Formal scientific modeling: a case study in global health

January 12 to January 16, 2026

at the

American Institute of Mathematics, Pasadena, California

organized by

Nina Fefferman, Tim Hosgood, and Mary Lou Zeeman

This workshop, sponsored by AIM, the NSF, the Topos Institute, and the US NSF Center for Analysis and Prediction of Pandemic Expansion, will consider how category-theoretic foundations for modeling as decision support for multidisciplinary collaboration might advance insights into pandemic science. Multidisciplinary modeling is extremely useful and also extremely difficult (for many reasons). By taking the very concept of "building a model" as itself a sort of model, and phrasing this in the formal mathematical language of (double) category theory, we can develop systems that greatly improve our capabilities for collaborative modeling.

The workshop will bring together a wide range of research communities: category theory, software engineering, dynamical systems, data science, epidemiology, infectious disease modeling, medical geography, behavioral psychology, social and urban networks, and economics. Driving questions for the workshop include:

How to identify features that put populations at increased risk of disease.
What causes increased vulnerability to adverse outcomes from disease.
What resources are needed to appropriately withstand disease, that could be the focus of well-informed and tailored monitoring and mitigation strategies for practical deployment.

The ability to detect and respond to an incipient disease outbreak is one of the great challenges in modern health security. However, even for seemingly well-understood pathogens, for which we have many historical comparators, there are some fundamental complexities that hamper our surveillance and rapid response capabilities. One of the most tantalizing of these complexities lies in the layered synergies among different factors that all contribute to shaping how and when the early spread of an infection in a human population becomes detectable to public health practitioners. Moreover, the disciplines that work towards understanding and monitoring each of these factors can be entirely distinct, with few tools for cross-disciplinary collaboration.

This is exactly the situation for which the category-theoretic tools for decision support and collaborative modeling being developed and implemented by the Topos Institute (currently publicly available in alpha version) are designed. By putting extra work up front in formalising the logical structures and decisions made in building a model, it means that the outcome of the (necessary and powerful) person-to-person collaboration and discussion is now a formal artifact — a model of a double theory — allowing us to design software that can highlight those aspects of the model that need further clarification or specification.

This event will be run as an AIM-style workshop. Participants will be invited to suggest open problems and questions before the workshop begins, and these will be posted on the workshop website. These include specific problems on which there is hope of making some progress during the workshop, as well as more ambitious problems which may influence the future activity of the field. Lectures at the workshop will be focused on familiarizing the participants with the background material leading up to specific problems, and the schedule will include discussion and parallel working sessions.

Space and funding is available for a few more participants. If you would like to participate, please apply by filling out the on-line form no later than August 12, 2025.

Before submitting an application, please read the description of the AIM style of workshop.

For more information email workshops@aimath.org

Plain text announcement or brief announcement.