Infectious disease modeling and computational power have evolved such that large-scale agent-based models (ABMs) have become feasible. However, the increasing hardware complexity requires adapted software designs to achieve the full potential of current high-performance workstations. We have found large performance differences with a discrete-time ABM for close-contact disease transmission due to data locality. We believe our conclusions to be valid for a wide range of infectious disease ABMs. We recommend that future studies evaluate the impact of data management, algorithmic procedures and parallelization on model performance.
This project is based on a free open source individual-based modeling system for close-contact disease transmission, called indismo, developed at the University of Antwerp and Hasselt University, Belgium. The software provides data structures and algorithms to model disease spreading in synthetic populations to compare and discuss model performance. We provide the source code, a user manual and extra documentation. More details on the project and results obtained with the software can be found in: