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1.
ACS Nano ; 2022.
Article in English | PubMed | ID: covidwho-1805554

ABSTRACT

The key to controlling the spread of the coronavirus disease 2019 (COVID-19) and reducing mortality is highly dependent on the safe and effective use of vaccines for the general population. Current COVID-19 vaccination practices (intramuscular injection of solution-based vaccines) are limited by heavy reliance on medical professionals, poor compliance, and laborious vaccination recording procedures, resulting in a waste of health resources and low vaccination coverage, etc. In this study, we developed a smart mushroom-inspired imprintable and lightly detachable (MILD) microneedle platform for the effective and convenient delivery of multidose COVID-19 vaccines and decentralized vaccine information storage. The mushroom-like structure allows the MILD system to be easily pressed into the skin and detached from the patch base, acting as a "tattoo" to record the vaccine counts in situ without any storage equipment, offering quick accessibility and effortless readout, saving a great deal of valuable time and energy for both patients and health professionals. After loading inactivated SARS-CoV-2 virus-based vaccines, MILD system induced a high level of antibodies against the SARS-CoV-2 receptor-binding domain (RBD) in vivo without eliciting systemic toxicity and local damage. Collectively, this smart delivery platform serves as a promising carrier to improve COVID-19 vaccination efficacy through its dual capabilities of vaccine delivery and in situ data storage, thus exhibiting great potential for helping to contain the COVID-19 pandemic or a resurgence.

2.
Front Public Health ; 10:829715, 2022.
Article in English | PubMed | ID: covidwho-1792879

ABSTRACT

OBJECTIVES: To investigate the impact of cannabis use on the infection and survival outcomes of COVID-19. STUDY DESIGN: Cross-sectional study based on the UK Biobank (UKB) dataset. METHODS: We identified 13,099 individuals with cannabis smoking history in the UKB COVID-19 Serology Study. The Charlson-Quan Comorbidity Index was estimated using inpatient ICD-10 records. Multivariable logistic regression characterized features associated with COVID-19 infection. Cox models determined the hazard ratios (HR) for COVID-19-related survival. RESULTS: Cannabis users were more likely to getting COVID-19 (odds ratio: 1.22, P = 0.001) but multivariable analysis showed that cannabis use was a protective factor of COVID-19 infection (adjusted odds ratio: 0.81, P = 0.001). Regular cannabis users, who smoked more than once per month, had a significantly poorer COVID-19-related survival, after adjusting for known risk factors including age, gender, smoking history, and comorbidity (adjusted hazard ratio: 2.81, P = 0.041). CONCLUSIONS: The frequency of cannabis use could be considered as a candidate predictor for mortality risk of COVID-19.

3.
Journal of Virology ; 96(1):23, 2022.
Article in English | Web of Science | ID: covidwho-1762628

ABSTRACT

The replication of coronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and the recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is closely associated with the endoplasmic reticulum (ER) of infected cells. The unfolded protein response (UPR), which is mediated by ER stress (ERS), is a typical outcome in coronavirus-infected cells and is closely associated with the characteristics of coronaviruses. However, the interaction between virus-induced ERS and coronavirus replication is poorly understood. Here, we demonstrate that infection with the betacoronavirus porcine hemagglutinating encephalomyelitis virus (PHEV) induced ERS and triggered all three branches of the UPR signaling pathway both in vitro and in vivo. In addition, ERS suppressed PHEV replication in mouse neuro-2a (N2a) cells primarily by activating the protein kinase R-like ER kinase (PERK)-eukaryotic initiation factor 2 alpha (eIF2 alpha) axis of the UPR. Moreover, another eIF2 alpha phosphorylation kinase, interferon (IFN)-induced double-stranded RNA-dependent protein kinase (PKR), was also activated and acted cooperatively with PERK to decrease PHEV replication. Furthermore, we demonstrate that the PERK/PKR-eIF2 alpha pathways negatively regulated PHEV replication by attenuating global protein translation. Phosphorylated eIF2 alpha also promoted the formation of stress granules (SGs), which in turn repressed PHEV replication. In summary, our study presents a vital aspect of the host innate response to invading pathogens and reveals attractive host targets (e.g., PERK, PKR, and eIF2 alpha) for anti-viral drugs. IMPORTANCE Coronavirus diseases are caused by different coronaviruses of importance in humans and animals, and specific treatments are extremely limited. ERS, which can activate the UPR to modulate viral replication and the host innate response, is a frequent occurrence in coronavirus-infected cells. PHEV, a neurotropic betacoronavirus, causes nerve cell damage, which accounts for the high mortality rates in suckling piglets. However, it remains incompletely understood whether the highly developed ER in nerve cells plays an antiviral role in ERS and how ERS regulates viral proliferation. In this study, we found that PHEV infection induced ERS and activated the UPR both in vitro and in vivo and that the activated PERK/PKR-eIF2 alpha axis inhibited PHEV replication through attenuating global protein translation and promoting SG formation. A better understanding of coronavirus-induced ERS and UPR activation may reveal the pathogenic mechanism of coronavirus and facilitate the development of new treatment strategies for these diseases.

4.
Clin J Sport Med ; 32(2): 177-232, 2022 Mar 01.
Article in English | MEDLINE | ID: covidwho-1758919
5.
INFORMS International Conference on Service Science, ICSS 2020 ; : 367-379, 2022.
Article in English | Scopus | ID: covidwho-1750469

ABSTRACT

In the face of public emergencies, how to better manage public opinion and maintain social stability is an important research content. Based on the background of the new epidemic in 2020, this paper explores how social emotions are transmitted among the government, the media and the public under public emergencies. Through natural language processing technology, this paper analyzes the relevant policies and media opinions of China, Britain and the United States under the new epidemic situation, and uses mf-dcca model to test the internal cross correlation. The results of the experiment unexpectedly found that a country’s government policy and the country’s media have a high degree of consistency in emotional orientation, and when the country’s social mood has abnormal fluctuations, the media will make adverse emotional statements, thus hedging the impact of some extreme policies on the society. From the perspective of emotion, this study provides a further theoretical basis for the relationship between the government and the public, proposes another control role of the media in emergencies, and discusses the relevant methods of media hedging government policies in the impact of social emotions. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

7.
Fortschritte Der Neurologie Psychiatrie ; 89(12):602-603, 2021.
Article in German | Web of Science | ID: covidwho-1576116
8.
Female Pelvic Medicine and Reconstructive Surgery ; 27(10 SUPPL 1):S126, 2021.
Article in English | EMBASE | ID: covidwho-1511128

ABSTRACT

Objective: Our department rapidly adopted a telemedicine option for outpatient evaluation of women with pelvic floor disorders during the pandemic. Our objective was to determine the proficiency of telemedicine in diagnosis of pelvic floor disorders and if an initial telemedicine visit impacted the rate of surgical management compared to an in-person evaluation. Methods: We performed a retrospective cohort study of all new patients referred to a single attending provider in female pelvic medicine at a tertiary care referral center who were seen via a telemedicine visit in the first 2 months of telehealth adoption during the COVID pandemic. New telemedicine patients were then compared to patients seen for a new in-person visit over the same time period the previous year. Via chart review, we collected demographic data, primary diagnoses rendered following visit completion and treatment (medical versus surgical) chosen. We compared the rate of surgical posting, number of visits from initial visit until the date of surgery, and rate of surgery cancellation in women seen for a pelvic floor disorder as a new in-person versus by telemedicine. Results: A total of 310 new patient visits were queried: 182 (59%) that took place in person between June 1 and July 30, 2019 and 128 via telemedicine over the same timeframe in 2020 (41%). Table 1 presents comparative demographic data, primary diagnoses and surgical procedures that resulted in each cohort. For women with a diagnosis of stress or mixed urinary incontinence, the rate of surgical posting for a sling procedure in-person- v. by telemedicine was 25% and 38%, P = 0.176. For women with a diagnosis of pelvic organ prolapse, the rate of surgical posting in-person v. by-telemedicine was 42% and 47%, P = 0.578. The median total number of outpatient visits required from initial visit to day of surgery was 2 in both groups, and the rate of surgery cancellation was 26% (in-person) and 12%(telemedicine), P = 0.168. Conclusions: New patient visits conducted via telemedicine resulted in similar rates of accurate surgical postings for both urinary incontinence and pelvic organ prolapse despite the absence of a pelvic examination. This data is useful for continuation of telemedicine platforms post pandemic.

