Modeling the Global Dynamic Contagion of COVID-19

Xiang, Lijin; Ma, Shiqun; Lü, Yu; Wang, Wenhao; Yin, Zhichao

doi:10.3389/fpubh.2021.809987

Cited by 13 publications

(9 citation statements)

References 44 publications

(38 reference statements)

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“…The reason for this occurrence may be that there were three global centers of the COVID-19 pandemic in the Americas: Canada, Brazil, and the US. The interactive contagion of the COVID-19 pandemic has doubled the difficulty of preventing COVID-19 spread in various countries and put the financial markets in a state of turbulence ( 50 ). For example, the stock markets of various countries have triggered the melting down one after another, which has intensified the financial market risk in the Americas.…”

Section: Resultsmentioning

confidence: 99%

The impact of the COVID-19 pandemic on the global dynamic spillover of financial market risk

Tan

Wang

et al. 2022

Front. Public Health

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The COVID-19 outbreak has greatly impacted the stability of the global financial markets. In the post-COVID-19 pandemic era, the risk contagion patterns of the global financial markets may change. This paper utilizes the conditional value-at-risk (ΔCoVaR) model to measure the risk level of the financial markets in various economies and uses the TVP-VAR-CONNECTEDNESS approach to construct a time-varying spillover index. Based on the dimensions of time and space, we explored the contagion path, contagion status, and contagion structure characteristics of global financial market risk before and during the COVID-19 pandemic. The results entail several conclusions. (i) The COVID-19 pandemic increased the spillover level of global financial market risk and the risk connectedness of financial markets in different countries. In addition, during the concentrated outbreak period of COVID-19, the risk spillover level in developing countries rose rapidly, while the financial risk spillover level in developed countries decreased significantly. (ii) The impact of the COVID-19 pandemic on the spillover of the global financial market risk is time-varying, and there is a strong correlation between the risk spillover level of the financial markets of the world and the severity of the COVID-19 pandemic. (iii) Due to the impact of the COVID-19 pandemic, Brazil, Canada, and Russia have become new risk spillover centers; in the post-COVID-19 pandemic era, China's spillover to developed countries has increased, and the financial influence of China has also gradually increased. In addition, the risk contagion capacity of financial markets among European countries is gradually converging. (iv) During the concentrated outbreak of the COVID-19 pandemic, the Americas were the main exporter of global financial market risk, while Europe played a role in risk absorption.

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Section: Resultsmentioning

confidence: 99%

The impact of the COVID-19 pandemic on the global dynamic spillover of financial market risk

Tan

Wang

et al. 2022

Front. Public Health

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“…With continuous improvements to epidemic prevention and control in the world, the level of market risk infection has declined periodically. However, the cross-border contagion of COVID-19 gives the epidemic the characteristics of strong repeatability and frequency ( 49 ). During 2020 and 2021, for instance, the volatility spillover level among the gold, silver, crude oil, and natural gas markets fluctuated greatly, showing a strong connectedness with the severity of the epidemic.…”

Section: Empirical Results and Discussionmentioning

confidence: 99%

COVID-19 Shock and the Time-Varying Volatility Spillovers Among the Energy and Precious Metals Markets: Evidence From A DCC-GARCH-CONNECTEDNESS Approach

Tan

Wang

et al. 2022

Front. Public Health

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The outbreak of the COVID-19 epidemic intensified the volatility of commodity markets (the energy and precious metals markets), which created a significant negative impact on the volatility spillovers among these markets. It may also have triggered a new volatility risk contagion. In this paper, we introduce the DCC-GARCH-CONNECTEDNESS approach to explore the volatility spillover level and multi-level spillover structure characteristics among the commodity markets before and during the COVID-19 epidemic in order to clarify the new volatility risk contagion patterns across the markets. The results implied several conclusions. (i) The COVID-19 epidemic has significantly improved the total volatility spillover level of the energy and precious metals markets and has enhanced the risk connectivity among the markets. (ii) The COVID-19 epidemic has amplified the volatility of the crude oil market, making it the main volatility spillover market, namely the source of volatility risk contagion. (iii) The COVID-19 epidemic outbreak enhanced the external risk absorption capacity of the natural gas and silver markets, and the absorption level of the external volatility spillover improved significantly. Furthermore, the risk absorption capacity of the gold market weakened, while the gold market has remained the endpoint of external volatility risk during the epidemic and has acted as a risk stabilizer. (iv) The volatility spillover among markets has clear time-varying characteristics and a positive connectedness with the severity of the COVID-19 epidemic. As the severity of the COVID-19 epidemic increases, the volatility risk connectivity among the markets rapidly increases.

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“…Since the COVID-19 outbreak, researchers have studied various phases such as transmission trends, pathological behavior, mitigation measures, preventive actions, and so on. 9,10 Fractional modeling of epidemiology can effectively capture the features of hysteresis depending on historical data better than ordinary derivatives. Memory effects of the fractional order system have a great impact on the immune responses of human cells to diseases.…”

Section: Introductionmentioning

confidence: 99%

“…Various studies have been examined in epidemiology with differential equations of integer order and fractional order as extensions, modifications, and inclusions to the basic SIR model. Since the COVID‐19 outbreak, researchers have studied various phases such as transmission trends, pathological behavior, mitigation measures, preventive actions, and so on 9,10 . Fractional modeling of epidemiology can effectively capture the features of hysteresis depending on historical data better than ordinary derivatives.…”

Section: Introductionmentioning

confidence: 99%

Fractional commensurate model on COVID‐19 with microbial co‐infection: An optimal control analysis

Vijayalakshmi,

Roselyn Besi,

Akgül

2024

Optim Control Appl Methods

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Crossover behaviors have always existed in the history of infectious pandemics due to a few distinct, erratic spread outlines. This research aims to investigate the crossover behavior of the proposed SVICR commensurate fractional model for the COVID‐19 delta variant, considering microbial coinfections. A mathematical model in terms of Atangana–Baleanu Caputo (ABC) category fractional integrals takes into account the co‐infection of mucormycosis in immunocompromised COVID‐19 patients caused by microbial infections. ABC operators preserve the intact history of the happenings under contemplation through its nonsingular kernel. It is observed that the framed five‐compartmental SVICR model is positively bounded on R5, the solution space. Two equilibrium points representing the survival and annihilation of sickness respectively are contributed by the single population N(t), which is counted in five dependent compartments: The bilinear growth rate of new additional infections from the contagious infectives over time ‘t’ is viewed through the threshold metric Lyapunov's stability function examines the parametric influences over the virulent spread globally. The significant focus is to investigate the Mucormycosis cases in COVID‐19 patients with underlying diabetic complications. Diabetes mellitus is the major concern for several coinfections among COVID‐19 recoveries. Aiming to minimalize the critical states, an Lagrangian–Hamiltonian optimum control structure is also performed for the SVICR model by introducing control variables in effect to tri‐control probes of minimized contact rates, persuasive vaccinations, and glycemic control of post recovered diabetic patients. The hike in the Severity of the ailment due to fungal pathogens is studied through numerical convergence of predictor–corrector scheme and simulations. Using estimated parametric values from the statistical data of mucormycosis and infections of COVID‐19 reported cases in India, the prominence of control effects are visualized graphically. To conclude, a complete qualitative analysis of the minimization problem is executed for different levels of control values. We avow that effective control intrusions would almost certainly decline the complexities associated with the viral pathogens.

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Modeling the Global Dynamic Contagion of COVID-19

Cited by 13 publications

References 44 publications

The impact of the COVID-19 pandemic on the global dynamic spillover of financial market risk

The impact of the COVID-19 pandemic on the global dynamic spillover of financial market risk

COVID-19 Shock and the Time-Varying Volatility Spillovers Among the Energy and Precious Metals Markets: Evidence From A DCC-GARCH-CONNECTEDNESS Approach

Fractional commensurate model on COVID‐19 with microbial co‐infection: An optimal control analysis

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