An agent-based model of the interrelation between the COVID-19 outbreak and economic activities

Kano, Takeshi; Yasui, Kotaro; Mikami, Taishi; Asally, Munehiro; Ishiguro, Akio

doi:10.1098/rspa.2020.0604

Cited by 43 publications

(32 citation statements)

References 35 publications

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“…The fine tuning of the parameters by noting the initial spread of the pandemic will help in predicting the medium term requirements of the public health facilities. However, there are many other aspects of a pandemic that we have not considered in this paper, e.g., the economic or financial implications [21] , [22] .…”

Section: Discussionmentioning

confidence: 99%

An agent-based model of spread of a pandemic with validation using COVID-19 data from New York State

Datta

Winkelstein

Sen

2022

Physica A: Statistical Mechanics and its Applications

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We introduce a novel agent based model where each agent carries an effective viral load that captures the instantaneous state of infection of the agent. We simulate the spread of a pandemic and subsequently validate it by using publicly available COVID-19 data. Our simulation tracks the temporal evolution of a virtual city or community of agents in terms of contracting infection, recovering asymptomatically, or getting hospitalized. The virtual community is divided into family groups with 2-6 individuals in each group. Agents interact with other agents in virtual public places like at grocery stores, on public transportation and in offices. We initially seed the virtual community with a very small number of infected individuals and then monitor the disease spread and hospitalization over a period of fifty days, which is a reasonable time-frame for the initial spread of a pandemic. An uninfected or asymptomatic agent is randomly selected from a random family group in each simulation step for visiting a random public space. Subsequently, an uninfected agent contracts infection if the public place is occupied by other infected agents. We have calibrated our simulation rounds according to the size of the population of the virtual community for simulating realistic exposure of agents to a contagion. Our simulation results are consistent with the publicly available hospitalization and ICU patient data from three distinct regions of varying sizes in New York state. Our model can predict the trend in epidemic spread and hospitalization from a set of simple parameters and could be potentially useful in predicting the disease evolution based on available data and observations about public behavior. Our simulations suggest that relaxing the social distancing measures may increase the hospitalization numbers by some 30% or more.

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Section: Discussionmentioning

confidence: 99%

An agent-based model of spread of a pandemic with validation using COVID-19 data from New York State

Datta

Winkelstein

Sen

2022

Physica A: Statistical Mechanics and its Applications

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“…In fact, ABMs have been used to identify and weight the plausible side effects of NPIs in the current pandemic. For example, Kano et al ( 2021 ) developed a simple ABM to explore the relationship between the spread of COVID-19 and economic activities. In that model, both health (e.g., infection) and economic traits (e.g., employment) of agents are considered, and special attention is paid to how they are related.…”

Section: Agent-based Modelsmentioning

confidence: 99%

Epidemiological models and COVID-19: a comparative view

Iranzo

Pérez-González

2021

HPLS

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Epidemiological models have played a central role in the COVID-19 pandemic, particularly when urgent decisions were required and available evidence was sparse. They have been used to predict the evolution of the disease and to inform policy-making. In this paper, we address two kinds of epidemiological models widely used in the pandemic, namely, compartmental models and agent-based models. After describing their essentials—some real examples are invoked—we discuss their main strengths and weaknesses. Then, on the basis of this analysis, we make a comparison between their respective merits concerning three different goals: prediction, explanation, and intervention. We argue that there are general considerations which could favour any of those sorts of models for obtaining the aforementioned goals. We conclude, however, that preference for particular models must be grounded case-by-case since additional contextual factors, as the peculiarities of the target population and the aims and expectations of policy-makers, cannot be overlooked.

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“…However, simple state division may not be sufficient to meet the requirements of accurate simulation. Some studies use more complex state division [ 17 , 18 , 27 ]. There are different definitions of “agent” in these studies.…”

Section: The Covid19_alps Modelmentioning

confidence: 99%

“…The most common metrics in these studies are infection rate, recovery rate, and mortality rate. On the other hand, some researchers have focused on the intensive care unit (ICU)-bed occupancy [ 13 ] and economic activities [ 17 ].…”

Section: The Covid19_alps Modelmentioning

confidence: 99%

Statistical analysis of the community lockdown for COVID-19 pandemic

Wang

2021

Appl Intell

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As the global pandemic of the COVID-19 continues, the statistical modeling and analysis of the spreading process of COVID-19 have attracted widespread attention. Various propagation simulation models have been proposed to predict the spread of the epidemic and the effectiveness of related control measures. These models play an indispensable role in understanding the complex dynamic situation of the epidemic. Most existing work studies the spread of epidemic at two levels including population and agent. However, there is no comprehensive statistical analysis of community lockdown measures and corresponding control effects. This paper performs a statistical analysis of the effectiveness of community lockdown based on the Agent-Level Pandemic Simulation (ALPS) model. We propose a statistical model to analyze multiple variables affecting the COVID-19 pandemic, which include the timings of implementing and lifting lockdown, the crowd mobility, and other factors. Specifically, a motion model followed by ALPS and related basic assumptions is discussed first. Then the model has been evaluated using the real data of COVID-19. The simulation study and comparison with real data have validated the effectiveness of our model.

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An agent-based model of the interrelation between the COVID-19 outbreak and economic activities

Cited by 43 publications

References 35 publications

An agent-based model of spread of a pandemic with validation using COVID-19 data from New York State

An agent-based model of spread of a pandemic with validation using COVID-19 data from New York State

Epidemiological models and COVID-19: a comparative view

Statistical analysis of the community lockdown for COVID-19 pandemic

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