9.
Female Pelvic Medicine and Reconstructive Surgery ; 27(10 SUPPL 1):S81, 2021.
Article in English | EMBASE | ID: covidwho-1511116

ABSTRACT

Objective: Minimizing hospital admission and maximizing utilization of outpatient surgery facilities are critical for patients undergoing elective surgery during the COVID-19 pandemic in order to prevent viral spread within healthcare facilities and maximize inpatient hospital bed availability. Methods: We implemented an early recovery after surgery (ERAS) protocol for all patients undergoing female pelvic reconstructive surgery starting on June 1st, 2020 by a single surgeon. The protocol included pre-op hydration, a urinary anesthetic, pre- and post-op acetaminophen and ibuprofen, postop perineal ice and bowel regimen, identification and enrollment of family members to assist with care, and communication regarding planned sameday discharge. We compared demographic, operative, hospital stay, complications, and cost data in patients pre (PRE) and post (POST) ERAS implementation. Results: In all, 173 patients (82 PRE Nov 2019 - Feb 2020, 91 POST June - Sept 2020) were included. There were no differences in age, body mass index, ASA score, smoking history, surgery type, operative time, intra-op complications, and post-op complications between the PRE and POST groups (P > 0.05). POST patients had a higher mean Charlson Comorbidity Index (2.6 vs 1.9, P = 0.0132). Significantly more surgeries were done in an outpatient setting in the POST group (73.6% vs 48.8%, P = 0.0008), and significantly more patients were discharged on the day of surgery in the POST group (80.2% vs 50.0%, P = 0.0003). There were no differences in the rates of unexpected emergency room or clinic visits (P > 0.05). Both peri-op and discharge opiate requirements did not significantly differ but trended towards being reduced in POST patients (P = 0.0782 and 0.0926, respectively). Post-op opiate requirement was significantly reduced in the POST group (P < 0.0001). There were no significant differences between revenues, expenses, and margins between the two groups (P > 0.05);however, there was a trend towards an increased operating margin in the POST group ($4,554 vs $2,151, p = 0.1163). Bed unit cost was significantly lower in the POST group ($210 vs $533, P < 0.0001). Conclusions: In patients undergoing female pelvic reconstructive surgery, an early recovery after surgery protocol facilitated transfer of procedures to an outpatient surgical site and permitted same-day discharge without increasing complications, clinic visits, or emergency room visits. It may also reduce cost and improve operating margins to hospital systems.

10.
ACS Earth and Space Chemistry ; 2021.
Article in English | Scopus | ID: covidwho-1467041

ABSTRACT

Lockdown due to the novel coronavirus disease 2019 (COVID-19) pandemic offers a unique opportunity to study the factors governing the variation in air pollution. A number of studies have investigated the cause underlying the occurrence of heavy haze pollution around the world during the lockdown period. However, information about spatiotemporal variations in gaseous pollutants and detailed quantifications of potential meteorological (METRO) impacts are limited. Ground measurements show that carbon monoxide (CO) pollution deteriorated in northern China despite strict control of human and industrial activities during the lockdown period in early 2020. In this study, a four-dimensional decomposition model was used to quantitatively extract the METRO impacts on the CO pollution over China. The results show that weakened winds elevated CO concentrations near Beijing and in northeastern China. Increased temperatures slightly elevated CO concentrations in northern and eastern China but reduced CO concentrations in northwestern China. Remarkable amounts of CO increases in northern China (e.g., by 0.21 mg/m3 within Beijing) were explained by anomalously high humidity, which could be associated with an enhanced interaction between aerosol and the boundary layer. After excluding the METRO impacts, the CO concentrations drastically declined across China (e.g., by 0.22 mg/m3 within Beijing), indicating that the lockdown indeed greatly lessened CO concentrations. However, the adverse METRO conditions counteracted the beneficial outcomes of emission reductions, leading to a deterioration of the CO pollution in northern China. These results indicate that the METRO factors can play a critical role in worsening air pollution despite a strict control of anthropogenic emissions. © 2021 American Chemical Society.

11.
Research Methodology in Strategy and Management ; 13:123-150, 2021.
Article in English | Scopus | ID: covidwho-1416184

ABSTRACT

In this chapter, we explicate two related techniques that help quantify the sensitivity of a given causal inference to potential omitted variables and/or other sources of unexplained heterogeneity. In particular, we describe the Impact Threshold of a Confounding Variable (ITCV) and the Robustness of Inference to Replacement (RIR). The ITCV describes the minimum correlation necessary between an omitted variable and the focal parameters of a study to have created a spurious or invalid statistical inference. The RIR is a technique that quantifies the percentage of observations with nonzero effects in a sample that would need to be replaced with zero effects in order to overturn a given causal inference at any desired threshold. The RIR also measures the percentage of a given parameter estimate that would need to be biased in order to overturn an inference. Each of these procedures is critical to help establish causal inference, perhaps especially for research urgently studying the COVID-19 pandemic when scholars are not afforded the luxury of extended time periods to determine precise magnitudes of relationships between variables. Over the course of this chapter, we define each technique, illustrate how they are applied in the context of seminal strategic management research, offer guidelines for interpreting corresponding results, and delineate further considerations. © 2021 Emerald Publishing Limited.

