Scaling of agent-based models to evaluate transmission risks of infectious diseases.

ABSTRACT: The scaling behaviour of agent-based computational models, to evaluate transmission risks of infectious diseases, is addressed. To this end we use an existing computational code, made available in the public domain by its author, to analyse the system dynamics from a general perspective. The goal being to obtain deeper insight into the system behaviour than can be obtained from considering raw data alone. The data analysis collapses the output data for infection numbers and leads to closed-form expressions for the results. It is found that two parameters are sufficient to summarize the system development and the scaling of the data. One of the parameters characterizes the overall system dynamics. It represents a scaling factor for time when expressed in iteration steps of the computational

SUBMITTER: Thomas PJ 

PROVIDER: S-EPMC9807651 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature