Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning

Vaccination offers health, economic, and social benefits. However, three major issues—vaccine quality, demand forecasting, and trust among stakeholders—persist in the vaccine supply chain (VSC), leading to inefficiencies. The COVID-19 pandemic has exacerbated weaknesses in the VSC, while presenting opportunities to apply digital technologies to manage it. For the first time, this study establishes an intelligent VSC management system that provides decision support for VSC management during the COVID-19 pandemic. The system combines blockchain, internet of things (IoT), and machine learning that effectively address the three issues in the VSC. The transparency of blockchain ensures trust among stakeholders. The real-time monitoring of vaccine status by the IoT ensures vaccine quality. Machine learning predicts vaccine demand and conducts sentiment analysis on vaccine reviews to help companies improve vaccine quality. The present study also reveals the implications for the management of supply chains, businesses, and government.

Bat pluripotent stem cells reveal unique entanglement between host and viruses (preprint)

Bats have evolved features unique amongst mammals, including flight, laryngeal echolocation, and certain species have been shown to have a unique immune response that may enable them to tolerate viruses such as SARS-CoVs, MERS-CoVs, Nipah, and Marburg viruses. Robust cellular models have yet to be developed for bats, hindering our ability to further understand their special biology and handling of viral pathogens. To establish bats as new model study species, we generated induced pluripotent stem cells (iPSCs) from a wild greater horseshoe bat ( Rhinolophus ferrumequinum ) using a modified Yamanaka protocol. Rhinolophids are amongst the longest living bat species and are asymptomatic carriers of coronaviruses, including one of the viruses most closely related to SARS-CoV-2. Bat induced pluripotent stem (BiPS) cells were stable in culture, readily differentiated into all three germ layers, and formed complex embryoid bodies, including organoids. The BiPS cells were found to have a core pluripotency gene expression program similar to that of other species, but it also resembled that of cells attacked by viruses. The BiPS cells produced a rich set of diverse endogenized viral sequences and in particular retroviruses. We further validated our protocol by developing iPS cells from an evolutionary distant bat species Myotis myotis (greater mouse-eared bat) non-lethally sampled in the wild, which exhibited similar attributes to the greater horseshoe bat iPS cells, suggesting that this unique pluripotent state evolved in the ancestral bat lineage. Although previous studies have suggested that bats have developed powerful strategies to tame their inflammatory response, our results argue that they have also evolved mechanisms to accommodate a substantial load of endogenous viral sequences and suggest that the natural history of bats and viruses is more profoundly intertwined than previously thought. Further study of bat iPS cells and their differentiated progeny should advance our understanding of the role bats play as virus hosts, provide a novel method of disease surveillance, and enable the functional studies required to ascertain the molecular basis of bats’ unique traits.

Does Resilience Exist in China’s Tourism Economy? From the Perspectives of Resistance and Recoverability

Since the 21st century, crisis events have been frequent and normalized globally, and improving resilience has become the key for the tourism industry to cope with various uncertainty risks. To reveal the reality of the economic resilience of tourism in China, this study employed the autoregressive integrated moving average model (ARIMA) to construct a counterfactual function and integrated with the peaks-over-threshold (POT) model and geographical detector model to evaluate the spatiotemporal evolution and influencing factors of the economic resilience of tourism in China from the resistance and recoverability perspective, with a view to providing a reference for consolidating the resilience of the economic system of tourism in China and promoting the sustainable development of its tourism economy. The results showed that the economic resilience of tourism in China can be divided into four types—robust, self-reliant, laissez-faire, and fragile—based on a baseline resistance of −0.361 and recoverability of 0.342. Under different contraction–recovery cycles, the resistance and recoverability of China’s tourism economy have been progressively improved, transforming from the centralized model to the discrete model, from a fragile to a self-reliant type. The type of economic resilience of tourism in China exhibited a clustered contiguous development trend, with obvious zonal distribution characteristics and self-reliant tourism economic resilience areas dominating, but most areas have not yet formed stable economic resilience in their tourism sector. The ecological environment quality, government management ability, and technological innovation level were the main factors affecting the economic resilience of tourism in China. The interactions between different influencing factors were more significant in strengthening the tourism economic resilience.