12.
25th International Conference on Pattern Recognition (ICPR) ; : 8782-8788, 2021.
Article in English | Web of Science | ID: covidwho-1388101

ABSTRACT

Lung segmentation on CT images is a crucial step for a computer-aided diagnosis system of lung diseases. The existing deep learning based lung segmentation methods are less efficient to segment lungs on clinical CT images, especially that the segmentation on lung boundaries is not accurate enough due to complex pulmonary opacities in practical clinics. In this paper, we propose a boundary-guided network (BG-Net) to address this problem. It contains two auxiliary branches that seperately segment lungs and extract the lung boundaries, and an aggregation branch that efficiently exploits lung boundary cues to guide the network for more accurate lung segmentation on clinical CT images. We evaluate the proposed method on a private dataset collected from the Osaka university hospital and four public datasets including StructSeg [1], HUG [2], VESSEL12 [3], and a Novel Coronavirus 2019 (COVID-19) dataset [4]. Experimental results show that the proposed method can segment lungs more accurately and outperform several other deep learning based methods.

13.
25th International Conference on Pattern Recognition (ICPR) ; : 9007-9014, 2021.
Article in English | Web of Science | ID: covidwho-1388100

ABSTRACT

COVID-19 emerged towards the end of 2019 which was identified as a global pandemic by the world heath organization (WHO). With the rapid spread of COVID-19, the number of infected and suspected patients has increased dramatically. Chest computed tomography (CT) has been recognized as an efficient tool for the diagnosis of COVID-19. However, the huge CT data make it difficult for radiologist to fully exploit them on the diagnosis. In this paper, we propose a computer-aided diagnosis system that can automatically analyze CT images to distinguish the COVID-19 against to community-acquired pneumonia (CAP). The proposed system is based on an unsupervised pulmonary opacity detection method that locates opacity regions by a detector unsupervisedly trained from CT images with normal lung tissues. Radiomics based features are extracted insides the opacity regions, and fed into classifiers for classification. We evaluate the proposed CAD system by using 200 CT images collected from different patients in several hospitals. The accuracy, precision, recall, fl-score and AUC achieved are 95.5%, 100%, 91%, 95.1% and 95.9% respectively, exhibiting the promising capacity on the differential diagnosis of COVID-19 from CT images.

14.
World Journal of Traditional Chinese Medicine ; 7(2):258-264, 2021.
Article in English | EMBASE | ID: covidwho-1270177

ABSTRACT

Background: The global outbreak of coronavirus disease 2019 (COVID-19) has brought disastrous consequences to public health and medical systems, whereas no approved medications are currently available. Benefits of traditional Chinese medicine (TCM) against COVID-19 have been observed, however, the underlying mechanistic actions remain unclarified. Due to high pathogenicity and infectivity of the new coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]), the lack of access to SARS-CoV-2 and biosafety level 3 (P3) facilities has impeded scientific investigations of TCM against COVID-19. Though low-pathogenic coronavirus and pseudoviral systems have been applied to substitute SARS-CoV-2 in fundamental studies, both models cannot imitate virological and clinical features associated with SARS-CoV-2. The virus-like particle (VLP) is a virological model that is safe and could be performed without biosafety protections. Aims and Objectives: To construct VLP of SARS-CoV-2 containing structural proteins of authentic viruses and resembling the morphology, partial life cycle, and immunoreactions of natural virions, and to introduce VLP into Chinese medical research. Materials and Methods: Using mammalian expression system, we have currently constructed SARS-CoV-2 VLP containing four essential structural proteins. Results: Based on this model, we propose six aspects of research that could be carried out for TCM formulas in the fight against COVID-19. Conclusion: Application of the VLP model provides a safe methodology to strengthen the response systems of Chinese medicine in preventing and controlling newly identified infectious diseases and offers collaborative opportunities for interdisciplinary deciphering of molecular and biological basis of anti-viral TCM formulas. ©2021 World Journal of Traditional Chinese Medicine ;Published by Wolters Kluwer . Medknow.

