Global stability and optimal control for a COVID-19 model with vaccination and isolation delays

Song, Haitao; Wang, Ruifeng; Liu, Shengqiang; Zhou, Jin; He, Daihai

doi:10.1016/j.rinp.2022.106011

Cited by 13 publications

(6 citation statements)

References 28 publications

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“…Therefore, in order to gain insight into the impact of pandemic attention on the Bitcoin futures market, it is essential to consider the potential influences of other related financial markets by controlling these markets. This paper then constructs a regression model including controlled markets, as shown in equation (4).…”

Section: Control Related Marketsmentioning

confidence: 99%

“…Specifically, "Worldwide" is set as the search scope, and daily GSVI for "coronavirus" is downloaded from Google Trends 3 from January 30, 2020 to February 28, 2022. The reason for setting January 30, 2020, as the beginning day of the pandemic, is that the WHO declared the pandemic a public health emergency of international concern on that day, 4 and thus triggered huge investor attention worldwide. GSVI can provide a time series of search volume indexes ranging from zero to one hundred.…”

Section: Datamentioning

confidence: 99%

“…The pandemic has become the most significant public health event since the outbreak of the 1918 flu, with substantial implications for human health, society, and global economic growth ( 3 ). In order to address the threats posed by the pandemic, countries have implemented effective prevention and control measures, such as non-pharmaceutical interventions and vaccination ( 4 ). Nevertheless, COVID-19 has a high propensity to mutate, leading to the creation of many variant strains.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

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The COVID-19 pandemic and Bitcoin: Perspective from investor attention

Wan

Zhu

2023

Front. Public Health

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The response of the Bitcoin market to the novel coronavirus (COVID-19) pandemic is an example of how a global public health crisis can cause drastic market adjustments or even a market crash. Investor attention on the COVID-19 pandemic is likely to play an important role in this response. Focusing on the Bitcoin futures market, this paper aims to investigate whether pandemic attention can explain and forecast the returns and volatility of Bitcoin futures. Using the daily Google search volume index for the “coronavirus” keyword from January 2020 to February 2022 to represent pandemic attention, this paper implements the Granger causality test, Vector Autoregression (VAR) analysis, and several linear effects analyses. The findings suggest that pandemic attention is a granger cause of Bitcoin returns and volatility. It appears that an increase in pandemic attention results in lower returns and excessive volatility in the Bitcoin futures market, even after taking into account the interactive effects and the influence of controlling other financial markets. In addition, this paper carries out the out-of-sample forecasts and finds that the predictive models with pandemic attention do improve the out-of-sample forecast performance, which is enhanced in the prediction of Bitcoin returns while diminished in the prediction of Bitcoin volatility as the forecast horizon is extended. Finally, the predictive models including pandemic attention can generate significant economic benefits by constructing portfolios among Bitcoin futures and risk-free assets. All the results demonstrate that pandemic attention plays an important and non-negligible role in the Bitcoin futures market. This paper can provide enlightens for subsequent research on Bitcoin based on investor attention sparked by public emergencies.

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Section: Control Related Marketsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introduction and Literature Reviewmentioning

confidence: 99%

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The COVID-19 pandemic and Bitcoin: Perspective from investor attention

Wan

Zhu

2023

Front. Public Health

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“…Although these measures seem to be effective in the short term, the implementation of these NPIs has not fundamentally curbed the spread of the virus. Once control is relaxed or cancelled, a new wave of infections is inevitable [ 3 , 4 ]. The rapid spread and severe outcomes of COVID-19 infections instigated an unprecedented pace of vaccine research and development.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the next major outbreak of COVID-19 in Mainland China and a vaccination strategy for it

Wu,

Zhou,

Tang

et al. 2023

R. Soc. open sci.

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After the widespread prevalence of COVID-19 at the end of 2022 in Mainland China, a major concern is when will the second major outbreak occur and with what prevalence and fatality rates will it be associated with, as peoples' immunity from natural infection subsides. To address this, we established an age-structured model considering vaccine and infection-derived immunity, fitted an immunity-waning curve, and calibrated the model using the epidemic and vaccination data from Hong Kong in 2022. The model and the situation of the first major epidemic in Mainland China were then used to predict the prevalence rate, fatality rate and peak time of the second wave. In addition, the controlling effects of different vaccination strategies on the second major outbreak are discussed. Finally, a characterization indicator for the level of population immunity was provided. We conclude that if the prevalence of the first major epidemic was 80%, the prevalence rate of the second major outbreak would be about 37.64%, and the peak time would have been July 2 2023. Strengthening vaccination can effectively delay the peak of the second wave of the epidemic and reduce the prevalence.

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“…Throughout history, viruses have been a major factor in the development of societies. Describing the mechanisms of epidemics spreading and predicting their epidemiological trends is the long-standing focus of research with the aim of effectively controlling the spread of diseases [ 1 , 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

Effects of Community Connectivity on the Spreading Process of Epidemics

Gao

Yang

2023

Entropy

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Community structure exists widely in real social networks. To investigate the effect of community structure on the spreading of infectious diseases, this paper proposes a community network model that considers both the connection rate and the number of connected edges. Based on the presented community network, a new SIRS transmission model is constructed via the mean-field theory. Furthermore, the basic reproduction number of the model is calculated via the next-generation matrix method. The results reveal that the connection rate and the number of connected edges of the community nodes play crucial roles in the spreading process of infectious diseases. Specifically, it is demonstrated that the basic reproduction number of the model decreases as the community strength increases. However, the density of infected individuals within the community increases as the community strength increases. For community networks with weak strength, infectious diseases are likely not to be eradicated and eventually will become endemic. Therefore, controlling the frequency and range of intercommunity contact will be an effective initiative to curb outbreaks of infectious diseases throughout the network. Our results can provide a theoretical basis for preventing and controlling the spreading of infectious diseases.

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Global stability and optimal control for a COVID-19 model with vaccination and isolation delays

Cited by 13 publications

References 28 publications

The COVID-19 pandemic and Bitcoin: Perspective from investor attention

The COVID-19 pandemic and Bitcoin: Perspective from investor attention

Prediction of the next major outbreak of COVID-19 in Mainland China and a vaccination strategy for it

Effects of Community Connectivity on the Spreading Process of Epidemics

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