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The COVID-19 pandemic has dramatically influenced urban mobility patterns. This paper explores the impact of the pandemic on the travel patterns and flow structure of bike-sharing, in Wuhan, China. We find that during the pandemic, bike-sharing became a major mode of transport and helped for the travel to hospitals. In post-pandemic Wuhan, more cycling neighbourhoods emerged in suburban areas, and the percentage of bike-sharing ridership in denser areas tends to decrease, especially in workplaces, indicating there is a decentralised trend of bike-sharing flow structure. These findings imply that bike-sharing plays a significant role in promoting urban resilience, and are helpful to build bike-friendly cities and communities in the post-pandemic era. [ABSTRACT FROM AUTHOR]

The general remit of this paper is the role of wildlife trade in pathogen spillover. Its underlying assumption is that, so far from being the exclusive domain of the life sciences, the study of pathogen spillover will be greatly enhanced by multi-perspectival approaches, including One Health and those employed here, namely, non-speciesist green criminology and critical animal studies. The paper moves from discussions of zoonosis, anthroponosis and wildlife trade to the emergence of COVID-19 in Wuhan, China. The paper recommends the abolition of all wildlife trade and the reclamation of wildlife habitat and broaches discussion of the extension of legal personhood to wild animals. [ABSTRACT FROM AUTHOR]

Antigen-specific class-switched antibodies are detected at the same time or even before IgM in serum of non-vaccinated individuals infected with SARS-CoV-2. These derive from the first wave of plasmablasts formed. Hence, the phenotype and specificity of plasmablasts can reveal information about early B-cell activation. Here we have analyzed B cells and plasmablasts circulating in blood of COVID-19 patients not previously exposed to SARS-CoV-2 during and after disease. We find that during infection with the original Wuhan strain, plasmablasts in blood produce IgA1, IgG1, and IgM, and that most express CCR10 and integrin β1, only some integrin β7, while the majority lack CCR9. Plasmablast-secreted antibodies are reactive to the spike (S) and nucleocapsid (N) proteins of the Wuhan strain as well as later variants of concern, but also bind S proteins from endemic and non-circulating betacoronaviruses. In contrast, after recovery, antibodies produced from memory B cells target variants of SARS-CoV-2 and SARS-CoV-1 but compared to previously non-infected individuals do not show increased binding to endemic coronaviruses. This suggests that the early antibody response to a large extent stems from pre-existing cross-reactive class-switched memory B cells, and that although newly formed memory cells target the novel SARS-CoV-2 virus the numbers of broadly cross-reactive memory B cells do not increase extensively. The observations give insight into the role of pre-existing memory B cells in early antibody responses to novel pathogens and may explain why class-switched antibodies are detected early in the serum of COVID-19 patients. During an infection, plasmablasts circulating in blood represent ongoing formation of antibody-producing cells from activated B cells. Here we study the early plasmablasts in previously naïve COVID-19 patients arriving at hospital. We find extensive cross-reactivity to circulating and non-circulating beta-coronaviruses, that IgA1 responses dominate, and that the cells express markers suggesting mucosal homing. [ABSTRACT FROM AUTHOR]

Summary: Since cases first emerged in December 2019, COVID‐19 (a type of coronavirus) has rapidly become pandemic. This fast‐tracked paper (published quickly) from China on COVID‐19 is written by dermatologists at the epicentre of the outbreak in Wuhan. Dermatology clinic staff may be at risk because protective equipment is not routinely available, and skin lesions might possibly transmit the virus indirectly. These authors suggest preventive measures based on experience in this and previous coronavirus outbreaks. Online consultation for non‐urgent patients reduces the numbers of patients attending clinics. Nurse‐led triage, to identify patients with possible COVID‐19, at the entrances of hospital and skin clinics directs patients with a cough or fever to a specific COVID‐19 area and a dermatologist is consulted if the fever might be related to skin disease. Clinic staff wear N95 masks and observe hand hygiene during consultations. Patients are admitted to a ward only if routine blood tests and chest CT scans exclude COVID‐19. Triage will not detect patients who are showing no symptoms but who are developing the disease, so the hospital should provide an on‐call expert team to discuss inpatients suspected or diagnosed with COVID‐19 and refer them to radiology, respiratory or intensive care colleagues as required. Confirmed cases are managed following local policies. Skin disorders in COVID‐19 inpatients can usually be managed remotely using photographs, email and teleconferencing. If necessary a multidisciplinary team (a team of medical staff from different specialties) can meet in the clean area of the isolation ward. If the dermatologist must see the patient, all records should be provided in advance to minimise exposure time. With these precautions, as of 20th February 2020 no infected patients were detected in the Wuhan Dermatology Department. This is a summary of the study: Emergency management for preventing and controlling nosocomial infection of 2019 novel coronavirus: implications for the dermatology department Linked Article: Tao et al. Br J Dermatol 2020; 182:1477–1478 [ABSTRACT FROM AUTHOR]

Since recording the first case in Wuhan in November 2020, COVID-19 is still spreading widely and rapidly affecting the health of millions all over the globe. For fighting against this pandemic, numerous strategies have been made, where the early isolation is considered among the most effective ones. Proposing useful methods to screen and diagnose the patient's situation for the purpose of specifying the adequate clinical management represents a significant challenge in diminishing the rates of mortality. Inspired from this current global health situation, we introduce a new autonomous process of decision-making that consists of two modules. The first module is the data analysis based on Bayesian network that is employed to indicate the coronavirus symptoms severity and then classify COVID-19 cases as severe, moderate or mild. The second module represents the decision-making based on association rules method that generates autonomously the adequate decision. To construct the model of Bayesian network, we used an effective method-oriented data for the sake of learning its structure. As a result, the algorithm accuracy in making the correct decision is 30% and in making the adequate decision is 70%. These experimental results demonstrate the importance of the suggested methods for decision-making. [ABSTRACT FROM AUTHOR]

The lack of an identifiable intermediate host species for the proximal animal ancestor of SARS-CoV-2, and the large geographical distance between Wuhan and where the closest evolutionary related coronaviruses circulating in horseshoe bats (members of the Sarbecovirus subgenus) have been identified, is fueling speculation on the natural origins of SARS-CoV-2. We performed a comprehensive phylogenetic study on SARS-CoV-2 and all the related bat and pangolin sarbecoviruses sampled so far. Determining the likely recombination events reveals a highly reticulate evolutionary history within this group of coronaviruses. Distribution of the inferred recombination events is nonrandom with evidence that Spike, the main target for humoral immunity, is beside a recombination hotspot likely driving antigenic shift events in the ancestry of bat sarbecoviruses. Coupled with the geographic ranges of their hosts and the sampling locations, across southern China, and into Southeast Asia, we confirm that horseshoe bats, Rhinolophus , are the likely reservoir species for the SARS-CoV-2 progenitor. By tracing the recombinant sequence patterns, we conclude that there has been relatively recent geographic movement and cocirculation of these viruses' ancestors, extending across their bat host ranges in China and Southeast Asia over the last 100 years. We confirm that a direct proximal ancestor to SARS-CoV-2 has not yet been sampled, since the closest known relatives collected in Yunnan shared a common ancestor with SARS-CoV-2 approximately 40 years ago. Our analysis highlights the need for dramatically more wildlife sampling to: 1) pinpoint the exact origins of SARS-CoV-2's animal progenitor, 2) the intermediate species that facilitated transmission from bats to humans (if there is one), and 3) survey the extent of the diversity in the related sarbecoviruses' phylogeny that present high risk for future spillovers. [ABSTRACT FROM AUTHOR]

Using state-of-the-art data-mining techniques, this research constructs a unique dataset comprising the votes cast by Chinese shareholders on 15,553 resolutions laid before 2,888 general meetings of Shanghai Stock Exchange-listed companies in the six-year period between 2015 and 2020. This research empirically depicts, for the first time, the manner in which minority shareholders exercise their rights to vote in China, presenting a counter-thesis to the conventional wisdom of shareholder passivity. In particular, this research offers a unique perspective on how the COVID-19 pandemic has influenced Chinese shareholders' voting behaviour by focusing its empirical investigation on the 76-day time window from 23 January to 7 April 2020, during which period Wuhan, the epicentre of the COVID-19 outbreak in China, came under a mandatory lockdown order. Our findings offer strong empirical evidence that Chinese shareholders cast their votes in a characteristically more informed manner in the 2020 sample period than they did during the sample periods in the previous five years. The research highlights the potential of shareholder activism in economies where share ownership is concentrated. It also has implications for the ongoing discourse on virtual shareholder meetings and the shareholder franchise. [ABSTRACT FROM AUTHOR]

