Speakers
Description
In a pandemic, alongside biological factors, societal interactions, cognitive behaviours, and personal attitudes can also influence the progression of an epidemic. For instance, people's compliance to vaccination or non-pharmaceutical measures rely on their social links as well as their individual opinions. How people connect with each other and their clustering structure also adds heterogeneity and complexity to disease dissemination. Thus, modeling frameworks should explicitly incorporate these aspects to enhance realism, accuracy, and predictive power. The key challenges exist in how to formulate and develop such models, rigorously validate and evaluate them, as well as feeding appropriate data to support public health strategies. Innovative modeling efforts may draw on a wide range of mathematical approaches, incorporating differential equations models to capture collective behaviours, network models to represent realistic contact patterns or structures, and agent-based models to simulate local feedback, or integrations thereof. Recently, there has been an increasing interest in combining social characteristics, cognitive choices, and epidemic spread. This mini symposium will catalyze cross-methodological conversations and provide a platform to showcase and highlight how novel approaches, techniques, and findings in this field may jointly inform robust and actionable responses for curbing infectious diseases.
