Size Effect in Cellular Automata Based Disease Spreading Model

Orzechowska, Julianna; Fordon, Dawid; Gwizdałła, Tomasz M.

doi:10.1007/978-3-319-99813-8_13

Cited by 4 publications

(4 citation statements)

References 10 publications

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“…The size effect is typical for dynamical system simulations and manifests itself in the dependence of results on the size of the sample. We have observed this effect for disease spreading [11] models, and we can also expect its existence for these calculations. The choice of particular values is done to achieve easy scaling and comparison with the number of nodes in the subsequent sections of Fig.…”

Section: Resultssupporting

confidence: 65%

“…The results are here reproduced for the whole area of Poland, divided into 36 × 36 squares, showing the possible spread of the influenza epidemic. In our earlier paper [11] , we showed, taking into account the same area of inhabitance as in this paper, that the model requires special attention, primarily due to the existence of so-called size effects.…”

Section: Introductionmentioning

confidence: 81%

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Viral disease spreading in grouped population

Gwizdałła

2020

Computer Methods and Programs in Biomedicine

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Highlights Epidemic curves created by using an agent-based model are presented. The network of interactions, and thus the possibility of infection, is modeled with the scale-free Barabasi-Albert model. Modifications based on whether these interactions belong to a particular group are proposed. A simple model of passing an infection via a direct interaction is proposed. The influence of the network creation method, division into different numbers of groups and different times of intervention is presented. The results are shown for two cases: the well-known influenza virus and the recently reported COVID-19.

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Section: Resultssupporting

confidence: 65%

Section: Introductionmentioning

confidence: 81%

Viral disease spreading in grouped population

Gwizdałła

2020

Computer Methods and Programs in Biomedicine

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“…The Web of Science database reveals over 80,000 and over 110,000 papers related to this topic registered in 2020 and in January–November 2021, respectively, in contrast to only 19 papers in 2019. Among them, only several [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ] are based on the cellular automata technique [ 21 , 22 , 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

Does Social Distancing Matter for Infectious Disease Propagation? An SEIR Model and Gompertz Law Based Cellular Automaton

Biernacki

Malarz

2022

Entropy

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In this paper, we present stochastic synchronous cellular automaton defined on a square lattice. The automaton rules are based on the SEIR (susceptible → exposed → infected → recovered) model with probabilistic parameters gathered from real-world data on human mortality and the characteristics of the SARS-CoV-2 disease. With computer simulations, we show the influence of the radius of the neighborhood on the number of infected and deceased agents in the artificial population. The increase in the radius of the neighborhood favors the spread of the pandemic. However, for a large range of interactions of exposed agents (who neither have symptoms of the disease nor have been diagnosed by appropriate tests), even isolation of infected agents cannot prevent successful disease propagation. This supports aggressive testing against disease as one of the useful strategies to prevent large peaks of infection in the spread of SARS-CoV-2-like diseases.

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“…The Web of Science database reveals over 80,000 and over 110,000 papers related to this topic registered in 2020 and in January-November 2021, respectively, in contrast to only 19 papers in 2019. Among them, only several [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] are based on cellular automata technique [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Does social distancing matter for infectious disease propagation? A SEIR model and Gompertz law based cellular automaton

Biernacki,

Malarz

2022

Preprint

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In this paper, we present stochastic synchronous cellular automaton defined on a square lattice. The automaton rules are based on SEIR model with probabilistic parameters gathered from real-world data on human mortality and SARS-CoV-2 disease characteristics. With computer simulations, we show the influence of the neighbourhood radius on the number of infected and deceased agents in the artificial population. The increase of the neighbourhood radius favors the spread of the epidemic. However, for a large range of interactions of exposed (who are both inward for and/or untested against) agents, even isolation of infected agents cannot prevent successful disease propagation. This supports aggressive testing against disease as one of the useful strategies preventing large peaks of infection in SARS-CoV-2-like disease spreading.

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Size Effect in Cellular Automata Based Disease Spreading Model

Cited by 4 publications

References 10 publications

Viral disease spreading in grouped population

Viral disease spreading in grouped population

Does Social Distancing Matter for Infectious Disease Propagation? An SEIR Model and Gompertz Law Based Cellular Automaton

Does social distancing matter for infectious disease propagation? A SEIR model and Gompertz law based cellular automaton

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