Agent-based modelling for public health

Background

Agent-Based Modelling (ABM) and simulation have been used in public health for some years now. However, we have observed a major increase in the development, applications, use and contributions of ABM in public health during the pandemic. ABM has been widely used in modelling disease transmission at various scales (local, regional and national), and settings (i.e. public transit, mass gathering, hospitals and long term care facilities), assessment of public health measures, vaccine uptake, individuals’ behaviour towards public health measures, public health information dissemination and propagation and public health logistics. Simultaneously, hardware and software technologies that enable the development and use of ABM have been advancing and thus helping the development of more detailed ABM with a large agent population even more possible. The use of ABM in public health is not free of its challenges theoretical, technical, data, validity and calibration challenges.

Goals

The main goals of the Agent-Based Modelling for Public Health speaker series are:

• Knowledge sharing among the ABM modelling community and public health experts;

• Learning about advances in ABM in public health;

• Exchanging best practices and lessons learned in the development and use of ABM in public health during the COVID-19 era; and

• Building and strengthening the ABM modelling and user networks.

Target Audiences

• Mathematics for Public Health Network researchers
• Public health professionals and decision-makers interested in and using ABM
• Graduate and undergraduate students
• Agent-based modelling community interested in public health