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

Abstract

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

Keywords

• agent-based modeling
• artificial population
• epidemic process
• computational epidemiology
• systematic review