Mapping the Trophic State Index of Eastern Lakes in China using an Empirical Model and Sentinel-2 Imagery Data

Lake eutrophication has become a critical environmental issue due to the global effects of anthropogenic activities and climate change, and has been comprehensively studied for many years. A series of models and indicators have been proposed to assess the trophic state of lakes. The trophic state index (TSI) is a synthetic index that integrates chlorophyll-a, water clarity, and total phosphorus and is widely used to evaluate the trophic state of aquatic environments. In this study, we collected in situ lake samples (N=431) from typical lakes to match Sentinel-2 MultiSpectral Instrument (MSI) imagery data using the Case 2 Regional Coast Color processor. Then we developed a new empirical model, TSI = –34.04 × (band 4/band 5) – 1.114 × (band 1/band 4) + 97.376). This model is valid for all of China, with good performance and few errors (RMSE=7.36;MAE=6.25) for the validation dataset. Recognizing that over 94% of the Chinese population located along eastern watersheds and large lakes have competing water uses, and given the TSI model on the seasonal scales, we further estimated the mean TSI and trophic state in eastern Chinese lakes (> 100 km2) from 2019 to 2020. The results revealed that more lakes were eutrophic in autumn (94.28%) than in spring (> 77.14%), indicating a serious eutrophication of eastern lakes. Although the eastern lakes have been studied in more detail, this study found that eutrophication still has markedly negative impacts on lake ecosystems. In addition, no significant improvement was observed in spring, most likely due to the months of curfew/lockdown from January 2020 onwards due to COVID-19. This may be due to the enrichment of nutrients deposited in sediment or watershed soil, which can be characterized as “autochthonous sources” of lake eutrophication, over decades with high rates of economic development. This study demonstrates the applicability of Sentinel-2 MSI data to monitor lake eutrophication as well as the feasibility of blue/red and red/red edge combinations. The framework and TSI model used bands available on MSI sensors to develop a novel approach for generating historical eutrophication data for large-scale evaluation of and decision-making related aquatic environmental changes, even in poorly studied areas.

Identification of RPSA as a Potential Biomarker in Bronchoalveolar Lavage Fluid for Acute Respiratory Distress Syndrome (preprint)

Background: Acute respiratory distress syndrome (ARDS) is a life-threatening condition leading to severe pulmonary injuries, and proteomic analysis of bronchoalveolar lavage fluid (BALF) might elucidate potential biomarkers for diagnosis and targets for treatment of ARDS. Methods: Through iTRAQ analysis, we investigated paired BALF samples from three ARDS patients in the acute and recovery phases. The proteins sharing the same expression patterns between the two ARDS phases among different patients were determined as co-upregulated and co-downregulated proteins (CUDPs), and differentially expressed proteins (DEPs), whose fold change > 1.2 and P value < 0.05, were selected from CUDPs. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to determine the enriched functions and pathways of the CUDPs. Protein-protein interaction (PPI) network was generated at STRING database, and hub genes were identified by the Cytoscape software. A549 cells were treated by lipopolysaccharide (LPS) to simulate alveolar epithelial cells in ARDS. Results: We identified 374 CUDPs and 53 DEPs. The GO analysis indicated that the most significantly enriched function was neutrophil mediated immunity response, and the KEGG analysis revealed that the 374 CUDPs were most significantly enriched in Coronavirus disease COVID-19 interaction. RPSA was discovered as the most top hub gene among DEPs, and was downregulated at protein levels during ARDS recovery. Moreover, we further confirmed that both RNA and protein level of RPSA increased upon inflammatory stimulation in vitro. Conclusion: Our results proposed RPSA as a candidate for biomarker and therapeutic target of ARDS.

Bibliometric Analysis and Systematic Review of Global Coronavirus Research Trends Before COVID-19: Prospects and Implications for COVID-19 Research.

Coronaviruses (CoV) cause respiratory and intestinal infections. We conducted this bibliometric analysis and systematical review to explore the CoV-related research trends from before COVID-19. We systematically searched the Ovid MEDLINE, Ovid Embase, and Web of Science (WOS) databases for published bibliometric analyses of CoV from database inception to January 24, 2021. The WOS Collection was searched from inception to January 31, 2020, to acquire the CoV-related publications before COVID-19. One-Way ANOVA and Bonferroni multiple-comparison tests were used to compare differences. Visualization mapping and keyword cluster graphs were made to illustrate the research topics and hotpots. We included 14,141 CoV-related publications for the bibliometric analysis and 16 (12 articles) CoV-related bibliometric analyses for the systematic review. Both the systematic review and bibliometric analysis showed (1) the number of publications showed two steep upward trajectories in 2003-2004 and in 2012-2014; (2) the research hotpots mainly focused on the mechanism, pathology, epidemiology, clinical diagnosis, and treatment of the coronavirus in MERS-CoV and SARS-Cov; (3) the USA, and China; the University of Hong Kong; and Yuen KY, came from the University of Hong Kong contributed most; (4) the Journal of Virology had the largest number of CoV related studies. More studies should focus on prevention, diagnosis, and treatment in the future.