15.
Public Health ; 195: 152-157, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1267892

ABSTRACT

OBJECTIVES: The retail food industry, a major essential business, is among the very few thriving sectors during the COVID-19 pandemic. However, such prosperity on the store side does not guarantee a sufficient food supply for all populations. This study aims to understand if people's risk perception and food security status shaped their food procurement behaviors during the early outbreak of the pandemic. STUDY DESIGN: Extended from the theory of risk perception, food consumers may behave differently during a disastrous event in terms of store patronization. The study evaluates how food procurement behaviors are affected by perceived risk aversion, resource scarcity, and consumers' food security status. METHODS: The study examines how people with different food security statuses made grocery shopping decisions at the risk of epidemic exposure based on a nationwide survey of 2590 participants in the U.S. during the early break of the pandemic in April 2020. The study uses a moderated mediation analysis on in-store shopping frequency and food expenditure. RESULTS: People having a food-secure status before the pandemic spent significantly more as a result of the reduced shopping frequency (i.e., the secure-insecure subgroup ß = -0.18, P < .01; the secure-secure subgroup ß = -0.35, P < .01). The increase in food expenditure was insignificant for people who were food-insecure before the pandemic (i.e., the insecure-insecure subgroup, ß = -0.01, P > .05; the insecure-secure subgroup, ß = -0.11, P > .05). CONCLUSIONS: The study reports that in general people reduced the frequency of grocery shopping trips to avoid epidemic exposure while increasing the food expenditure per trip. The increase in food expenditure was not statistically significant among the food-insecure populations likely due to their budget constraints.


Subject(s)
COVID-19/epidemiology , Consumer Behavior , Food Supply/statistics & numerical data , Pandemics , Adult , Aged , Aged, 80 and over , COVID-19/psychology , Commerce , Cross-Sectional Studies , Disease Outbreaks , Food , Humans , Male , Middle Aged , Perception , SARS-CoV-2 , Surveys and Questionnaires , Young Adult
16.
Chinese Journal of Pharmacology and Toxicology ; 34(6):408-417, 2020.
Article in Chinese | Scopus | ID: covidwho-1134277

ABSTRACT

OBJECTIVE To establish an agile discovery method of drugs or natural products for epidemics (aCODE) for the development of anti-infectious disease drugs. METHODS Five infectious diseases (HIV infection, human influenza, Paramyxoviridae infections, bacterial infections and whooping cough) involving more than 40 drugs approved by the United States Food and Drug Administration (FDA) were selected. An experimental group and two negative control groups (A and B) for each disease were set up. The experimental group randomly selected (500 times) M FDA-approved indications as seed drugs for the disease, while negative control group A used all FDA-approved infectious drugs for non-current diseases instead of seed drugs, and negative control group B used all non-infectious disease drugs for non-infectious diseases instead of seed drugs. M ranged from 2 to 20, the target gene infor mation of the seed drug was input, and the feature vector of the seed drug set was calculated. Candi date compounds were predicted through similarity search of drug feature vectors. The size of the inter section between the predicted drug and the positive set of drugs approved by the FDA for the disease, and the significance of the intersection were calculated. After the establishment of the aCODE method, four drugs (lopinavir, ribavirin, ritonavir and chloroquine) were selected as seed drugs for COVID-19 to predict the composition of natural products. Using natural products with known anti-coronavirus activi ties as the verification set, the significance of the prediction results was calculated. RESULTS In the case of the five infectious diseases, the proportion of positive drugs in the results of prediction in the experimental group increased with the number of seed drugs, while the positive rate of the two negative control groups remained basically unchanged or somewhat trended down. The aCODE method, when applied to COVID-19 drug screening, could effectively predict drugs with potential anti-SARS-Cov-2 activity (P=0.0046). CONCLUSION With the aCODE method, the more the seed drugs, the more accu rate the characteristics of the disease-related gene modules calculated from this group of seed drugs, and the higher the proportion of positive drugs in the prediction result. This method may contribute to the discovery of drugs for COVID-19. © 2020 Chinese Journal of Pharmacology and Toxicology. All rights reserved.

