Neutrophil Elastase Inhibitor (Sivelestat) in the Treatment of Acute Respiratory Distress Syndrome Induced by COVID- 19: A Multicenter Retrospective Cohort Study (preprint)

Background Recent studies suggest that neutrophil elastase inhibitor (Sivelestat) may improve pulmonary function and reduce mortality in patients with acute respiratory distress syndrome. We examined the association between receipt of sivelestat and improvement in oxygenation among patients with acute respiratory distress syndrome (ARDS) induced by COVID-19.Methods A large multicentre cohort study of patients with ARDS induced by COVID-19 who had been admitted to intensive care units (ICUs). We used propensity score matching to compare the outcomes of patients treated with sivelestat to those who were not. The differences in continuous outcomes were assessed with the Wilcoxon signed-rank test. Kaplan-Meier method was used to show the 28-day survival curves in the matched cohorts. A log-rank P-test stratified on the matched pairs was used to test the equality of the estimated survival curves. A Cox proportional hazards model that incorporated a robust sandwich-type variance estimator to account for the matched nature of the data was used to estimate hazard ratios (HR). All statistical analyses were performed with SPSS 26.0 and R 4.2.3. A two-sided p-value of < 0.05 was considered statistically significant.Results A total of 387 patients met inclusion criteria, including 259 patients (66.9%) who were treated with sivelestat. In 158 patients matched on the propensity for treatment, receipt of sivelestat was associated with improved oxygenation, decreased Murray lung injury score, increased non-mechanical ventilation time within 28 days, increased alive and ICU-free days within 28 days (HR, 1.85; 95% CI, 1.29 to 2.64; log-rank p < 0.001), shortened ICU stay and ultimately improved survival (HR, 2.78; 95% CI, 1.32 to 5.88; log-rank p = 0.0074).Conclusions Among patients with ARDS induce by COVID-19, sivelestat administration is associated with improved clinical outcomes.

Examining Dynamic Connectedness between Green Bonds and Traditional Assets During Crises (preprint)

We investigate the volatility connectedness between US green bonds and several major traditional financial market volatility indices by applying a novel TVP-VAR frequency connectedness methodology. This paper aims to explore the specific role that the US green bond market possesses during three dynamic events that resulted in substantial financial market instability and discontinuity, such as the US-China trade war, the COVID-19 pandemic, and the Russian-Ukraine conflict. Empirical results highlight that US green bond market is a shock receiver from each of the analysed stock, oil, gold, and exchange rate markets, but rather, is a transmitter of shocks to the cryptocurrency market. Furthermore, we identify significant evidence of strong decoupling of green bond connectedness during the Ukraine crisis. Such findings prove that black swan events have been deeply disruptive to the green transition, specifically relevant to policymakers and market participants.

The growth of oil futures in China: Evidence of market maturity through global crises

Chinese oil futures products were created in 2018, and have since presented an alternative, regional exchange through which to invest. This research tests for evidence of developing market maturity during the time since the market was established, specifically focusing on static and time-varying spillovers of higher moments between Chinese oil futures prices and other international crude oil markets. Chinese oil markets are also valuable when considering contagion and informational effects within the COVID-19 outbreak. Results indicate significant evidence of market maturity, to the extent that Chinese oil futures play a dominant role in the risk transmission of volatility, information asymmetry and extreme values, to both the international oil market and China’s domestic energy-related markets before the outbreak of the COVID-19. After the escalation of the COVID-19 pandemic, such maturity and informational effects deteriorate significantly. Such outcomes suggest that while Chinese oil futures markets were growing at pace to become a leading international oil product, the outbreak of COVID-19 has stalled such progress.

