Impact and Recovery of Coastal Tourism Amid COVID-19: Tourism Flow Networks in Indonesia

This study aims to explore tourism changes in coastal tourism destinations before and during the COVID-19 pandemic from the perspective of regional resilience. A mixed method of a social network and spatial analysis was used to evaluate inbound tourists' geotagged photos of Indonesia on Flickr from 2018–2022 as metadata. The DBSCAN algorithm and Markov chains were used to comprehensively analyze the hotspot areas and the patterns of tourism movement trajectories amid a complicated recovery. The results demonstrate that: (1) The distribution of geotagged photos before and during the pandemic generally exhibited stage and regional unevenness. The main clusters were Java and the Nusa Tenggara Islands, with the rest displaying a scattered distribution. (2) The tourism flow network was unevenly distributed, and the nodes had obvious core and edge areas. Owing to the crisis, the tourism flow network realized a change in form from network to line and point. (3) Its impact on Indonesian inbound tourism may persist in the short term, and the volatility of national anti-pandemic policies influences the resilience of tourism flow during COVID-19. The dominance of the core nodes highlights the network's resistance to disruptions due to the prominence of the location of network connections during the pandemic, and marginal nodes reflect the vulnerability to pandemic shocks owing to the hypocentricity of the nodes and the thinness of the connections within and outside the islands. These results provide marketing and promotion policies for the sustainable development of coastal areas.

The impact of CoronaVac on the neutralization breadth and magnitude of the antibody response to SARS-CoV-2 viruses

Although immune response enhancement has been reported after primary and booster vaccines of CoronaVac, neutralization breadth of SARS-CoV-2 variants is still unclear. In the present study, we examined the neutralization magnitude and breadth of SARS-CoV-2 variants including Beta (B.1.351), Delta (B.1.617.2) and Omicron (B.1.1.529) in 33 convalescent COVID-19 patients and a cohort of 55 medical staff receiving primary CoronaVac vaccines and an additional homologous booster dose. Results showed that, as compared with the two-dose primary vaccination, the homologous booster dose achieved 2.24-, 3.98-, 4.58- and 2.90-fold increase in neutralization titer against wild-type, Beta, Delta, and Omicron, respectively. After booster dose, neutralization titer reduction for variants was less than that after the primary vaccine or that for convalescents. The proportion of recipients able to neutralize 2 or more variants increased from 36.36% post the primary vaccination to 87.27% after the booster. Significant increase in neutralization breadth of 1.24 (95% confidence interval (CI), 0.89–1.59) variants was associated with a log10 increase in neutralization titer against the wild-type. In addition, anti-RBD IgG level was identified as an excellent surrogate for positive neutralization of SARS-CoV-2 and neutralization breadth of variants. These findings highlight the value of an additional homologous CoronaVac dose in broadening the cross-neutralization against SARS-CoV-2 variants, and are critical for informing the booster dose vaccination efforts.

Predicting the Hate: A GSTM Model based on COVID-19 Hate Speech Datasets

COVID-19 crisis has been accompanied by copious hate speeches widespread on social media. It reinforces the fragmentation of the world, resulting in more significant racial discrimination and distrust between people, leading to crimes, and injuring individuals spiritually or physically. Hate speech is hard to crack for a global recovery in the post-epidemic era. Conducting with Twitter datasets, this paper aims to find the key indicators that influence the trend of hate speech, then builds a Gaussian Spatio-Temporal Mixture (GSTM) model for trends prediction based on the pre-analysis. Findings show that in the early period, the participation of influential users is closely related to the emergence of sentiment peaks, and the interval time is around one week. After hate speech waves up, the indicator of total exposure becomes more critical, suggesting that grass-root release influences at this stage. Compared with three classical time-series predicting models, the GSTM model shows better peak prediction ability and lower residual mean. This work enriches the approaches of predicting unknown but foreseeable hate speeches accompanied by future pandemics.

Impact of the COVID-19 pandemic on career intention amongst undergraduate medical students: a single-centre cross-sectional study conducted in Hubei Province.

BACKGROUND: Undergraduate medical (UM) students faced the difficulties inherent in medical careers due to the coronavirus (COVID-19) outbreak. Thus, imperative containment measures might affect UM students' career intentions. Information on the factors that may be associated with these students' career change intentions is limited. METHODS: We conducted a cross-sectional survey in August 2020 to investigate the impact of the COVID-19 pandemic on career intention and the associated factors in UM students. Univariate analyses and logistic regression analysis were performed to identify said factors. RESULTS: A total of 2040 medical students from the Hubei University of Medicine were surveyed. Univariate analyses showed that grade, attitude towards healthcare, and the degree of the COVID-19 pandemic's impact on the students' lives were associated with changes in career choice (P<0.05). Logistic regression analysis showed that Grade 2, Grade 5, attitude towards a medical career, and having relatives with a medical background were associated with changes in career choice. The degree of the COVID-19 pandemic's impact was a common and significant factor associated with career preference, career perspective, and ideal workplace. CONCLUSIONS: Changes in career intentions were particularly influenced by grade, attitude towards being a health worker, and the degree of COVID-19's impact on the participants' lives. Treating large-scale public health emergencies rationally, setting up correct views of occupation choice, and building reasonable career planning may reduce the loss of medical talent.

Social Group Differences in the Exposure Risk of COVID-19: A Case Study in Beijing, China.

Taking Beijing as a case, this paper conducted a survey to collect the characteristics of residents' daily activities, including the mode of frequency and duration of travel, the type and environment of activities, and the duration and frequency of activities. We calculated the COVID-19 exposure risk of residents in different activities based on the exposure risk formula; the influencing factors of residents' exposure risk were analyzed by regression analysis. The variance of residents' COVID-19 exposure risk was calculated by coefficient of variation. The main conclusions are as follows: (1) There are differences in activity types of COVID-19 exposure risk, which are survival activity, daily activity and leisure activity from high to low. (2) There are differences in populations of COVID-19 exposure risk. Education level, occupation and income are the main factors affecting residents' COVID-19 exposure risk. (3) There is internal inequity in the risk of COVID-19 exposure. The exposure risk was higher on work days than on rest days. Health inequities at work are highest on both work days and rest days. Among the different population characteristics, male, 31-40 years old, married, with a high school education, income level of 20,001-25,000 yuan, with a non-local rural hukou, rental housing, farmers, three generations or more living together have a greater degree of COVID-19 exposure risk.

Right Ventricle Dilation Detected on Point-of-Care Ultrasound Is a Predictor of Poor Outcomes in Critically Ill Patients With COVID-19.

BACKGROUND: During the COVID-19 pandemic, the need for judicious use of diagnostic tests and to limit personnel exposure has led to increased use and dependence on point-of-care ultrasound (POCUS) examinations. We reviewed POCUS findings in patients admitted to the intensive care unit (ICU) for acute respiratory failure with COVID-19 and correlated the findings to severity of illness and 30-day outcomes. METHODS: Patients admitted to the ICU in March and April 2020 were reviewed for inclusion (acute hypoxemic respiratory failure secondary to COVID-19 pneumonia; documentation of POCUS findings). RESULTS: Forty-three patients met inclusion criteria. B lines and pleural thickening were associated with a lower PaO2/FiO2 by 71 (P = .005; adjusted R 2 = 0.24). Right ventricle (RV) dilation was more common in patients with 30-day mortality (P = .02) and was a predictor of mortality when adjusted for hypertension, diabetes mellitus, and age (odds ratio, 12.0; P = .048). All patients with RV dilation had bilateral B lines with pleural irregularities. CONCLUSIONS: Although lung ultrasound abnormalities are prevalent in patients with severe disease, RV involvement seems to be predictive of outcomes. Further studies are needed to discern the etiology and pathophysiology of RV dilation in COVID-19.

Study on mechanism of qufeidu no.1 prescription in treatment of corona virus disease 2019 based on network pharmacology

Objective: To explore the material basis and potential mechanism of Qufeidu No.1 Prescription in the treatment of corona virus disease 2019 (COVID-19) by network pharmacology and molecular docking technology.

A highly sensitive stretchable strain sensor based on multi-functionalized fabric for respiration monitoring and identification

Wearable strain sensors have generated considerable recent research interest due to their huge potential in the real-time detection of human body deformation. State-of-the-art strain sensors are normally fabricated through conductive networks with a single sensing element, which always faces the challenge of either limited stretchability or inferior quality in sensitivity. In this work, we report a highly sensitive strain sensor based on a multi-functionalized fabric through carbonization and polymer-assisted copper deposition. The sensor shows high sensitivity (Gauge factor∼3557.6 in the strain range from 0 to 48%), and outstanding stretchability up to the strain of 300%, which is capable of detecting different types of deformation of the human body. By integrating the high-performance sensor with a deep learning network, we demonstrate a high accuracy of respiration monitoring and emergency alarm system, showing the enormous application potential of the sensor in personal and public healthcare.

