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2.
BJR Open ; 4(1):20210062, 2022.
Article in English | MEDLINE | ID: covidwho-2029763

ABSTRACT

Objective: To predict short-term outcomes in hospitalized COVID-19 patients using a model incorporating clinical variables with automated convolutional neural network (CNN) chest radiograph analysis. Methods: A retrospective single center study was performed on patients consecutively admitted with COVID-19 between March 14 and April 21 2020. Demographic, clinical and laboratory data were collected, and automated CNN scoring of the admission chest radiograph was performed. The two outcomes of disease progression were intubation or death within 7 days and death within 14 days following admission. Multiple imputation was performed for missing predictor variables and, for each imputed data set, a penalized logistic regression model was constructed to identify predictors and their functional relationship to each outcome. Cross-validated area under the characteristic (AUC) curves were estimated to quantify the discriminative ability of each model. Results: 801 patients (median age 59;interquartile range 46-73 years, 469 men) were evaluated. 36 patients were deceased and 207 were intubated at 7 days and 65 were deceased at 14 days. Cross-validated AUC values for predictive models were 0.82 (95% CI, 0.79-0.86) for death or intubation within 7 days and 0.82 (0.78-0.87) for death within 14 days. Automated CNN chest radiograph score was an important variable in predicting both outcomes. Conclusion: Automated CNN chest radiograph analysis, in combination with clinical variables, predicts short-term intubation and death in patients hospitalized for COVID-19 infection. Chest radiograph scoring of more severe disease was associated with a greater probability of adverse short-term outcome. Advances in knowledge: Model-based predictions of intubation and death in COVID-19 can be performed with high discriminative performance using admission clinical data and convolutional neural network-based scoring of chest radiograph severity.

3.
2022 International Conference on Blockchain Technology and Information Security, ICBCTIS 2022 ; : 246-254, 2022.
Article in English | Scopus | ID: covidwho-2029226

ABSTRACT

The COVID-19 pandemic has led to a worldwide surge in demand for masks, protective clothing, and other epidemic prevention materials. The lack of epidemic prevention materials has put the lives of frontline health care workers at serious risk. However, epidemic prevention materials are not being distributed fairly and efficiently. This, coupled with the occasional scramble for scarce materials, makes epidemic prevention materials scarcer. The traditional centralized donation model makes it difficult to obtain the demand for materials in a timely manner, and the existing blockchain-based donation systems have not improved the efficiency of material donation. Moreover, most of the donation systems do not consider privacy and security issues. In this paper, we propose a blockchain-based material donation platform designed and implemented through the Ethereum platform. We solve the difficulty of demand acquisition and improve the transparency of the donation process through blockchain;reduce the possibility of a second disaster and improve the efficiency of material distribution through smart contracts;and protect the privacy and security of the donation process through zero-knowledge proof. We validate the security and efficiency of the proposed epidemic donation platform. © 2022 IEEE.

4.
Frontiers in Public Health ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2022982

ABSTRACT

Network meta-analysis of deaths from various underlying diseases after COVID-19 infection. This study included more than 10 research centers with the same level of care. In total, 1,676 subjects were included in our study, including 1,122 men and 554 women, patients diagnosed with COVID-19, and combined with underlying diseases;provided data on the number of deaths from related diseases, such as hypertension, diabetes, heart disease, cerebrovascular disease, malignant tumor, chronic kidney disease, chronic liver disease, and respiratory disease. The comparison RR between hypertension and different diseases shows that it is (RR = 2.35, 95% CI: 1.47, 3.98) compared with diabetes, compared with coronary heart disease (RR = 2.57, 95% CI: 1.5, 4.4), compared with cerebrovascular disease (RR = 3.68, 95% CI: 1.87, 7.29), compared with malignant tumor (RR = 6.35, 95% CI: 3.45, 11.97), and compared with chronic kidney disease (RR = 5.53 95% CI: 3.04, 10.34), compared with chronic liver disease (RR = 15.51, 95% CI: 5.26, 50.98), compared with respiratory diseases (RR = 4.35, 95% CI: 2.37, 7.65), RR values are >1, which is statistically significant. The surface under the cumulative ranking curve (SUCRA) showed that the ranking of disease mortality from high to low was hypertension> diabetes> heart disease> cerebrovascular disease> respiratory disease> chronic kidney disease> malignant tumor> chronic liver disease. The study that hypertension, diabetes, and heart disease are the top three risk factors for patients infected with COVID-19, and management of these patients should be strengthened to improve the prognosis of patients. Ethical approval and patient consent are not required as this study is a meta-analysis based on published studies. The results of this network meta-analysis will be submitted to a peer-reviewed journal for the publication.

5.
Frontiers in Psychology ; 13:977609, 2022.
Article in English | MEDLINE | ID: covidwho-2022898

ABSTRACT

Since December 2019, the COVID-19 has continued to rage, and epidemic prevention policies have limited contact between individuals, which may has a great influence on the income of individuals, exacerbate anxiety and depression, and cause serious mental health problems. The current study aims to examine the association between income and mental health during the COVID-19 pandemic by using the data of 9,296 observations from the 2020 China Family Panel Studies. Employing ordinary least squares regression and two-stage least squares regression, we find the significant positive effect of income on Chinese mental health during this pandemic. In addition, the number of cigarettes smoked per day has significant negative effects on mental health. Education level'marriage and exercise frequency have significant positive correlation with mental health. Furthermore, the impact of income on individuals of different groups is heterogeneous during this pandemic. The impact of income for well-educated individuals is less strong than their less-educated counterparts. People who exercise regularly respond less strongly to changes in income than those who do not exercise. Finally, individuals' salary satisfaction and interpersonal relationship are shown to be the potential mechanism for the effect of income on Chinese mental health.

6.
Frontiers in Pharmacology ; 13:936925, 2022.
Article in English | MEDLINE | ID: covidwho-2022836

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) was declared a global pandemic in March 2020 by the World Health Organization (WHO). As of July 2, 2022, COVID-19 has caused more than 545 million infections and 6.3 million deaths worldwide, posing a significant threat to human health. Currently, there is still a lack of effective prevention and control strategies for the variation and transmission of SARS-CoV-2. Traditional Chinese medicine (TCM), which has a unique theoretical system, has treated various conditions for thousands of years. Importantly, recent studies have revealed that TCM contributed significantly to COVID-19. SanHanHuaShi (SHHS) granules, a Chinese herbal medicine, which has been included in Protocol for the Diagnosis and Treatment of Novel Coronavirus Disease 2019 (6th to 9th editions) issued by the National Health Commission of China and used to prevent and treat COVID-19 disease. A previous retrospective cohort study showed that SHHS could significantly reduce the severity of mild and moderate COVID-19. However, there is an absence of high-quality randomized controlled clinical studies to confirm the clinical effectiveness of SHHS. Therefore, a clinical study protocol and a statistical analysis plan were designed to investigate the efficacy and safety of SHHS for the prevention and treatment of COVID-19. This study will increase the integrity and data transparency of the clinical research process, which is of great significance for improving the practical application of SHHS granules in the future. Methods and analysis: The study was designed as a 7-day, randomized, parallel controlled, open-label, noninferiority clinical trial of positive drugs. A total of 240 patients with mild and moderate COVID-19 will be enrolled and randomly assigned to receive SanHanHuaShi granules or LianHuaQingWen granules treatment in a 1:1 ratio. Disease classification, vital signs, SARS-CoV-2 nucleic acid testing, symptoms, medications, adverse events, and safety evaluations will be recorded at each visit. The primary outcome will be the clinical symptom recovery rate. Secondary outcomes will include the recovery time of clinical symptoms, negative conversion time of SARS-CoV-2 nucleic acid test negative conversion rate, hospitalization time, antipyretic time, rate of conversion to severe patients, and time and rate of single symptom recovery. Adverse incidents and safety assessments will be documented. All data will be analyzed using a predetermined statistical analysis plan, including our method for imputation of missing data, primary and secondary outcome analyses, and safety outcomes. Discussion: The results of this study will provide robust evidence to confirm the effectiveness and safety of SHHS in the treatment of COVID-19. Clinical Trial Registration: http://www.chictr.org.cn. Trial number: ChiCTR2200058080. Registered on 29 March 2022.

7.
Frontiers in Bioengineering and Biotechnology ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2022647

ABSTRACT

Drug addiction is a serious problem globally, recently exacerbated by the COVID-19 pandemic. Glial cell-derived neurotrophic factor (GDNF) is considered a potentially effective strategy for the treatment of addiction. Previous animal experiments have proven that GDNF has a good therapeutic effect on drug addiction, but its clinical application is limited due to its poor blood-brain barrier (BBB) permeability. Low-frequency focused ultrasound, combined with microbubbles, is a non-invasive and reversible technique for locally-targeted BBB opening. In the present study, magnetic resonance imaging-guided low-frequency focused ultrasound, combined with GDNF microbubbles, was used to target BBB opening in the ventral tegmental area (VTA) region. The effects of GDNF on morphine-induced conditioned place preference (CPP) and acute withdrawal symptoms in rats after a partially opened BBB were evaluated by behavioral observation. Western blot was used to detect changes in tyrosine hydroxylase (TH) expression levels in the VTA region after different treatments, and high performance liquid chromatography was used to detect the changes in monoamine neurotransmitter content. The results showed that ultrasound combined with GDNF microbubbles targeted and opened the BBB in the VTA region, and significantly increased GDNF content, destroyed morphine-induced CPP, and reduced the withdrawal symptoms of morphine addiction in rats. Furthermore, the up-regulation of TH expression and the increase of norepinephrine and dopamine content induced by morphine were significantly reversed, and the increase of 5-hydroxytryptamine content was partially reversed. Therefore, ultrasound combined with GDNF microbubbles to target and open the BBB can effectively increase the content of central GDNF, thus playing a therapeutic role in morphine addiction. Our study provides a new approach to locally open the BBB and target delivery of neurotrophic factors, such as GDNF, to treat brain diseases like addiction.

8.
J Biomed Sci ; 29(1):68, 2022.
Article in English | PubMed | ID: covidwho-2021289

ABSTRACT

The novel coronavirus disease (COVID-19) pandemic remains a global public health crisis, presenting a broad range of challenges. To help address some of the main problems, the scientific community has designed vaccines, diagnostic tools and therapeutics for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The rapid pace of technology development, especially with regard to vaccines, represents a stunning and historic scientific achievement. Nevertheless, many challenges remain to be overcome, such as improving vaccine and drug treatment efficacies for emergent mutant strains of SARS-CoV-2. Outbreaks of more infectious variants continue to diminish the utility of available vaccines and drugs. Thus, the effectiveness of vaccines and drugs against the most current variants is a primary consideration in the continual analyses of clinical data that supports updated regulatory decisions. The first two vaccines granted Emergency Use Authorizations (EUAs), BNT162b2 and mRNA-1273, still show more than 60% protection efficacy against the most widespread current SARS-CoV-2 variant, Omicron. This variant carries more than 30 mutations in the spike protein, which has largely abrogated the neutralizing effects of therapeutic antibodies. Fortunately, some neutralizing antibodies and antiviral COVID-19 drugs treatments have shown continued clinical benefits. In this review, we provide a framework for understanding the ongoing development efforts for different types of vaccines and therapeutics, including small molecule and antibody drugs. The ripple effects of newly emergent variants, including updates to vaccines and drug repurposing efforts, are summarized. In addition, we summarize the clinical trials supporting the development and distribution of vaccines, small molecule drugs, and therapeutic antibodies with broad-spectrum activity against SARS-CoV-2 strains.

9.
2022 International Conference on Cloud Computing, Internet of Things, and Computer Applications, CICA 2022 ; 12303, 2022.
Article in English | Scopus | ID: covidwho-2019669

ABSTRACT

As one of the main means of transportation for citizens in Wuhan, urban rail transit has assumed the dual responsibility of ensuring the travel needs of citizens and blocking the spread of the epidemic in the context of COVID-19. Taking the security check space of Wuhan subway Street entrance station as an example, the paper aims at putting forward the optimization strategy of security space design to solve the obstruction problem caused by the excessive flow of subway stations at present. The paper takes the COVID-19 prevention and control requirements in Wuhan into consideration, uses intelligent technology, combines the construction of social force model to conduct pedestrian simulation, and applies simulation variable analysis. The findings indicate that the optimization strategy of security space design effectively shortens the arrival time and effectively controls the flow of people. It is expected to provide some reference and research basis for the design and optimization of security inspection space of subway transportation system in the future. © 2022 SPIE.

10.
Physical Chemistry Chemical Physics ; 09:09, 2022.
Article in English | MEDLINE | ID: covidwho-2016863

ABSTRACT

The pneumonia outbreak caused by the SARS-CoV-2 virus poses a serious threat to human health and the world economy. The development of safe and highly effective antiviral drugs is of great significance for the treatment of COVID-19. The main protease (Mpro) of SARS-CoV-2 is a key enzyme for viral replication and transcription and has no homolog in humans. Therefore, the Mpro is an ideal target for the design of drugs against COVID-19. Insights into the inhibitor-Mpro binding mechanism and conformational changes of the Mpro are essential for the design of potent drugs that target the Mpro. In this study, we analyzed the conformational changes of the Mpro that are induced by the binding of three inhibitors, YTV, YSP and YU4, using multiple replica accelerated molecular dynamics (MR-aMD) simulations, dynamic cross-correlation map (DCCM) calculations, principal component analysis (PCA), and free energy landscape (FEL) analysis. The results from DCCM calculations and PCA show that the binding of inhibitors significantly affects the kinetic behavior of the Mpro and induces a conformational rearrangement of the Mpro. The binding ability and binding mechanism of YTV, YSP and YU4 to the Mpro were investigated using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. The results indicate that substitution of the tert-butanol group by methylbenzene and trifluoromethyl groups enhances the binding ability of YSP and YU4 to the Mpro compared with YTV;moreover, massive hydrophobic interactions are detected between the inhibitors and the Mpro. Meanwhile, T25, L27, H41, M49, N142, G143, C145, M165, E166 and Q189 are identified as the key residues for inhibitor-Mpro interactions using residue-based free energy decomposition calculations, which can be employed as efficient targets in the design of drugs that inhibit the activity of the Mpro.

11.
World Wide Web ; : 1-18, 2022.
Article in English | MEDLINE | ID: covidwho-2014367

ABSTRACT

Medical reports have significant clinical value to radiologists and specialists, especially during a pandemic like COVID. However, beyond the common difficulties faced in the natural image captioning, medical report generation specifically requires the model to describe a medical image with a fine-grained and semantic-coherence paragraph that should satisfy both medical commonsense and logic. Previous works generally extract the global image features and attempt to generate a paragraph that is similar to referenced reports;however, this approach has two limitations. Firstly, the regions of primary interest to radiologists are usually located in a small area of the global image, meaning that the remainder parts of the image could be considered as irrelevant noise in the training procedure. Secondly, there are many similar sentences used in each medical report to describe the normal regions of the image, which causes serious data bias. This deviation is likely to teach models to generate these inessential sentences on a regular basis. To address these problems, we propose an Auxiliary Signal-Guided Knowledge Encoder-Decoder (ASGK) to mimic radiologists' working patterns. Specifically, the auxiliary patches are explored to expand the widely used visual patch features before fed to the Transformer encoder, while the external linguistic signals help the decoder better master prior knowledge during the pre-training process. Our approach performs well on common benchmarks, including CX-CHR, IU X-Ray, and COVID-19 CT Report dataset (COV-CTR), demonstrating combining auxiliary signals with transformer architecture can bring a significant improvement in terms of medical report generation. The experimental results confirm that auxiliary signals driven Transformer-based models are with solid capabilities to outperform previous approaches on both medical terminology classification and paragraph generation metrics.

12.
Journal of Medical Virology ; 02:02, 2022.
Article in English | MEDLINE | ID: covidwho-2013638

ABSTRACT

Prazuck et al. evaluated an innovative two-step self-test, the AAZ COVID-VIRO ALL IN R, switching from the classic nasal swab to a nasal sponge. We notice that the agreement between COVID-VIRO ALL IN R and RT-PCR was not assessed. Although the authors had evaluated the overall agreement between COVID-VIRO ALL IN R and RT-PCR, applying overall agreement to evaluate intra-rater consistency is not always appropriate. Our second concern is about the precise number of patients. Thinking the exact number of patients is a prerequisite for statistical analysis, we would be grateful if the authors could explain their data in detail and clarify the misunderstanding. This article is protected by copyright. All rights reserved.

