available vehicle to the location of emergency and routing deals with selecting the ideal route to reach the destination. The objective is to minimize incident response time and the total time travel for the vehicle from the dispatch point to the destination. This usually depends on the emergency service vehicle availability and other dynamic factors such as traffic, number of turns in the route, etc. Three different bio-inspired algorithms, namely, ant colony optimization, adaptive ACO and firefly algorithm are investigated. Performance evaluation shows that firefly algorithm outperforms the other algorithms in terms of cost, number of turns, and run time for the given data set. However, in case of larger datasets and multiple variables if involved, adaptive ACO gives better results but takes longer time. © 2022 IEEE.

15.
J Eur Acad Dermatol Venereol ; 36(9): 1612-1622, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1832146

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, wearing PPE can induce skin damage such as erythema, pruritus, erosion, and ulceration among others. Although the skin microbiome is considered important for skin health, the change of the skin microbiome after wearing PPE remains unknown. OBJECTIVE: The present study aimed to characterize the diversity and structure of bacterial and fungal flora on skin surfaces of healthcare workers wearing personal protective equipment (PPE) during the COVID-19 pandemic using metagenomic next-generation sequencing (mNGS). METHODS: A total of 10 Chinese volunteers were recruited and the microbiome of their face, hand, and back were analysed before and after wearing PPE. Moreover, VISIA was used to analyse skin features. RESULTS: Results of alpha bacterial diversity showed that there was statistically significant decrease in alpha diversity indice in the skin samples from face, hand, and three sites after wearing PPE as compared with the indice in the skin samples before wearing PPE. Further, the results of evaluated alpha fungal diversity show that there was a statistically significant decrease in alpha diversity indices in the skin samples from hand after wearing PPE as compared with the indices in the skin samples before wearing PPE (P < 0.05). Results of the current study found that the main bacteria on the face, hand, and back skin samples before wearing the PPE were Propionibacterium spp. (34.04%), Corynebacterium spp. (13.12%), and Staphylococcus spp. (38.07%). The main bacteria found on the skin samples after wearing the PPE were Staphylococcus spp. (31.23%), Xanthomonas spp. (26.21%), and Cutibacterium spp. (42.59%). The fungal community composition was similar in three skin sites before and after wearing PPE. CONCLUSION: It was evident that wearing PPE may affect the skin microbiota, especially bacteria. Therefore, it was evident that the symbiotic microbiota may reflect the skin health of medical workers during the COVID-19 pandemic.


Subject(s)
COVID-19 , Personal Protective Equipment , Bacteria , COVID-19/epidemiology , Fungi , Health Personnel , Humans , Pandemics
16.
Chinese Journal of Evidence-Based Medicine ; 22(4):457-462, 2022.
Article in Chinese | EMBASE | ID: covidwho-1818645

ABSTRACT

Objective To assess the methodological quality of pediatric COVID-19 guidelines using the AGREE Ⅱ. Methods Domestic and foreign pediatric COVID-19 guidelines from inception to 1st Oct 2021 were electronically searched in PubMed, CBM, CNKI, VIP, WanFang Data, Medlive, NGC, GIN, and NICE databases and relevant websites. Two researchers independently assessed the methodological quality of the guidelines by using AGREE Ⅱ. Results A total of 21 guidelines were included. The AGREE Ⅱ results revealed that the average scores of included guidelines in 6 domains (scope and purpose, stakeholder involvement, rigor of development, clarity of presentation, applicability, and editorial independence) were 62.70%, 36.24%, 20.34%, 50.42%, 22.12% and 53.17%, respectively. Conclusion The methodological quality of pediatric COVID-19 guidelines is poor. Guideline developers should follow the requirements of AGREE Ⅱ in guideline development.

17.
14th International Conference on Agents and Artificial Intelligence (ICAART) ; : 561-567, 2022.
Article in English | Web of Science | ID: covidwho-1798808

ABSTRACT

With the COVID-19 pandemic, several efforts have been made to develop quick and effective diagnoses to assist health professionals in decision-making. In this work, we employed convolutional neural networks to classify chest radiographic images of patients between normal, pneumonia, and COVID-19. We evaluated the division of the images into patches, followed by the ensemble between the specialist networks in each of the image's parts. As a result, our classifier reached 90.67% in the test, surpassing another method in the literature.

18.
10th International Conference of Educational Innovation through Technology, EITT 2021 ; : 63-68, 2021.
Article in English | Scopus | ID: covidwho-1769573

ABSTRACT

To examine the online teaching attitudes of university teachers and the influencing factors during the Covid-19 pandemic, this study conducted a large-scale survey (N=1090) on university teachers in 16 provinces in China. A series of Kruskal-Wallis nonparametric tests were performed to determine the impact of teacher demographic characteristics on their online teaching attitudes. The results revealed that most teachers had positive opinions of online instruction with several perceived benefits, but also recognized the challenges and disadvantages to teach online. The differences in age, educational background, professional titles and prior online teaching experience significantly affected teachers' attitudes towards online teaching. The study concluded with several implication for preparing university teachers for online instruction in the post-pandemic world. © 2021 IEEE.

19.
Patient Educ Couns ; 105(8): 2793-2800, 2022 08.
Article in English | MEDLINE | ID: covidwho-1763930

ABSTRACT

OBJECTIVE: Describe COVID-19 information-seeking experiences for culturally and linguistically diverse groups in Sydney, Australia. METHODS: Cross-sectional survey, translated into 11 languages; participants recruited from March 21 to July 9, 2021. Regression models identified factors associated with difficulty finding easy-to-understand COVID-19 information. RESULTS: Across 708 participants (88% born overseas, 31% poor English proficiency), difficulty finding easy-to-understand COVID-19 information was rated 4.13 for English (95%CI: 3.85-4.41) and 4.36 for non-English language materials (95%CI: 4.07-4.66) (1 easy to 10 hard). Participants who were older (p < 0.001), had inadequate health literacy (p < 0.001), or poor English proficiency (p < 0.001) found it harder to find easy-to-understand English-language COVID-19 information. Those who had greater difficulty finding easy-to-understand non-English COVID-19 information were younger (p = 0.004), had poor English proficiency (p < 0.001), were university-educated (p = 0.05), and had spent longer living in Australia (p = 0.001). They were more likely to rely on friends and family for COVID-19 information (p = 0.02). There was significant variation in information-seeking experiences across language groups (p's < 0.001). CONCLUSIONS: Easy-to-understand and accessible COVID-19 information is needed to meet the needs of people in culturally and linguistically diverse communities. PRACTICE IMPLICATIONS: COVID-19 communication efforts must involve working alongside these communities to leverage existing communication channels and tailor messages.


Subject(s)
COVID-19 , Health Literacy , Australia/epidemiology , COVID-19/epidemiology , Cross-Sectional Studies , Humans , Language
20.
Biophysical Journal ; 121(3):225A-225A, 2022.
Article in English | Web of Science | ID: covidwho-1755809
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