A Network Pharmacology Study to Uncover the Multiple Molecular Mechanism of the Chinese Patent Medicine Toujiequwen Granules in the Treatment of Corona Virus Disease 2019 (COVID-19).

Since the outbreak of the novel corona virus disease 2019 (COVID-19) at the end of 2019, specific antiviral drugs have been lacking. A Chinese patent medicine Toujiequwen granules has been promoted in the treatment of COVID-19. The present study was designed to reveal the molecular mechanism of Toujiequwen granules against COVID-19. A network pharmacological method was applied to screen the main active ingredients of Toujiequwen granules. Network analysis of 149 active ingredients and 330 drug targets showed the most active ingredient interacting with many drug targets is quercetin. Drug targets most affected by the active ingredients were PTGS2, PTGS1, and DPP4. Drug target disease enrichment analysis showed drug targets were significantly enriched in cardiovascular diseases and digestive tract diseases. An "active ingredient-target-disease" network showed that 57 active ingredients from Toujiequwen granules interacted with 15 key targets of COVID-19. There were 53 ingredients that could act on DPP4, suggesting that DPP4 may become a potential new key target for the treatment of COVID-19. GO analysis results showed that key targets were mainly enriched in the cellular response to lipopolysaccharide, cytokine activity and other functions. KEGG analysis showed they were mainly concentrated in viral protein interaction with cytokine and cytokine receptors and endocrine resistance pathway. The evidence suggests that Toujiequwen granules might play an effective role by improving the symptoms of underlying diseases in patients with COVID-19 and multi-target interventions against multiple signaling pathways related to the pathogenesis of COVID-19.

Human Identical Sequences of SARS-CoV-2 Promote Clinical Progression of COVID-19 by Upregulating Hyaluronan via NamiRNA-Enhancer Network (preprint)

The COVID-19 pandemic is a widespread and deadly public health crisis. The pathogen SARS-CoV-2 replicates in the lower respiratory tract and causes fatal pneumonia. Although tremendous efforts have been put into investigating the pathogeny of SARS-CoV-2, the underlying mechanism of how SARS-CoV-2 interacts with its host is largely unexplored. Here, by comparing the genomic sequences of SARS-CoV-2 and human, we identified five fully conserved elements in SARS-CoV-2 genome, which were termed as "human identical sequences (HIS)". HIS are also recognized in both SARS-CoV and MERS-CoV genome. Meanwhile, HIS-SARS-CoV-2 are highly conserved in the primate. Mechanically, HIS-SARS-CoV-2 RNA directly binds to the targeted loci in human genome and further interacts with host enhancers to activate the expression of adjacent and distant genes, including cytokines gene and angiotensin converting enzyme II (ACE2), a well-known cell entry receptor of SARS-CoV-2, and hyaluronan synthase 2 (HAS2), which further increases hyaluronan formation. Noteworthily, hyaluronan level in plasma of COVID-19 patients is tightly correlated with severity and high risk for acute respiratory distress syndrome (ARDS) and may act as a predictor for the progression of COVID-19. HIS antagomirs, which downregulate hyaluronan level effectively, and 4-Methylumbelliferone (MU), an inhibitor of hyaluronan synthesis, are potential drugs to relieve the ARDS related ground-glass pattern in lung for COVID-19 treatment. Our results revealed that unprecedented HIS elements of SARS-CoV-2 contribute to the cytokine storm and ARDS in COVID-19 patients. Thus, blocking HIS-involved activating processes or hyaluronan synthesis directly by 4-MU may be effective strategies to alleviate COVID-19 progression.