Phylogeny, Evolution, and Transmission Dynamics of Canine and Feline Coronaviruses: A Retro-Prospective Study

Canine coronavirus (CCoV) and feline coronavirus (FCoV) are endemic in companion animals. Due to their high mutation rates and tendencies of genome recombination, they pose potential threats to public health. The molecular characteristics and genetic variation of both CCoV and FCoV have been thoroughly studied, but their origin and evolutionary dynamics still require further assessment. In the present study, we applied a comprehensive approach and analyzed the S, M, and N genes of different CCoV/FCoV isolates. Discriminant analysis of principal components (DAPC) and phylogenetic analysis showed that the FCoV sequences from Chinese isolates were closely related to the FCoV clusters in Netherlands, while recombination analysis indicated that of S N-terminal domain (NTD) was the most susceptible region of mutation, and recombination of this region is an important cause of the emergence of new lineages. Natural selection showed that CCoV and FCoV subgenotypes were in selection constraints, and CCoV-IIb was in strong positive selection. Phylodynamics showed that the mean evolution rate of S1 genes of CCoV and FCoV was 1.281 × 10–3 and 1.244 × 10–3 subs/site/year, respectively, and the tMRCA of CCoV and FCoV was about 1901 and 1822, respectively. Taken together, our study centered on tracing the origin of CCoV/FCoV and provided ample insights into the phylogeny and evolution of canine and feline coronaviruses.

Have crisis-induced banking supports influenced European bank performance, resilience and price discovery?

The ownership structures of European banks are today quite different relative to those before the Global Financial Crisis (GFC), particularly due to new takeovers, government guarantees, bailouts, and other defensive market responses post-GFC. These new ownership structures raise questions as to how these banks have performed, particularly during the implementation of non-standard central bank monetary policies in response to crises that have occurred since the GFC. This paper develops a time-varying series of changing government, private and public bank ownership structures, and compares the performance of several major European banking institutions during periods of crises and mitigating central bank actions. We specifically evaluate as to whether crisis-driven changes of ownership structure have influenced the corporate performance, resilience and signals of price discovery generated by these institutions? The COVID-19 pandemic is identified and used as an example of an idiosyncratic shock on which testing procedures are implemented. Significant differentials within the European banking system based on government supports are identified. The data examined show that the information share of price discovery among government-supported European banks is significantly higher in non-crisis periods than non-government supported banks. We present several companion tests consistent with this evidence and discuss a variety of implications for future research and policy.

Calculus of Consent via MARL: Legitimating the Collaborative Governance Supplying Public Goods (preprint)

Public policies that supply public goods, especially those involve collaboration by limiting individual liberty, always give rise to controversies over governance legitimacy. Multi-Agent Reinforcement Learning (MARL) methods are appropriate for supporting the legitimacy of the public policies that supply public goods at the cost of individual interests. Among these policies, the inter-regional collaborative pandemic control is a prominent example, which has become much more important for an increasingly inter-connected world facing a global pandemic like COVID-19. Different patterns of collaborative strategies have been observed among different systems of regions, yet it lacks an analytical process to reason for the legitimacy of those strategies. In this paper, we use the inter-regional collaboration for pandemic control as an example to demonstrate the necessity of MARL in reasoning, and thereby legitimizing policies enforcing such inter-regional collaboration. Experimental results in an exemplary environment show that our MARL approach is able to demonstrate the effectiveness and necessity of restrictions on individual liberty for collaborative supply of public goods. Different optimal policies are learned by our MARL agents under different collaboration levels, which change in an interpretable pattern of collaboration that helps to balance the losses suffered by regions of different types, and consequently promotes the overall welfare. Meanwhile, policies learned with higher collaboration levels yield higher global rewards, which illustrates the benefit of, and thus provides a novel justification for the legitimacy of, promoting inter-regional collaboration. Therefore, our method shows the capability of MARL in computationally modeling and supporting the theory of calculus of consent, developed by Nobel Prize winner J. M. Buchanan.

