Forecasting of COVID-19 Dynamics by Agent-Based Model
Lecture Notes on Data Engineering and Communications Technologies
; 158:420-429, 2023.
Article
in English
| Scopus | ID: covidwho-2293492
ABSTRACT
The novel coronavirus pandemic has continued to spread worldwide for more than two years. The development of automated solutions to support decision-making in pandemic control is still an ongoing challenge. This study aims to develop an agent-based model of the COVID-19 epidemic process to predict its dynamics in a specific area. The model shows sufficient accuracy for decision-making by public health authorities. At the same time, the advantage of the model is that it allows taking into account the stochastic nature of the epidemic process and the heterogeneity of the studied population. At the same time, the adequacy of the model can be improved with a more detailed description of the population and external factors that can affect the dynamics of the epidemic process. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Agent-based model; Agent-based simulation; COVID-19; Epidemic model; Epidemic process simulation; Infectious disease simulation; Autonomous agents; Computational methods; Decision making; Dynamics; Simulation platform; Stochastic models; Stochastic systems; Agent based simulation; Coronaviruses; Decisions makings; Epidemic modeling; Epidemic process; Infectious disease; Process simulations
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
Lecture Notes on Data Engineering and Communications Technologies
Year:
2023
Document Type:
Article
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