Pandemic Dynamics with Social Effects: Rapid Model Prototyping with Fuzzy Logic

The human behavior aspect of pandemic prevention and mitigation involve uncertainties manifested as a range of responses, from the extreme to the indifferent. Relationships between variables influencing human behavior are usually described qualitatively, and as such do not suffice for stock and flow models. These uncertainties can slow down the modelling process considerably, thus limiting the effectiveness of a model-based approach in time-critical studies such as an impending pandemic outbreak. Our proposed approach utilizes fuzzy modelling concepts integrated within the system dynamics modelling framework to create a rapid model prototyping process of developing a pandemic dynamics model. This can facilitate quantitative analysis for policy making in pandemic mitigation interventions. We use the recent H1N1 pandemic in Singapore as a case example to demonstrate the practical usefulness of our approach.