Modeling is the process of creating a simplified representation of a real-world system to understand it, explain it, or predict its behavior. Considering the complexities of crises, such as outbreaks and natural hazard events, models and simulations are important tools for prevention and response. There is growing recognition that we need to work across disciplines and modeling practices – and learn from each other – to address complex challenges. Because of this, the PDPC has launched the Modeling for Preparedness initiative, starting with three initial problem-driven, interdisciplinary modeling projects (PRISM, ALARM and OPTICAL) that start in January 2026 and will be supported for a duration of two years.

PRISM: Pandemic Response through Integrated Simulation and Modeling

The PRISM modeling project focuses on modeling to inform integrated advice for pandemic response. PRISM will work in collaboration with the pandemic modeling work package team in the ZonMw-funded UNITY project to develop and deploy models that simulate and compare pandemic policy options. The goal is to establish a generic individual-based model (IBM) framework for human-to-human transmitted respiratory infections in the Netherlands. This framework will be able to simulate both pharmaceutical and nonpharmaceutical interventions, potentially tailored to specific geographic regions, with consideration of the effectiveness and uptake across different regions and demographic groups. In addition, the model will be designed to facilitate rapid adaptations to expert and stakeholder inputs about key uncertainties, such as disease biology and intervention uptake and effects.

Project team: Luc Coffeng and Sake de Vlas (Erasmus MC); Postdoctoral researcher: Scott Dahlgren (Erasmus MC), additional research collaboration with PingPing Song and Erin Frame (Erasmus MC) (in collaboration with the UNITY project).

ALARM: Acquired social LeArning Risk Management

ALARM tackles a key challenge in flood risk management: how to design strategies that reduce community exposure to floods by considering not only physical infrastructure, but also how people and institutions change their behavior over time. The project focuses on understanding and modeling how these social and behavioral responses evolve both immediately after major disasters and in the years that follow. By connecting social and behavioral aspects with community and governmental preparedness measures in the context of climate change, this project will contribute to the development of decision-support tools that integrate technical and social dimensions. The project also leverages ongoing work of the Behavioral Digital Twin of Rotterdam for flooding events (Resilient Hydro Twin Project).

Project team: Maria Nogal, Srijith Balakrishnan, Erica Arango (TU Delft); Clara Egger (Erasmus University Rotterdam); Vittoria Nespeca (Leiden University); Postdoctoral researcher to be announced.

OPTICAL: Optimized Planning and strategies Integration for flood Alleviation

OPTICAL focuses on improving how flood protection measures are planned and placed. The project develops and tests a decision-making framework to help determine where retention basins and temporary flood barriers can be most effective in reducing flood impacts. It takes into account not only flood reduction, but also competing land-use needs and both short- and long-term economic costs. By combining flood modeling with spatial and economic analysis, OPTICAL helps decision-makers understand trade-offs between cost, feasibility, and flood protection benefits. The approach is designed to be scalable, practical to apply, and robust to uncertainty, and will be tested in real flood-prone regions such as Limburg, in close collaboration with local stakeholders.

Project team (developing): Davide Wuthrich, Maria Pregnolato, Theo Chatzivasileiadis (TU Delft); Postdoctoral researcher: Walter Box (TU Delft).

Outlook on cross-disciplinary modeling

Through the PDPC Modeling for Preparedness initiative, the PDPC aims to advance integrated and interdisciplinary modeling approaches to support decision-making, both for long-term risk analysis and mitigation as well as to inform response to extreme events. Moreover, the projects also aim to facilitate cross-disciplinary learning, explore approaches to integrating knowledge both within and in relation to modeling, and foster an interdisciplinary modeling Community of Practice. In fact, in October 2025, the Modeling for Preparedness initiative organized a technical workshop on dealing with uncertainty in modeling for preparedness that involved 28 researchers from TU Delft and Erasmus MC for a cross-disciplinary exchange of approaches to dealing with modeling uncertainty in technical terms.