Background Since December 2019, coronavirus disease (COVID-19) has affected over 50 000 people in Wuhan, China. However, the number of daily infection cases, hospitalization rate, lag time from onset to diagnosis date and their associations with measures introduced to slow down the spread of COVID-19 have not been fully explored. Methods This study recruited 6872 COVID-19 patients in the Wuchang district, Wuhan. All of the patients had an onset date from 21 December 2019 to 23 February 2020. The overall and weekly hospitalization rate and lag time from onset to diagnosis date were calculated. The number of daily infections was estimated by the back-projection method based on the number of daily onset cases. Their association with major government reactions and measures was analyzed narratively. Results The overall hospitalization rate was 45.9% (95% CI 44.7 to 47.1%) and the mean lag time from onset to diagnosis was 11.1±7.4 d. The estimated infection curve was constructed for the period from 14 December 2019 to 23 February 2020. Raising public awareness regarding self-protecting and social distancing, as well as the provision of timely testing and inpatient services, were coincident with the decline in the daily number of infections. Conclusion Early public awareness, early identification and early quarantine, supported by appropriate infrastructure, are important elements for containing the spread of COVID-19 in the community. [ABSTRACT FROM AUTHOR]

Motivation The outbreak of novel severe acute respiratory syndrome coronavirus (SARS-CoV-2, also known as COVID-19) in Wuhan has attracted worldwide attention. SARS-CoV-2 causes severe inflammation, which can be fatal. Consequently, there has been a massive and rapid growth in research aimed at throwing light on the mechanisms of infection and the progression of the disease. With regard to this data science is playing a pivotal role in in silico analysis to gain insights into SARS-CoV-2 and the outbreak of COVID-19 in order to forecast, diagnose and come up with a drug to tackle the virus. The availability of large multiomics, radiological, bio-molecular and medical datasets requires the development of novel exploratory and predictive models, or the customisation of existing ones in order to fit the current problem. The high number of approaches generates the need for surveys to guide data scientists and medical practitioners in selecting the right tools to manage their clinical data. Results Focusing on data science methodologies, we conduct a detailed study on the state-of-the-art of works tackling the current pandemic scenario. We consider various current COVID-19 data analytic domains such as phylogenetic analysis, SARS-CoV-2 genome identification, protein structure prediction, host–viral protein interactomics, clinical imaging, epidemiological research and drug discovery. We highlight data types and instances, their generation pipelines and the data science models currently in use. The current study should give a detailed sketch of the road map towards handling COVID-19 like situations by leveraging data science experts in choosing the right tools. We also summarise our review focusing on prime challenges and possible future research directions. Contact hguzzi@unicz.it , sroy01@cus.ac.in [ABSTRACT FROM AUTHOR]

Coronavirus Disease 2019 (COVID-19) is a sudden viral contagion that appeared at the end of last year in Wuhan city, the Chinese province of Hubei, China. The fast spread of COVID-19 has led to a dangerous threat to worldwide health. Also in the last two decades, several viral epidemics have been listed like the severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002/2003, the influenza H1N1 in 2009 and recently the Middle East respiratory syndrome coronavirus (MERS-CoV) which appeared in Saudi Arabia in 2012. In this research, an automated system is created to differentiate between the COVID-19, SARS-CoV and MERS-CoV epidemics by using their genomic sequences recorded in the NCBI GenBank in order to facilitate the diagnosis process and increase the accuracy of disease detection in less time. The selected database contains 76 genes for each epidemic. Then, some features are extracted like a discrete Fourier transform (DFT), discrete cosine transform (DCT) and the seven moment invariants to two different classifiers. These classifiers are the k -nearest neighbor (KNN) algorithm and the trainable cascade-forward back propagation neural network where they give satisfying results to compare. To evaluate the performance of classifiers, there are some effective parameters calculated. They are accuracy (ACC), F1 score, error rate and Matthews correlation coefficient (MCC) that are 100%, 100%, 0 and 1, respectively, for the KNN algorithm and 98.89%, 98.34%, 0.0111 and 0.9754, respectively, for the cascade-forward network. [ABSTRACT FROM AUTHOR]