13.
Innovation in Aging ; 5:735-736, 2021.
Article in English | Web of Science | ID: covidwho-2012744
14.
Frontiers in Cellular and Infection Microbiology ; 12, 2022.
Article in English | EMBASE | ID: covidwho-2009847

ABSTRACT

Fungal infections are global public health problems and can lead to substantial human morbidity and mortality. Current antifungal therapy is not satisfactory, especially for invasive, life-threatening fungal infections. Modulating the antifungal capacity of the host immune system is a feasible way to combat fungal infections. Neutrophils are key components of the innate immune system that resist fungal pathogens by releasing reticular extracellular structures called neutrophil extracellular traps (NETs). When compared with phagocytosis and oxidative burst, NETs show better capability in terms of trapping large pathogens, such as fungi. This review will summarize interactions between fungal pathogens and NETs. Molecular mechanisms of fungi-induced NETs formation and defensive strategies used by fungi are also discussed.

15.
Nat Commun ; 13, 2022.
Article in English | PMC | ID: covidwho-2008278

ABSTRACT

Preliminary evidence from China and other countries has suggested that coronavirus disease 2019 (COVID-19) mitigation measures have caused a decline in preterm births, but evidence is conflicting. Utilising a national representative data of 11,714,947 pregnant women in China, we explored the immediate changes in preterm birth rates during the COVID-19 mitigation period using an interrupted-time-series analysis. We defined the period prior to February 1, 2020 as the baseline, followed by the COVID-19 mitigation stage. In the first month of the COVID-19 mitigation, a significant absolute decrease in preterm birth rates of 0.68% (95%CI:−1.10% to −0.26%) in singleton, and of 2.80% (95%CI:−4.51% to −1.09%) in multiple births was noted. This immediate decline in Wuhan was greater than that at the national level among singleton births [−2.21% (95%CI:−4.09% to −0.34% vs. −0.68%)]. Here we report an immediate impact of COVID-19 mitigation measures on preterm birth in China.

17.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2005715

ABSTRACT

Background: To direct limited specialized palliative care resources to patients in greatest need, we developed STEP (Symptom screening with Targeted Early Palliative care). STEP entails symptom screening (ESAS-r) at each oncology clinic visit and triggered alerts (for moderate-high physical and psychological symptoms) to a nurse who calls the patient to offer a palliative care clinic (PCC) visit. We conducted a phase III RCT to assess the impact of STEP versus usual care on quality of life and other patient-reported outcomes (PROs). Methods: Adults with advanced cancer were recruited from medical oncology clinics at the Princess Margaret Cancer Centre, Toronto, Canada. Consenting patients with oncologist-assessed ECOG 0-2 and estimated survival of 6-36 months were enrolled and block randomized (stratified by tumour site and symptom severity) to STEP or usual care. Participants completed measures of quality of life (FACT-G7), depression (PHQ-9), symptom control (ESASr-CS), and satisfaction with care (FAMCARE-P16) at baseline, 2, 4 and 6 months. The primary outcome was FACT-G7 at 6 months, with a planned sample size of 261/arm. Results: From 8/2019 to 3/2020, 69 patients were enrolled: 33 randomized to STEP and 36 to usual care. The trial was then halted permanently due to the COVID-19 pandemic, owing to substantial changes to elements of STEP (shift to virtual symptom screening and palliative care) and usual care (shift to virtual oncology care). Median age was 64 years (range 25-87) and 62% (43/69) were women;study arms were balanced at baseline except gender, with more women randomized to STEP. Within the STEP arm, 20 (61%) participants triggered a nurse's call to offer a PCC visit, of whom 13 attended the clinic at least once. All outcomes tended to be better in the STEP arm compared to usual care, particularly depression and satisfaction with care at 6 months;however, results were not statistically significant (Table). Conclusions: STEP holds promise for improving quality of life and other PROs in patients with advanced cancer and effectively directing early palliative care towards those who need it most. In response to the pandemic, an online version of STEP has been developed and a further trial is in progress.