Benchmarking the Effects of the Fed’s Secondary Market Corporate Credit Facility Using Yankee Bonds (preprint)

We use “Yankee” bonds, which are dollar-denominated bonds issued by foreign corporations but traded in the US, to benchmark the effects of the Federal Reserve’s Secondary Market Corporate Credit Facility (SMCCF). The SMCCF was established to purchase short-term, investment-grade bonds of US, but not foreign, corporations. Our tests apply a difference-in-differences technique to bond subsamples sorted by short- and long- maturities and AA, A, BBB, and BB credit ratings. Consistent with the SMCCF’s objective, we find that its announcement reduced the yield spreads on short-maturity US investment-grade bonds relative to the yield spreads on similarly-rated short-maturity Yankee bonds. Yet our results show that it also led to relatively lower yield spreads on US long-maturity AA- and A-rated bonds. Moreover, yield spreads on US BB-rated bonds actually rose relative to the spreads on their Yankee counterparts, indicating the SMCCF harmed these excluded bonds. Using the Amihud measure and bond-CDS basis as proxies for illiquidity, our analysis also shows that the SMCCF influenced both the illiquidity and default risk components of US bond yield spreads.

Reporting and methodological quality of COVID-19 systematic reviews needs to be improved: an evidence mapping.

OBJECTIVES: To assess the reporting and methodological quality of COVID-19 systematic reviews, and to analyze trends and gaps in the quality, clinical topics, author countries, and populations of the reviews using an evidence mapping approach. STUDY DESIGN AND SETTING: A structured search for systematic reviews concerning COVID-19 was performed using PubMed, Embase, Cochrane Library, Campbell Library, Web of Science, CBM, WanFang Data, CNKI, and CQVIP from inception until June 2020. The quality of each review was assessed using the Assessment of Multiple Systematic Reviews 2 (AMSTAR 2) checklist and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. RESULTS: In total, 243 systematic reviews met the inclusion criteria, over 50% of which (128, 52.7%) were from 14 developing countries, with China contributing the most reviews (76, 31.3%). In terms of methodological quality of the studies, 30 (12.3%) were of moderate quality, 63 (25.9%) were of low quality, and 150 (61.7%) were of critically low quality. In terms of reporting quality, the median (interquartile range) PRISMA score was 14 (10-18). Regarding the topics of the reviews, 24 (9.9%) focused on the prevalence of COVID-19, 69 (28.4%) focused on the clinical manifestations, 30 (12.3%) focused on etiology, 43 (17.7%) focused on diagnosis, 65 (26.7%) focused on treatment, 104 (42.8%) focused on prognosis, and 25 (10.3%) focused on prevention. These studies mainly focused on general patients with COVID-19 (161, 66.3%), followed by children (22, 9.1%) and pregnant patients (18, 7.4%). CONCLUSION: This study systematically evaluated the methodological and reporting quality of systematic reviews of COVID-19, summarizing and analyzing trends in their clinical topics, author countries, and study populations.

One Risk, Two Debts: The Effects of Rare Disasters on Credit Markets (preprint)

The COVID-19 pandemic has highlighted the impacts that rare disasters can have on credit markets. We discuss and quantify the asset-pricing implications of disaster risk on the risk-free rate, credit spreads, and their term structures. The findings underscore the heterogeneous effects of disasters on the risk-free and risky debt segments of credit markets. The results reveal that federal and private debt are ``two sides of the same coin”, call for a closer coordination between these two distinct sectors of the credit market, and shed light on deleveraging issues that likely lie ahead in the post-disaster world.

Prognostic Nomogram on Admission Predicting Progression for Patients with Nonsevere COVID-19

The present study aimed to establish a prognostic nomogram to stratify high-risk patients with Coronavirus Disease 2019 (COVID-19) who progressed from the nonsevere condition on admission to severe during hospitalization. This multicenter retrospective study included patients with nonsevere COVID-19 on admission from Jan 10, 2020 to Feb 7, 2020. In the training cohort, independent risk factors associated with disease progression were identified by univariate and multivariate analyses. The prognostic nomogram was established and then validated externally using C-index. The study included 351 patients (293 and 58 in the training and validation cohorts, respectively), with 27 (9.2%) and 5 (8.6%) patients progressed, respectively. In the training cohort, older age (OR 1.036, 95% CI 1.000-1.073), more lobes involved on chest CT (OR 1.841, 95% CI 1.117-3.035), comorbidity present (OR 2.478, 95% CI 1.020-6.018), and lower lymphocyte count (OR 0.081, 95% CI 0.019-0.349) were identified as independent risk factors. The prognostic nomogram was established in the training cohort with satisfied external prognostic performance (C-index 0.906, 95% CI 0.806-1.000). In conclusion, older age, comorbidity present, more lobes involved on chest CT, and lower lymphocyte count are independent risk factors associated with disease progression during hospitalization for patients with nonsevere COVID-19.

