Mean field game for modeling of COVID-19 spread

Petrakova, Viktoriya; Krivorotko, Olga

doi:10.1016/j.jmaa.2022.126271

Cited by 20 publications

(4 citation statements)

References 20 publications

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“…Функционал вида (11) представляет собой обобщение двух противонаправленных процессов (9) и (10). Здесь…”

Section: вычислительные эксперименты для модели оптимального управленияunclassified

“…С развитием вычислительной техники большую популярность в прогнозировании развития эпидемий приобрели вычислительно более сложные агентные модели [3][4][5][6], которые позволили учитывать неоднородность населения и внешние ограничительные мероприятия. Помимо двух описанных подходов, некоторые исследования посвящены анализу эпидемиологического процесса в других контекстах, например, уравнениям в частных производных [7,8], моделям «среднего поля» [9,10], анализу временных рядов [3,11,12], нейронным сетям и машинному обучению [13].…”

Section: Introductionunclassified

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Approaches to the Simulation of Personal Income Variations During Epidemics

Петракова¹,

Krivorotko²

2023

Успехи Кибернетики / Russian Journal of Cybernetics

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в статье предлагаются две модели, описывающие влияние динамики распространения вируса на такие макроэкономические показатели, как численность рабочей силы и уровень среднедушевого дохода населения. Первая предложенная модель объединяет камерный подход SIR к моделированию распространения эпидемий и урбанистическую модель Лотки-Вольтерры. Вторая обобщает предложенную дифференциальную модель на задачу оптимального управления. Приведено сравнение результатов моделирования между собой и реальными данными на примере Новосибирской области за 2020–2021 гг. Для модели оптимального управления предложено несколько сценариев, которые могут быть использованы при расширении модели для моделирования отличной от рассматриваемой экономико-эпидемиологической ситуации. this study proposes two models representing the impact of the virus spread on such macroeconomic metrics as the labor force size and per capita income. The first model combines the SIR compartmental epidemics modeling and the Lotka-Volterra model. The second one extends the proposed differential model to the optimal control problem. The simulation results are compared with each other and real-world data for the Novosibirsk Region, 2020–2021. We used several scenarios for the optimal control model to further expand the model to other economic and epidemiological conditions.

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“…Функционал вида (11) представляет собой обобщение двух противонаправленных процессов (9) и (10). Здесь…”

Section: вычислительные эксперименты для модели оптимального управленияunclassified

Section: Introductionunclassified

Approaches to the Simulation of Personal Income Variations During Epidemics

Петракова¹,

Krivorotko²

2023

Успехи Кибернетики / Russian Journal of Cybernetics

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“…Another stream of research have explored the notion of mean-field games in the context of epidemics [ 44 ], particularly for social distancing [ 10 , 43 ], vaccination [ 15 , 45 ] and Stackelberg game settings [ 7 , 31 ]. In addition, authors in [ 42 ] examined the impact of asymptomatic infections in a partially observed mean-field game framework.…”

Section: Introductionmentioning

confidence: 99%

Learning to Mitigate Epidemic Risks: A Dynamic Population Game Approach

Hota,

Maitra,

Elokda

et al. 2023

Dyn Games Appl

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We present a dynamic population game model to capture the behavior of a large population of individuals in presence of an infectious disease or epidemic. Individuals can be in one of five possible infection states at any given time: susceptible, asymptomatic, symptomatic, recovered and unknowingly recovered, and choose whether to opt for vaccination, testing or social activity with a certain degree. We define the evolution of the proportion of agents in each epidemic state, and the notion of best response for agents that maximize long-run discounted expected reward as a function of the current state and policy. We further show the existence of a stationary Nash equilibrium and explore the transient evolution of the disease states and individual behavior under a class of evolutionary learning dynamics. Our results provide compelling insights into how individuals evaluate the trade-off among vaccination, testing and social activity under different parameter regimes, and the impact of different intervention strategies (such as restrictions on social activity) on vaccination and infection prevalence.

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“…The major technical di culties arise since we assume that each class has di erent goals with respect to keeping social distance and that the epidemics dynamics for individuals is described through piecewise deterministic stochastic processes that jump from a compartment to the next at random times whose intensity depends on the interaction. To the best of our knowledge, the only attempts in this direction available in the epidemic modeling literature are [17,32,34], where, however, the optimization problem is the same for all classes, thus avoiding a major technical di culty of the model. We also mention [7], where MFGs with change of states are studied.…”

Section: Introductionmentioning

confidence: 99%

A Mean Field Game Model for COVID-19 with Human Capital Accumulation

Ghilli,

Ricci,

Zanco

2022

SSRN Journal

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Mean field game for modeling of COVID-19 spread

Cited by 20 publications

References 20 publications

Approaches to the Simulation of Personal Income Variations During Epidemics

Approaches to the Simulation of Personal Income Variations During Epidemics

Learning to Mitigate Epidemic Risks: A Dynamic Population Game Approach

A Mean Field Game Model for COVID-19 with Human Capital Accumulation

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