The novel coronavirus or COVID-19 has first been found in Wuhan, China, and became pandemic. Angiotensin-converting enzyme 2 (ACE2) plays a key role in the host cells as a receptor of Spike-I Glycoprotein of COVID-19 which causes final infection. ACE2 is highly expressed in the bladder, ileum, kidney and liver, comparing with ACE2 expression in the lung-specific pulmonary alveolar type II cells. In this study, the single-cell RNAseq data of the five tissues from different humans are curated and cell types with high expressions of ACE2 are identified. Subsequently, the protein–protein interaction networks have been established. From the network, potential biomarkers which can form functional hubs, are selected based on k-means network clustering. It is observed that angiotensin PPAR family proteins show important roles in the functional hubs. To understand the functions of the potential markers, corresponding pathways have been researched thoroughly through the pathway semantic networks. Subsequently, the pathways have been ranked according to their influence and dependency in the network using PageRank algorithm. The outcomes show some important facts in terms of infection. Firstly, renin-angiotensin system and PPAR signaling pathway can play a vital role for enhancing the infection after its intrusion through ACE2. Next, pathway networks consist of few basic metabolic and influential pathways, e.g. insulin resistance. This information corroborate the fact that diabetic patients are more vulnerable to COVID-19 infection. Interestingly, the key regulators of the aforementioned pathways are angiontensin and PPAR family proteins. Hence, angiotensin and PPAR family proteins can be considered as possible therapeutic targets. Contact: sagnik.sen2008@gmail.com, umaulik@cse.jdvu.ac.in Supplementary information: Supplementary data are available online. [ABSTRACT FROM AUTHOR]

Background The new coronavirus (COVID-19) rapidly resulted in a pandemic. We report the characteristics of patients with severe or critical severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Wuhan city, China, and the risk factors related to infection severity and death. Methods We extracted the demographic and clinical data of 7283 patients with severe COVID-19 infection from designated Wuhan hospitals as of 25 February 2020. Factors associated with COVID-19 critical illness and mortality were analysed using logistic- and Cox-regression analyses. Results We studied 6269 patients with severe COVID-19 illness and 1014 critically ill patients. The median (IQR) age was 64 (53–71) years; 51.2% were male, 38.9% were retirees and 7.4% had self-reported histories of chronic disease. Up to the end of the study, 1180 patients (16.2%) recovered and were discharged, 649 (8.9%) died and the remainder were still receiving treatment. The number of daily confirmed critical cases peaked between 23 January and 1 February 2020. Patients with advanced age [odds ratio (OR), 1.03; 95% confidence intervals (CIs), 1.03–1.04], male sex (OR, 1.57; 95% CI, 1.33–1.86) and pre-existing diabetes (OR, 2.11), hypertension (OR, 2.72), cardiovascular disease (OR, 2.15) or respiratory disease (OR, 3.50) were more likely to be critically ill. Compared with those who recovered and were discharged, patients who died were older [hazard ratio (HR), 1.04; 95% CI, 1.03–1.05], more likely to be male (HR, 1.74; 95% CI, 1.44–2.11) and more likely to have hypertension (HR, 5.58), cardiovascular disease (HR, 1.83) or diabetes (HR, 1.67). Conclusion Advanced age, male sex and a history of chronic disease were associated with COVID-19 critical illness and death. Identifying these risk factors could help in the clinical monitoring of susceptible populations. [ABSTRACT FROM AUTHOR]

Background Novel coronavirus disease 2019 (COVID-19) emerged in Wuhan and rapidly spread, affecting >10 million cases worldwide. Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and primarily manifesting as an acute respiratory failure with interstitial and alveolar pneumonia, it can also affect multiple organs. Kidney involvement was underestimated in early reports and its role remains controversial. The aim of this study was to analyse the role of kidney damage in COVID-19 outcome. Methods This is a prospective cohort study of 1603 consecutive patients admitted in a University Reference Hospital in the heart of the European outbreak. Results Median age was 64 years, 40.4% were female, 15.2% presented diabetes mellitus, 35.7% hypertension and 20.3% obesity. On admission, the prevalence of elevated serum creatinine (sCr), proteinuria, leucocyturia and haematuria were 21.0, 37.8, 31.8 and 45.6%, respectively. In total, 43.5% of those with an elevated sCr had previous chronic kidney disease (CKD) and 11.4% of those with normal sCr developed an in-hospital acute kidney injury (AKI); 17 patients needed acute haemodialysis; and 197 patients died during hospitalization. Cox proportional hazard regression confirmed that elevated baseline sCr [hazard ratio (95% confidence interval) 2.40 (1.79–3.22)], previous CKD [1.59 (1.06-2.37)], haematuria [1 + 1.68 (0.92–3.06), 2–3 + 2.69 (1.49–4.87)] and in-hospital AKI [1.50 (0.92–2.44)] were independent risk factors for in-hospital death after adjusting for age, sex and comorbidity. Conclusion The prevalence of acute and chronic kidney disease on admission and in-hospital AKI is higher than previously reported in Wuhan, and is associated with high in-hospital mortality. We should increase our awareness towards kidney involvement and design specific strategies for management of COVID-19 in these patients. [ABSTRACT FROM AUTHOR]