Reanalysis of MERS, SARS and COVID-19 Infection Datasets using VirOmics Playground Reveals Common Patterns in Gene and Protein Expression (preprint)

Three lethal lower respiratory tract coronavirus epidemics have occurred over the past 20 years. This coincided with major developments in genome-wide gene and protein expression analysis, resulting in a wealth of datasets in the public domain. Seven such in vitro studies were selected for comparative bioinformatic analysis through the VirOmics Playground, a user-friendly visualisation and exploration platform we recently developed. Despite the heterogeneous nature of the data sets, several commonalities could be observed across studies and species. Differences, on the other hand, reflected not only variations between species, but also other experimental variables, such as cell lines used for the experiments, infection protocols and potential discrepancies between transcriptome and proteome data. The results presented here are available online and can be replicated through the VirOmics Playground.

Nitazoxanide and JIB-04 have broad-spectrum antiviral activity and inhibit SARS-CoV-2 replication in cell culture and coronavirus pathogenesis in a pig model (preprint)

Pathogenic coronaviruses represent a major threat to global public health. Here, using a recombinant reporter virus-based compound screening approach, we identified several small-molecule inhibitors that potently block the replication of the newly emerged severe acute respiratory syndrome virus 2 (SARS-CoV-2). Two compounds, nitazoxanide and JIB-04 inhibited SARS-CoV-2 replication in Vero E6 cells with an EC50 of 4.90 M and 0.69 M, respectively, with specificity indices of greater than 150. Both inhibitors had in vitro antiviral activity in multiple cell types against some DNA and RNA viruses, including porcine transmissible gastroenteritis virus. In an in vivo porcine model of coronavirus infection, administration of JIB-04 reduced virus infection and associated tissue pathology, which resulted in improved body weight gain and survival. These results highlight the potential utility of nitazoxanide and JIB-04 as antiviral agents against SARS-CoV-2 and other viral pathogens.

Coping Abilities of Nursing Graduates Under Public Health Emergency (COVID-19): A Cross-Sectional Study (preprint)

Background: Public health emergencies are serious social problems, threatening people's lives, causing considerable economic losses, and related to all mankind life and health and safety. Nurses are essential in the fight against the public health emergency, corona virus disease 2019 (COVID-19). Nursing graduates are considered as backup health care providers for licensed nurses, the coping abilities and crisis management of nursing students at present deserve attention all around the world. Methods: 2035 graduating nursing graduates were invited to participate in mobile phone app-based survey from Feb 6 to 20, 2020. The demographic items, psychological and behavioral responses, and the coping abilities were conducted. Multiple linear regression was used to identify the independent factors to nursing graduates’ coping abilities under COVID-19.Results: 1992 submitted were valid. Multiple linear regression analysis showed that Confidence to overcome difficulties, Optimism, Active coping, Help seeking and Practice hospital as designated treatment unit were independently associated with the positive coping of graduates. Fear of COVID-19, Optimism, Avoidance, Help seeking and Severity of epidemic around were independently associated with the negative coping of graduates.

Discovery of Synergistic and Antagonistic Drug Combinations against SARS-CoV-2 In Vitro (preprint)

COVID-19 is undoubtedly the most impactful viral disease of the current century, afflicting millions worldwide. As yet, there is not an approved vaccine, as well as limited options from existing drugs for treating this disease. We hypothesized that combining drugs with independent mechanisms of action could result in synergy against SARS-CoV-2. Using in silico approaches, we prioritized 73 combinations of 32 drugs with potential activity against SARS-CoV-2 and then tested them in vitro. Overall, we identified 16 synergistic and 8 antagonistic combinations, 4 of which were both synergistic and antagonistic in a dose-dependent manner. Among the 16 synergistic cases, combinations of nitazoxanide with three other compounds (remdesivir, amodiaquine and umifenovir) were the most notable, all exhibiting significant synergy against SARS-CoV-2. The combination of nitazoxanide, an FDA-approved drug, and remdesivir, FDA emergency use authorization for the treatment of COVID-19, demonstrate a strong synergistic interaction. Notably, the combination of remdesivir and hydroxychloroquine demonstrated strong antagonism. Overall, our results emphasize the importance of both drug repurposing and preclinical testing of drug combinations for potential therapeutic use against SARS-CoV-2 infections.

An OpenData portal to share COVID-19 drug repurposing data in real time (preprint)

The National Center for Advancing Translational Sciences (NCATS) has developed an online open science data portal for its COVID-19 drug repurposing campaign - named OpenData - with the goal of making data across a range of SARS-CoV-2 related assays available in real-time. The assays developed cover a wide spectrum of the SARS-CoV-2 life cycle, including both viral and human (host) targets. In total, over 10,000 compounds are being tested in full concentration-response ranges from across multiple annotated small molecule libraries, including approved drug, repurposing candidates and experimental therapeutics designed to modulate a wide range of cellular targets. The goal is to support research scientists, clinical investigators and public health officials through open data sharing and analysis tools to expedite the development of SARS-CoV-2 interventions, and to prioritize promising compounds and repurposed drugs for further development in treating COVID-19.