18.
Asia Pacific Journal of Tourism Research ; 27(6):652-670, 2022.
Article in English | Web of Science | ID: covidwho-2004891

ABSTRACT

Leadership and crisis are closely intertwined, yet studies of leadership during crisis remain scarce. The 2020 Covid-19 outbreak offers an ideal context to examine leaders' roles during severe crises. Grounded in the theoretical framework of transformative leadership and based on a study of four cases in rural Ningbo, Zhejiang Province, the study examines rural tourism enterprises' post-pandemic recovery to identify how leadership navigated organizations through the recovery process. The study demonstrates that each case displays components of transformational leadership that facilitated businesses' recovery. Creativity appears especially important in promoting effective leadership amid crisis and uncertainty. Theoretical and practical implications are discussed.

19.
Psychosomatic Medicine ; 84(5):A12, 2022.
Article in English | EMBASE | ID: covidwho-2003263

ABSTRACT

Background: When the WHO declared COVID-19 a global pandemic on March 11, 2020, stay-at-home orders and business closures were imposed to contain viral spread. Accumulating evidence suggests that these societal disruptions caused abrupt changes in important health behaviors such as physical activity, but most work to date has used self-report measures. Longitudinal studies collecting objective measures of activity and sleep behavior and heart rate before and after the pandemic could shed light on potential health implications of the ongoing pandemic and associated social distancing measures. Objective: To determine whether significant within-person changes in objective heart rate, sleep, and physical activity occurred from pre- to post-COVID pandemic. Methods: Adult smartphone users were recruited from an online registry. 22 participants (M 47 years old, range 20-72;76% female;91% White;55% with at least one chronic medical condition) provided access to their Fitbit data and had at least one week of pre-COVID (March 11, 2019 to March 10, 2020;M = 256 days of data, range 25-366 days) and post-COVID (March 11, 2020 to December 31, 2020;M = 231 days of data, range 107-294 days) Fitbit data. Results: Paired t-tests revealed significant decreases in mean heart rate (77 to 75 bpm;t(18) = 2.91, p < .01), step counts (7946 to 6969 steps/day;t(21) = 2.72, p = .01), and total active time (185 to 165 minutes/day;t(21) = 3.02, p < .001) and significant increases in total sedentary time (766 to 781 minutes/day;t(21) =-2.88, p < .01) from pre- to post-COVID but no significant changes in Fitbit-assessed sleep time, latency, or efficiency. Conclusions: These prospective sensor data captured before and after the pandemic contribute to our understanding of how COVID-19 has affected physical activity and heart rate. Findings suggest that adults became less physically active and more sedentary after the pandemic relative to the year prior to COVID-19 but that sleep behaviors remained relatively stable. Although this is a small nonrepresentative sample, these longitudinal objective behavioral data corroborate larger self-report studies. Future analyses will examine trajectories of activity change over the course of the pandemic and characteristics of participants who maintained or increased activity levels despite social distancing mandates.

20.
PLoS ONE [Electronic Resource] ; 17(8):e0269200, 2022.
Article in English | MEDLINE | ID: covidwho-2002294

ABSTRACT

BACKGROUND: Vaccination is indeed one of the interventional strategies available to combat coronavirus disease (COVID-19). This study emphasizes the relevance of citizens' acceptance of the COVID-19 vaccine in assisting global recovery from the pandemic and aiding the tourism industries to return to normalcy. This study further presented the impact of COVID-19 on the tourism industry in China. Also, the study confirmed the past performance of tourism in China to the current tourism-related COVID-19 effects from a global perspective by employing Australia's outbound tourism data from 2008 to 2020 on top 6 destinations, including China, Indonesia, New Zealand, Thailand, the United Kingdom, and the United States. METHODS: Jeffrey's Amazing Statistical Program (JASP) was used to analyze this study. The JASP statistical software was employed to accurately analyze the vaccines administered in China from December 15, 2020, to March 28, 2021. RESULTS: The study results demonstrate an overwhelming acceptance of vaccines in China which will positively and significantly impact the globe's travel and tourism industries. Also, the study findings indicated that industries in tourism are hopeful of regaining the past losses. Further, the study results showed an enormous decline in death and new cases. CONCLUSION: Vaccine acceptance is relevant for the eradication of the COVID-19 pandemic. Therefore, neighborhood and individual-level acceptance of the vaccine will help reduce the challenges facing the tourism industries and the world. The researchers recommend that authorities should strictly check the vaccination certificates of visitors. Furthermore, hoteliers should put adequate measures to monitor all visitors who visit the various tourist destinations.

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