Collateral Damage or Benefit? The Impacts of COVID-19 Induced Lockdown and Mandatory Screening Policy on Lung Surgery: Evidence from Wuhan (preprint)

Background: The COVID-19 pandemic, accompanied by governments' regulatory restrictions to contain it, interfered with surgical services provision. We aimed to evaluate the impact of a 76-day city-wide lockdown in Wuhan, China, on the provision of four types of surgery and investigate the association between COVID-19 screening measures and the post-lockdown surge in lung surgery. Methods: We collected data of four types of surgery: lung, esophagus, liver, and stomach, conducted between October 1, 2019, to July 31, 2020, from three major hospitals in Wuhan. We compared the demographic information of patients before and after the COVID-19 induced lockdown by surgery types. We then used difference-in-differences analysis to compare the volumes of lung surgery with three other types of surgery. We estimated the abnormal post-lockdown surge in lung surgery, accounting for scheduling delay. Next, we probed into the association between such abnormal increase in lung surgery and the mandatory chest CT scans required by the government as a COVID-19 screening measure using linear regression. Finally, we analyzed the proportion of lung cancer surgery and its demographic characteristics before and after the lockdown.Findings: After the lockdown started, all four types of surgery quickly dropped to a very low level and stayed at that minimum level throughout the lockdown period. Within 12 weeks after the lockdown was lifted, all three surgery types returned to and stayed at the pre-lockdown period except lung surgery, which surged to 150% of the pre-lockdown level. Specifically, the weekly volume of lung surgery in the post-lockdown period was 60% higher than that of esophagus surgery (95% CI, 0·31-0·90), 39% higher than that of liver surgery (95% CI, 0·17-0·63), and 24% higher than that of stomach surgery (95% CI, 0·01-0·47). Moreover, for every 1,000 chest CT scans conducted in week t-1, on average 3·5 (95% CI, 0·56-6·49) lung surgery were expected to occur in the week that followed. Besides, more young female patients received lung surgery after the lockdown [82 (58%) vs. 57 (45%)]. Finally, the fractions of post-lockdown lung cancer surgery were significantly greater than those in the pre-lockdown period (73% vs. 66%).Interpretation: The lockdown severely affected surgical services in Wuhan. Amid the recovery, the surge in lung surgery was associated with the large-scale chest CT screening policy implemented during and after the lockdown. Such a large-scale chest CT screening could be a blessing as it advanced the diagnosis window of lung diseases for young females.Funding: No funding is declared for this study.Declaration of Interests: None reported.Ethics Approval Statement: The authors have used data with the approval from the healthcare information system of three Triple-A accredited hospitals.

Pulmonary function of 47 patients with COVID-19 in recovery period in Guangzhou

Objective: To explore and understand the injury degree of human lung induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), through retrospectively analysis of the 47 patients' pulmonary function in the period of recovery from COVID-19.

Development and validation of a prognostic risk score system for COVID-19 inpatients: A multi-center retrospective study in China (preprint)

Coronavirus Disease 2019 (COVID-19) has become a world-wide pandemic. Hospitalized patients of COVID-19 suffer from a high mortality rate, motivating the development of convenient and practical methods for clinicians to promptly identify high-risk patients. Here we developed a risk score using clinical data from 1,479 inpatients admitted to Tongji Hospital, Wuhan, China (development cohort) and externally validated with data from two other centers: 141 inpatients from Jinyintan Hospital in Wuhan (validation cohort 1) and 432 inpatients from the Third People’s Hospital Shenzhen (validation cohort 2). The risk score is based on three biomarkers readily available in routine blood samples and can be easily translated into a probability of death. The risk score can predict the mortality of individual patients more than 12 days in advance with more than 90% accuracy across all cohorts. Moreover, the Kaplan-Meier score shows that patients upon admission can clearly be differenciated into low, medium or high risk, with an AUC score of 0.9551. In summary, a simple risk score was validated to predict death in patients infected with COVID-19 and was validated in independent cohorts.

