Investigating the trade-off between self-quarantine and forced quarantine provisions to control an epidemic: An evolutionary approach

Individual preferences, government policy, and COVID-19: A game-theoretic epidemiological analysis

“…In terms of the game between the government and individuals, Khan et al. [29] further complements the limitations of previous scholars. Their topic is fascinating.…”

“…How solve this contradiction (or finding an equilibrium between these two points) is a significant question for future research. A new research issue comes from [ 29 , 30 , 55 ], which proposes that SED is a critical way to solve social efficiency (welfare). In the case of public health emergencies, how to maximize social welfare through government decision-making is an important research direction in the future.…”

Time delay of the appearance of a new strain can affect vaccination behavior and disease dynamics: An evolutionary explanation

“…We also demonstrated the impact of the new strain's introduction on disease dynamics and individual vaccination behavior, as well as the total vaccine coverage considering the time delay. The concept of social efficiency deficit (SED), which is the difference between Nash equilibrium (NE) and the social optimum, is incorporated into our model (SO), to generate a social dilemma, taking into account the vaccine's efficacy and cost ( Ariful Kabir & Tanimoto, 2019 ; Kabir et al., 2021 ; Tori & Tanimoto, 2022 ; Tanimoto, 2019 ; Tanimoto, 2015 ; Tanimoto, 2021 ; Arefin, Kabir, Jusup, Ito, & Tanimoto, 2020 ; Huang, Wang, & Xia, 2020 ; wang & Xia, 2020 ; Khan, Arefin, & Tanimoto, 2022a ; Khan, Arefin, & Tanimoto, 2022b ).…”

Coupled disease-vaccination behavior dynamic analysis and its application in COVID-19 pandemic

“…To overcome these limitations, the impact of disease spreading (and its prevention) has also been studied on different social network structures. Here, the interactions between individuals are modeled as the links in a social network whose nodes are the individuals themselves [19] , [20] . Whether diseases, computer viruses or rumors, their spread is inevitably influenced by the topology and structure of the social network [21] , [22] , [23] .…”