17.
Zhongguo Huanjing Kexue/China Environmental Science ; 41(2):505-516, 2021.
Article in Chinese | Scopus | ID: covidwho-1130266

ABSTRACT

In order to evaluate the effect of air pollutions emission reduction in Beijing, Tianjin, Hebei and its surrounding 26 cities ("2 + 26" cities) from January to March in 2020 during the epidemic of COVID-19, the air quality model of nested air quality prediction modeling system (NAQPMS) was applied to conduct a few scenarios. The characteristics of air quality from January to March 2020, and during the periods before and after the epidemic of COVID-19 were investigated. The influences of meteorology, emergency emission reduction measures and social economic activities on ambient air quality as well as the uncertainties were elucidated and discussed. The results showed that the number of days achieving good and moderate air quality standard in "2+26" cities accounted for 59.6%, on average of 10.9% increase relative to the same period last year. The mean concentration of PM10, PM2.5, SO2, NO2, O3-8h-90 per and CO-95 per in "2 + 26" cities from January to March in 2020 were 108, 76, 14, 109, 36μg/m3, and 2.3mg/m3, respectively. During the epidemic period from January 24 to March 31, the concentrations of PM10, NO2, PM2.5, and CO decreased significantly compared with the period prior to the epidemic from January 1to 23. In contrast to January to March in 2019, the PM2.5 concentrations of the cities along the Yan mountain and Taihang mountain increased by 1%~8% in 2020. However, the model simulations revealed that the emergency emission reduction measures potentially avoided twice of the regional heavy air pollution events, resulting in the quarterly mean PM2.5 concentration in "2 + 26" cities reduced by 6 to 26μg/m3. Due to the influence of the Spring Festival holiday and epidemic, the traffic emissions were reduced substantially. In contrast, the emissions from the industry such as coking and thermal power did not show large variations, and the negative impact of loose coal combustion on ambient air quality may become even more severe. © 2021, Editorial Board of China Environmental Science. All right reserved.

19.
Chinese General Practice ; 23(9):1078-1082, 2020.
Article in Chinese | Scopus | ID: covidwho-833460

ABSTRACT

Background: The COVID-19 is characterized by a long incubation period, high contagion and general susceptibility. Due to lack of specific preventive measures and targeted drugs, it brings great panic to the society. All regions across China launched first-level responses to this public health emergency. Medical workers in the county stick to their post to save patients, among them frontline clinicians fighting against COVID-19 have great pressure caused by excess workload with a high risk of infection, whose psychological status should be concerned and intervened by relevant departments. Moreover, the survey of their psychological status may also provide a basis for the improvement of emergency plan and public health management. Objective: To investigate the experience and feelings of frontline clinicians fighting against COVID-19, providing a reference for the delivery of corresponding psychological intervention for this group and for epidemic control and prevention. Methods: A qualitative study using in-depth individual interviews and a phenomenology method was implemented between February 1 and 7, 2020.Participants were frontline clinicians fighting against COVID-19 from hospitals in some cities or provinces, China. The Colaizzi's method was adopted to analyze the interview results: and extract themes. Results Six themes were extracted: complex and diverse feelings (fear of infection, panic caused by the epidemic, anger and helplessness induced by noncooperation of some patients and residents, and self-accusation caused by non-efficient life saving efforts ), insufficient clinical experience, high work pressure, being disrespected and misunderstood by some patients and residents, sense of responsibility and duty to heal the wounded and rescue the dying, and insufficient self-protective materials. Conclusion In view of the feelings(fear of infection, panic caused by the epidemic, great work pressure and being disrespected and misunderstood by some patients and residents, and so on) of frontline clinicians fighting against COVID-19, administrative departments of hospitals should provide them with appropriate psychological guidance, humanistic care and sufficient self-protection materials, as well as intensive education on professional knowledge and emergency management of this disease. Copyright © 2020 by the Chinese General Practice.

20.
IEEE Engineering Management Review ; 2020.
Article in English | Scopus | ID: covidwho-832793

ABSTRACT

As one of the few operating retail sectors, the food retail industry is encountering unique challenges and opportunities during the 2019 Novel Coronavirus. The pandemic led to various transformations in the food retail industry, including changes in consumers perception and behavior. Although the pandemic has a situational nature, such transformations could have both temporary and long-lasting effects on reforms of the grocery retail industry. We examined consumers retail grocery shopping behaviors change during the pandemic using a survey among 2,500 U.S. adults. Survey results show that consumers now have higher expectations for in-store safety;they have reduced the frequency of store patronage, travel time, and in-store duration;they have shifted shopping schedule and shopping destinations;and they have spent more per shopping trip. The increased spending in-store also paralleled with the expanded transactions across various online grocery shopping platforms, which created a perfect competition in the emerging online grocery retail industry. Such perfect competition is unique in the overall monopoly ecommerce world and it creates new opportunities for platforms to reform and co-develop a sustainable online grocery retailing industry. We further came up with managerial implications in short- and long-term for the brick-and-mortar stores as well as online grocery vendors. IEEE

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