Lymphocytopenia and neutrophilia deteriorate at the lowest oxygenation index timepoint in COVID-19 patient (preprint)

BackgroundCoronavirus disease 2019 (COVID-19) spread throughout the world and caused hundreds of thousands of infected people to death. However, the pathogenesis of severe acute respiratory syndrome coronavirus-2 (SARS COV-2) is poorly understood. The objective of this study is to retrospectively explore the pathogenesis of COVID-19 from clinical laboratory findings, taking disease progression into account.MethodsA single-centered, retrospective study was carried out, which included moderate (n=76) and severe COVID-19 cases (n=22). The difference of laboratory findings from blood routine examination and hepatorenal function test were retrospectively evaluated between the state of moderate and severe. The disease progression was indicated by oxygenation index.ResultsAge is a risk factor for disease progression from moderate to severe. Lymphocytopenia, neutrophilia, liver and kidney function decreasement occurred in severe patients on admission, compared with moderate patients. Lymphocytopenia and neutrophilia deteriorated at the lowest oxygenation index timepoint in the severe patients. And the oxygenation index was associated with ratio of lymphocyte and neutrophil in COVID-19 patients.ConclusionsLymphocytopenia and neutrophilia, which deteriorate in the progression of severe patients, are the main pathogenesis of COVID-19. More measures need to be taken to control lymphocytopenia and neutrophilia in severe COVID-19. Oxygenation index presented potentiality as predictor on the progression of COVID-19.  

Alarming Symptoms Leading To Severe COVID-19 Pneumonia: A Meta-Analysis (preprint)

Background: To identify alarming symptoms that could potentially lead to severe form of COVID-19 pneumonia (i.e. novel coronavirus pneumonia: NCP), a disease that is now having pandemic spread.Methods: Articles from PubMed, Embase, Cochrane database and Google up to 24 February 2020 were systematically reviewed. 18 publications that had documented cases of COVID-19 pneumonia were identified. The relevant data were extracted, systematically reviewed and further evaluated using meta-analysis. We define severe COVID-19 pneumonia as the disease status that requires admission to the intensive care unit (ICU) and respiratory/circulatory support, which is in align with the guideline from the World Health Organization (WHO).Results: 14 studies including 1,424 patients were considered eligible and analyzed. Symptoms such as fever (89.2%), cough (67.2%), fatigue (43.6%) were quite common; but dizziness, hemoptysis, abdominal pain and conjunctival congestion/conjunctivitis were relatively rare. The incidence of dyspnea was significantly higher in patients with severe than non-severe COVID-19 pneumonia (42.7% vs.16.3%, p<0.0001). Similarly, fever and diarrhea were also drastically more common in patients with severe form (p=0.0374 and 0.0267). Further meta-analysis using three high-quality China-based studies confirmed such findings and showed that dyspnea, fever and diarrhea were 3.53 (OR: 3.53, 95%CI: 1.95-6.38), 1.70 (OR: 1.70, 95%CI: 1.01-2.87), and 1.80 (OR: 1.80, 95%CI: 1.06-3.03) folds higher respectively in patients with severe COVID-19 pneumonia.Conclusion: Dyspnea, fever and diarrhea are significantly more prevalent in patients with severe COVID-19 pneumonia, suggesting they are alarming symptoms that warrant close attention and timely management.

COVID-19 is a risk factor for severe liver damage for patients with intrahepatic cholestasis of pregnancy: a case report (preprint)

Background: Patients with intrahepatic cholestasis of pregnancy (ICP) may present with slight liver damage. In the global outbreak, the number of pregnant women infected with coronavirus disease 2019 (COVID-19) is increasing. For the pregnant patients with ICP, COVID-19 may cause severe liver damage.Case presentation: A 31-year-old pregnant woman was admitted with fever and respiratory symptoms to Tongji Hospital in Wuhan amid the outbreak of COVID-19. Her chest CT scan showed an infection with viral pneumonia as multiple ground glass opacities in both lungs were spotted. Laboratory tests revealed increased white blood cell (WBC) count and decreased lymphocyte count. The levels of serum total bile acid (TBA) were highly elvated. So were the indices of liver function, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), direct bilirubin (DBIL), alkaline phosphatase (AKP), 𝛄-glutamyltranspeptidase (𝛄-GT), and lactate dehydrogenase (LDH). The patient was later diagnosed of COVID-19 with comorbid ICP, presenting severe liver damage. Through timely termination of pregnancy and effective treatments, the prognoses of the patient and the fetus were well improved.Conclusions: This case highlights that COVID-19 may be a risk factor of severe liver damage for patients with ICP.Timely termination of pregnancy and effective symptomatic treatments are helpful to improve the progonosis.