Study of spreading phenomenon in network population considering heterogeneous property

Zou, Rongcheng; Deng, Zhenghong; Lu, Yikang; Hu, Jun; Han, Zhen

doi:10.1016/j.chaos.2021.111520

Cited by 11 publications

(3 citation statements)

References 21 publications

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“…We propose the game-based susceptible-exposed-asymptomatic -symptomatic-hospitalized-recovery-dead (Game-based SEAIHRD) model to describe the dynamics of the epidemic, where the factor related to medical resources is involved and the human's decision to go to the hospital is considered using the evolutionary game theory. The framework of evolutionary games provides an available tool to investigate the epidemic problem related to human behaviors [28][29][30][31][32][33]. According to the difference in human behavior [34][35][36], we define a parameter m to represent individual motivation to seek medical care.…”

Section: Introductionmentioning

confidence: 99%

Assessing the medical resources in COVID-19 based on evolutionary game

Guo

Geng

et al. 2023

PLoS ONE

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COVID-19 has brought a great challenge to the medical system. A key scientific question is how to make a balance between home quarantine and staying in the hospital. To this end, we propose a game-based susceptible-exposed-asymptomatic -symptomatic- hospitalized-recovery-dead model to reveal such a situation. In this new framework, time-varying cure rate and mortality are employed and a parameter m is introduced to regulate the probability that individuals are willing to go to the hospital. Through extensive simulations, we find that (1) for low transmission rates (β < 0.2), the high value of m (the willingness to stay in the hospital) indicates the full use of medical resources, and thus the pandemic can be easily contained; (2) for high transmission rates (β > 0.2), large values of m lead to breakdown of the healthcare system, which will further increase the cumulative number of confirmed cases and death cases. Finally, we conduct the empirical analysis using the data from Japan and other typical countries to illustrate the proposed model and to test how our model explains reality.

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Section: Introductionmentioning

confidence: 99%

Assessing the medical resources in COVID-19 based on evolutionary game

Guo

Geng

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Traditional models for the spread of infectious diseases are the so-called compartment models, including the SIS (susceptible-infected-susceptible) and the SIR (susceptible-infected-recovered) models [5] , [6] , [7] , [8] , or the more sophisticated SIRS (susceptible-infected-recovered-susceptible) and SEIR (susceptible-exposed-infected-recovered) models [9] , [10] , [11] , [12] , among many others. In these models, individuals in the population are divided into different compartments that describe their status (susceptible or infected, for example).…”

Section: Introductionmentioning

confidence: 99%

“…Although the traditional spreading models describe the spreading behavior of many diseases, they have important limitations, as they ignore the heterogeneity of the infectious capacity of different individuals in different places and times [12] , [17] , [18] . To overcome these limitations, the impact of disease spreading (and its prevention) has also been studied on different social network structures.…”

Section: Introductionmentioning

confidence: 99%