Limitations in creating artificial populations in agent-based epidemic modeling: a systematic review DOI Creative Commons

Irina I. Maslova,

Alexander I. Manolov, Oksana E. Glushchenko

et al.

Journal of microbiology epidemiology immunobiology, Journal Year: 2024, Volume and Issue: 101(4), P. 530 - 545

Published: Sept. 9, 2024

Introduction. The key step in agent-based modeling of epidemics, which allows researchers to take into account individual characteristics people, is the creation an artificial population. main difficulty this procedure finding a balance between detail population description and computational efficiency calculations. aim objectives review: Critically analyze summarize current evidence on how create populations; evaluate limitations advantages available approaches solving various problems epidemiology. Materials methods. An analysis literature sources devoted has been performed. focused algorithms for creating with given level human respiratory infections. Results. populations are generalized. principles realization interaction agents revealed: by means networks contacts basis taking movement locations. first approach most computationally efficient simple; second better change behavior during development epidemic process. Conclusion. Agent-based optimal tool selecting best scenario control investigating role people epidemics. When population, it important include model factors that can be targeted control. A significant limitation lack factual data structure, but overcome using indirect data.

Language: Английский

Agent-based modeling of spreading infectious diseases: state-of-the-art DOI Open Access
N. V. Saperkin

Fundamental and Clinical Medicine, Journal Year: 2024, Volume and Issue: 9(3), P. 109 - 119

Published: Sept. 27, 2024

Agent-based simulation modeling provides additional opportunities to study the patterns of pathogen spread among populations, taking into account complexity and stochasticity epidemic process. is considered as a computational approach in which agents with predefined characteristics can interact each other environment according pre-specified rules. Here I consider historical background agent-based field infectious diseases, describe basic definitions classifications, discuss strengths weaknesses modeling. The article details four interconnected main components that are subject modeling: disease features (transmission routes, process), population, movement patterns, environment. also addresses need for validation models. reader's attention drawn following important models: ability model various scenarios on different scales (global, national, regional); use them epidemiological studies when controlled experiments impossible (e.g., consequences non-compliance preventive measures, «cultural pathogens»); make decisions depending their characteristics; consideration behavioral aspects at individual level; mobility social contacts agents. models well-suited modeling, particularly surveillance, including emerging infections COVID-19).

Language: Английский

Citations

1

Limitations in creating artificial populations in agent-based epidemic modeling: a systematic review DOI Creative Commons

Irina I. Maslova,

Alexander I. Manolov, Oksana E. Glushchenko

et al.

Journal of microbiology epidemiology immunobiology, Journal Year: 2024, Volume and Issue: 101(4), P. 530 - 545

Published: Sept. 9, 2024

Introduction. The key step in agent-based modeling of epidemics, which allows researchers to take into account individual characteristics people, is the creation an artificial population. main difficulty this procedure finding a balance between detail population description and computational efficiency calculations. aim objectives review: Critically analyze summarize current evidence on how create populations; evaluate limitations advantages available approaches solving various problems epidemiology. Materials methods. An analysis literature sources devoted has been performed. focused algorithms for creating with given level human respiratory infections. Results. populations are generalized. principles realization interaction agents revealed: by means networks contacts basis taking movement locations. first approach most computationally efficient simple; second better change behavior during development epidemic process. Conclusion. Agent-based optimal tool selecting best scenario control investigating role people epidemics. When population, it important include model factors that can be targeted control. A significant limitation lack factual data structure, but overcome using indirect data.

Language: Английский

Citations

0