Interpretable Artificial Intelligence for COVID-19 Diagnosis from Chest CT Reveals Specificity of Ground-Glass Opacities (preprint)

Background The use of CT imaging enhanced by artificial intelligence to effectively diagnose COVID-19, instead of or in addition to reverse transcription-polymerase chain reaction (RT-PCR), can improve widespread COVID-19 detection and resource allocation. Methods 904 axial lung window CT slices from 338 patients in 17 countries were collected and labeled. The data included 606 images from COVID-19 positive patients (confirmed via RT-PCR), 224 images of a variety of other pulmonary diseases including viral pneumonias, and 74 images of normal patients. We developed, trained, validated, and tested an object detection model which detects features in three categories: ground-glass opacities (GGOs) for COVID-19, GGOs for non-COVID-19 diseases, and features that are inconsistent with a COVID-19 diagnosis. These collected features are passed into an interpretable decision tree model to make a suggested diagnosis. Results On an independent test of 219 images from COVID-19 positive, a variety of pneumonia, and healthy patients, the model predicted COVID-19 diagnoses with an accuracy of 96.80 % (95% confidence interval [CI], 96.75 to 96.86) , AUC-ROC of 0.9664 (95% CI, 0.9659 to 0.9671) , sensitivity of 98.33% (95% CI, 98.29 to 98.40) , precision of 95.93% (95% CI, 95.83 to 95.99), and specificity of 94.95% (95% CI, 94.84 to 95.05). On an independent test of 34 images from asymptomatic COVID-19 positive patients, our model achieved an accuracy of 97.06% (95% CI, 96.81 to 97.06) and a sensitivity of 96.97% (95% CI, 96.71 to 96.97). Similarly high performance was also obtained for out-of-sample countries, and no significant performance difference was obtained between genders. Conclusion We present an interpretable artificial intelligence CT analysis tool to diagnose COVID-19 in both symptomatic and asymptomatic patients. Further, our model is able to differentiate COVID-19 GGOs from similar pathologies suggesting that GGOs can be disease-specific.

Detection of a novel coronavirus (SARS-CoV-2) by real-time reverse transcription-polymerase chain reaction, China, 2020 (preprint)

Background: During the outbreak of unexplained pneumonia in the city of Wuhan in the late December, 2019, a novel coronavirus named SARS-CoV-2 was identified as the cause of this outbreak.Methods: A real-time polymerase chain reaction, which targets the orf1ab gene of viral genome, was established to detect and identify the SARS-CoV-2. We used this assay to screen 309 samples from persons with suspected SARS-CoV-2 infection in Wuhan. Then 6 close-phylogenic coronaviruses and 7 viruses which could cause pneumonia were detected. Moreover, 57 clinical samples infected with other viruses and 77 healthy samples were also tested.Results: The limit of detection of the assay was 6.25 copies per reaction in the detection of cRNA transcribed in vitro. The results of detection of throat and fecal swabs from persons with suspected SARS-CoV-2 infection showed throat swabs were more sensitive than fecal swabs during the first 15 days after onset of symptoms (throat: 56.80%, fecal: 30.43%), while the situation was reversed after 15 days (throat: 20.83%, fecal: 27.58%). And matched pair tests suggested the sputum samples had higher virus loads than throat swabs in the patients (P < 0.05). There was no cross-reaction when we detected the inactive culture of six other coronaviruses (human coronavirus 229E, NL63, OC43, HKU1, SARS-CoV, MERS-CoV) and seven other viruses (influenza virus A H1N1, influenza virus A H3N2, influenza virus B, parainfluenza viruses 1, 2, and 3; and respiratory syncytial virus). Besides, 27 BALF samples from pneumonia patients infected with human coronavirus 229E, OC43, HKU1 or human adenovirus 7, 30 throat swabs from patients infected with H1N1 and 77 throat swabs from healthy people tested negative by this assay.Conclusions: The results indicated that the assay specifically and sensitively detected the SARS-CoV-2.