Background COVID-19 has spread rapidly and internationally, which has elicited public panic and psychological problems. Public protective behaviors and perception play crucial roles in controlling the spread of illness and psychological status. Methods We conducted a cross-sectional online survey in the hardest-hit Hubei province and other areas in China affected by the COVID-19 outbreak. Questions about their basic information, the perception of the COVID-19 outbreak, recent preventive or avoidance behaviors, and self-reported mental health scales including the Patient Health Questionnaire and Self-Rating Anxiety Scale were included. Binary logistic regressions were used to investigate the association between personal variables/perceptions and psychological distress. Results A total of 6261 people were included in the analysis, with 3613 (57.7%) in Hubei province (1743 in Wuhan). The majority of people have adopted preventive and avoidance behaviors. People from Hubei, with contact history, and people who were infected or whose family members were infected had a much higher prevalence of depression and anxiety. Providing truthful and sufficient information, informing the public about the severity of the disease, and perceptions that the outbreak can be controlled by protective behaviors were associated with lower prevalence of depression and anxiety. Conclusions Assessing the public response, perception, and psychological burden during the outbreak may help improve public health recommendations and deliver timely psychological intervention. Further research may focus on the psychological status of a specialized group to identify methods of delivery of better support based on public response and psychological demand. [ABSTRACT FROM AUTHOR]

A recent outbreak of pneumonia in Wuhan, China was found to be caused by a 2019 novel coronavirus (2019-nCoV or SARS-CoV-2 or HCoV-19). We previously reported the clinical features of 12 patients with 2019-nCoV infections in Shenzhen, China. To further understand the pathogenesis of COVID-19 and find better ways to monitor and treat the disease caused by 2019-nCoV, we measured the levels of 48 cytokines in the blood plasma of those 12 COVID-19 patients. Thirty-eight out of the 48 measured cytokines in the plasma of 2019-nCoV-infected patients were significantly elevated compared to healthy individuals. Seventeen cytokines were linked to 2019-nCoV loads. Fifteen cytokines, namely M-CSF, IL-10, IFN-α2, IL-17, IL-4, IP-10, IL-7, IL-1ra, G-CSF, IL-12, IFN-γ, IL-1α, IL-2, HGF and PDGF-BB, were strongly associated with the lung-injury Murray score and could be used to predict the disease severity of 2019-nCoV infections by calculating the area under the curve of the receiver-operating characteristics. Our results suggest that 2019-nCoV infections trigger extensive changes in a wide array of cytokines, some of which could be potential biomarkers of disease severity of 2019-nCoV infections. These findings will likely improve our understanding of the immunopathologic mechanisms of this emerging disease. Our results also suggest that modulators of cytokine responses may play a therapeutic role in combating the disease once the functions of these elevated cytokines have been characterized. [ABSTRACT FROM AUTHOR]

Novel coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China, and declared by World Health Organization as a pandemic in March 2020. Since then, it has been well known for COVID-19 patients to present with clinical manifestations of severe acute respiratory syndrome (SARS-CoV-2) similar to the influenza. However, in the course of the disease, various pathological complications of high clinical significance have remained unknown. Impaired blood supply to the visceral vascular system can cause serious life-threatening acute damage. We report a case of a 60-year-old female with difficulty in breathing and extensive acute intestinal ischemia confirmed to be associated with SARS-CoV-2 infection. The patient developed a sudden abdominal pain and succumbed shortly after admission before imaging studies were performed. Autopsy revealed massive bowel ischemia. This case highlights the importance of paying attention to serious and less known clinical manifestations other than pulmonary symptoms and fever. [ABSTRACT FROM AUTHOR]