Abstract for: Enhancing Pandemic Preparedness:Multi-layered Dynamic Simulation Modeling for Intervention Strategies Targeting Indoor Settings

In pandemic preparedness, the effective design of intervention policies is crucial to mitigate the adverse impacts of future pandemics. The epidemiological evidence shows that indoor settings are important sources of transmission. The overall risk of individuals is based on the settings in which they spend their time and the transmission risk associated with these specific settings. However, an incomplete understanding of the contribution of different indoor settings to overall transmission still hampers the assessment of the impact of different intervention strategies. To investigate this problem, we build a multi-layered dynamic simulation modeling framework in which individuals have daily schedules based on their demographic characteristics and interact with each other in different settings (e.g., homes, schools, workplaces, restaurants, etc.). The virus can be transmitted among interacted agents, and the progression of the disease is tracked with an SEIR-type model. As the result, we obtain the progression of the epidemic in the community along with the contribution of each setting type to the overall transmission, so we can test the impact of different interventions on the characteristics of the epidemic. The model will be calibrated, validated and results will be illustrated using the data of the recent SARS-CoV-2 pandemic in the Netherlands.