How and when to combine system dynamics and agent-based simulation for modelling infectious diseases

Simulation modelling has been used extensively in epidemiology to study the transmission dynamics of infectious diseases and the impacts of different interventions. Recently, a large and growing body of literature has adopted system dynamics (SD) or agent-based modelling (ABM), to investigate the spread of COVID-19 and assist policymakers in making decisions on the most effective strategies to control the pandemic.

Some problems may require modellers to look at different levels and dimensions of a system which is composed of interactive and interconnected constituents with dynamic behaviours. Hybrid simulation models that combine the advantages of SD and ABM can be useful in finding the best solution for such problems. Despite the growing interest in this approach, developing hybrid SD-AB models has been a challenging task as guidance on when and how they should be combined is scanty.

This may limit the use of hybrid models in addressing important questions on infection prevention and control. In this session, we will present several designs for combining SD and ABM, provide examples of epidemic hybrid models from literature where available, and suggest relevant questions for modelling infectious diseases that may benefit from hybrid modelling. We will also discuss the design of the hybrid model that we develop to investigate the impact of staff sharing upon the spread of COVID-19 within a network of care homes.