Modelling the effect of local and regional emissions on PM2.5 concentrations in Wuhan, China during the COVID-19 lockdown

PM2.5 concentrations in Wuhan, China decreased by 36.0% between the period prior to the COVID-19 pandemic (1‒23 January, 2020) and the COVID-lockdown period (24 January to 29 February, 2020). However, decreases in PM2.5 concentration due to regional PM2.5 transport driven by meteorological changes, and the relationship between the PM2.5 source and receptor, are poorly understood. Therefore, this study assessed how changes in meteorology, local emissions, and regional transport from external source emissions contributed to the decrease in Wuhan’s PM2.5 concentration, using FLEXPART-WRF and WRF-Chem modelling experiments. The results showed that meteorological changes in central China explain up to 22.2% of the total decrease in PM2.5 concentrations in Wuhan, while the remaining 77.8% was due to air pollutant emissions reduction. Reduction in air pollutant emissions depended on both local and external sources, which contributed alomst equally to the reduction in PM2.5 concentrations (38.7% and 39.1% of the total reduction, respectively). The key emissions source areas affecting PM2.5 in Wuhan during the COVID-lockdown were identified by the FLEXPART-WRF modeling, revealing that regional-joint control measures in key areas accounted for 89.3% of the decrease in PM2.5 concentrations in Wuhan. The results show that regional-joint control can be enhanced by identifying key areas of emissions reduction from the source‒receptor relationship of regional PM2.5 transport driven by meteorology under the background of East Asian monsoon climate change.

An analysis of investor behaviour and information flows surrounding the negative WTI oil price futures event

Intertwined with the persisting effects of the COVID-19 pandemic on the world economy, the price of WTI crude oil futures became negative on April 20, 2020. This anomalous incident has drawn much attention within the literature. This paper attempts to investigate the origins and specific impacts of the negative pricing event on the price discovery of WTI futures by employing a bivariate VECM-DCC-GARCH-SNP model, incorporating Legendre polynomials, where the dynamics of major information share measures at high-frequency time intervals are uncovered. Time-varying patterns of information share are identified across the period surrounding negative WTI prices. In particular, price discovery effects steadily abate after a sharp shock during the eight weeks before the negative pricing event. Peak price discovery differentials then re-occur within the negative-pricing event, before once again abating. Such results verify CFTC concerns surrounding the peculiarity of WTI futures trading conditions, that is, the conditions for the negative pricing event were well-established in the weeks before April 2020. Our results shed light on stylised evidence relating to the information efficiency of the international crude oil market more generally.

Evaluation and Prediction of COVID-19 Prevention and Control Strategy Based on the SEIR-AQ Infectious Disease Model

Based on the SEIR model, which takes into account prevention and control measures, prevention and control awareness, and economic level and medical level indicators, this paper proposes an infectious disease model of “susceptible-exposed-infected-removed-asymptomatic-isolated” (short for SEIR-AQ) to assess and predict the development of the COVID-19 pandemic with different prevention and control strategies. The kinetic parameters of the SEIR-AQ model were obtained by fitting, and the parameters of the SEIR-AQ model were solved through the Euler method. Furthermore, the effects of different countries’ prevention and control strategies on the number of infections, the proportion of isolation, the number of deaths, and the number of recoveries were also simulated. The theoretical analysis showed that measures such as isolation for prevention and control and medical tracking isolation had a significant inhibitory effect on the development of the COVID-19 pandemic, among which stratified treatment and enhanced awareness played a key role in the rapid regression of the peak of COVID-19-infected patients. Conclusion of the Simulation. The SEIR-AQ model can be used to evaluate the development status of the COVID-19 epidemic and has some theoretical value for the prediction of COVID-19.

Chinese Herbal Medicine (“3 Medicines and 3 Formulations”) for COVID-19: Rapid Systematic Review and Meta-Analysis (preprint)

Background: To evaluate the evidence behind claims that Chinese Herbal Medicine, specifically “three medicines and three formulations” (3M3F, comprising Jinhua Qinggan, Lianhua Qingwen, Xuebijing, Qingfei Paidu, Huashi Baidu and Xuanfei Baidu), is an effective treatment for COVID-19. Methods: We searched PubMed, MEDLINE and CNKI databases, preprint servers, clinical trial registries and supplementary sources for Chinese- or English-language randomised trials or non-randomised studies with comparator groups, which tested the constituents of 3M3F in the treatment of COVID-19 up to September 2020. Primary outcome was change in disease severity. Secondary outcomes included various symptoms. Meta-analysis (using generic inverse variance random effects model) was performed when there were two or more studies reporting on the same symptom. Results: Of 607 articles identified, thirteen primary studies (six RCTs and seven retrospective non-randomised comparative studies) with 1467 participants met our final inclusion criteria. Studies were small and had significant methodological limitations, most notably potential bias in assessment of outcomes. No study convincingly demonstrated a statistically significant impact on change in disease severity. Eight studies reported sufficiently similar secondary outcomes to be included in a meta-analysis. Some statistically significant impacts on symptoms, chest CT manifestations, laboratory variables and length of stay were demonstrated, but such findings were sparse and many remain unreplicated.Conclusions: These findings neither support nor refute the claim that 3M3F alters the severity of COVID-19 or alleviates symptoms. More rigorous studies are required to properly ascertain the potential role of Chinese Herbal Medicine in COVID-19.Systematic review registration:  This review was registered on PROSPERO (CRD42020187502) prior to data collection and analysis.

Effectiveness of digital interventions to improve household and community infection prevention and control behaviours and to reduce incidence of respiratory and/or gastro-intestinal infections: A rapid systematic review (preprint)

BackgroundDigital interventions have potential to efficiently support improved hygiene practices to reduce transmission of COVID-19. ObjectiveTo evaluate the evidence for digital interventions to improve hygiene practices within the community. MethodsWe reviewed articles published between 01 January 2000 and 26 May 2019 that presented a controlled trial of a digital intervention to improve hygiene behaviours in the community. We searched MEDLINE, Embase, PsycINFO, Cochrane Controlled Register of Trials (CENTRAL), China National Knowledge Infrastructure and grey literature. Trials in hospitals were excluded, as were trials aiming at prevention of sexually transmitted infections; only target diseases with transmission mechanisms similar to COVID-19 (e.g. respiratory and gastrointestinal infections) were included. Trials had to evaluate a uniquely digital component of an intervention. Study designs were limited to randomised controlled trials, controlled before-and-after trials, and interrupted time series analyses. Outcomes could be either incidence of infections or change in hygiene behaviours. The Risk of Bias 2 tool was used to assess study quality. ResultsWe found seven studies that met the inclusion criteria. Six studies reported successfully improving self-reported hygiene behaviour or health outcomes, but only one of these six trials confirmed improvements using objective measures (reduced consultations and antibiotic prescriptions), Germ Defence. Settings included kindergartens, workplaces, and service station restrooms. Modes of delivery were diverse: WeChat, website, text messages, audio messages to mobiles, electronic billboards, and electronic personal care records. Four interventions targeted parents of young children with educational materials. Two targeted the general population; these also used behaviour change techniques or theory to inform the intervention. Only one trial had low risk of bias, Germ Defence; the most common concerns were lack of information about the randomisation, possible bias in reporting of behavioural outcomes, and lack of an analysis plan and possible selective reporting of results. ConclusionThere was only one intervention that was judged to be at low risk of bias, Germ Defence, which reduced incidence and severity of illness, as confirmed by objective measures. Further evaluation is required to determine the effectiveness of the other interventions reviewed.

Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre

Utilising Chinese-developed data based on long-standing influenza indices, and the more recently-developed coronavirus and face mask indices, we set out to test for the presence of volatility spillovers from Chinese financial markets upon a broad number of traditional financial assets during the outbreak of the COVID-19 pandemic. Such indices are used to specifically measure the performance of Chinese companies who are inherently involved in the R&D and production of materials and products used to mitigate and counteract the effects of influenza and coronavirus, therefore, such indices present a unique barometer of broad population-based sentiment relating to COVID-19 in comparison to traditional Chinese influenza. Within days of the formal announcement of the COVID-19 outbreak, results indicate exceptionally pronounced and persistent impacts of the coronavirus pandemic upon Chinese financial markets, compared to that of the traditional and long-standing influenza index. Further, in a novel finding to date, COVID-19 is found to have had a substantial effect on directional spillovers upon the Bitcoin market. Cryptocurrency-based confidence appears to have been instigated through government-developed education schemes, which are identified as one possible explanation for our results, which are found to remain robust across both data-frequency and methodological variation.