Contributing Institutes

Institute of Epidemiology and Social Medicine

Epidemiology deals with the frequency, spread and determinants of health and disease by studying the population or population groups. It analyzes probable correlations between risk factors, health burdens or living conditions and the occurrence of diseases.

The institute of epidemiology and social medicine uses modern statistical and epidemiological methods to generate evidence to evaluate the consequences of contact with infectious agents and/or changes in the immune system on the burden of communicable and non-communicable diseases. This includes the areas of description, understanding pathogenesis, prevention, diagnosis, prognosis, and effects of interventions.

Infectious disease modeling is a fundamental tool within epidemiology, answering relevant public health questions and providing guidance to decision-makers in various contexts, including in healthcare settings and during epidemic and pandemic situations.

Institute of Virology

Research at the Institute of Virology Munster (IVM) focuses on the question of how respiratory viral pathogens such as influenza viruses or SARS coronaviruses interact with the host cell and the immune system for efficient viral replication. The institute is organized in different subgroups, addressing different questions ranging from the importance of intracellular signal transduction processes or the role of post-translational modifications of viral and cellular proteins, up to projects on the oncolytic activity of influenza viruses and general molecular aspects of acute and chronic inflammatory responses. The aim of the work is to learn more about viral replication strategies through knowledge of the cellular processes that control virus replication, and possibly to find new points of attack, both for antiviral or tumor therapy. The institute is home of the management office of the nationwide One-Health Platform, partially funded by the BMBF. In this context the institute was also active in joint projects aiming to develop flexible, easy-to-use simulation frameworks for constructing, executing, and analyzing agent-based infectious disease models, in part funded by the BMBF and the state of NRW (Epipredict, Copredict, VIRAL.NRW). The IVM is among the founding members of IMMIDD. In addition to the geno- and phenotypic characterization and risk assessment of circulating and new respiratory pathogens, the modelling of possible epidemic or pandemic outbreaks of viruses such as SARS-CoV or influenza viruses is one of the essential building blocks for effective civil protection. This is to be addressed in the IMMIDD in collaboration with other groups.

Institute for Analysis and Numerics

The research group "Applications of PDEs" focuses on the modeling and numerical simulation of complex systems, the use of high-performance computing (HPC), and the development of open-source research software. Advanced models and numerical methods enable more precise analyses and more reliable predictions.

One of the group's main areas of research is the modeling of infectious diseases, particularly the integration of additional features and data to improve forecasting accuracy. The spatial spread of infections presents a mathematical challenge, as it cannot be described solely using classical distance measures. Travel behavior influences contacts, meaning that distances cannot be considered purely in Euclidean terms. For example, in a relevant mobility model, a nearby village may be effectively farther away than a larger city with direct transportation links. The analysis of such spatial effects reveals similarities to traveling waves but goes beyond classical model assumptions.

Another key aspect is numerical simulation and the efficient analysis of large datasets. Computing model predictions requires methods that balance accuracy and computational cost. In particular, quantifying uncertainty poses an additional challenge, as it often significantly increases computational demands. The development of improved numerical methods and the use of HPC help address these challenges.

In the past, the group has mainly investigated questions related to the spatial and age-dependent dynamics of infectious diseases, often in the context of student projects. By extending classical ODE models with partial differential equations, spatial factors such as vegetation, topography, and transportation infrastructure were incorporated into simulations. Considering mobility through private and public transportation led to a graph-based modeling approach.

The research group continuously works on mathematical questions arising from practical challenges. The modeling of infectious diseases remains particularly relevant in an increasingly interconnected world.

Institute for Geoinformatics

Geoinformatics is the science of modelling spatiotemporal processes computationally. Infectuous disease spread is inherently a spatiotemporal process, where interactions between persons play a role as well as influences from the environment on them. Data on human activity and mobility, traffic, origin-destination data from census surveys, or even weather data or satellite imagery may inform the modelling and prediction of disease transmissions.

In an ongoing PhD research we investigate the relationship between COVID-19 incidences and activity data obtained from Mapbox and origin-destination matrices from census data, using spatial statistical methods (generalized linear mixed models with explicit spatially correlated random effects). We hope that the interaction with other IMMIDD members will help us understand the models we fit, and that we may help others understanding explicit spatial and spatiotemporal effects.

Department of Information Systems

The Department of Information Systems (Institut für Wirtschaftsinformatik) deals with the design and application of information systems. These systems form the socio-technical interface between people and technology.

In the context of infectious disease research, information systems specialists develop systems that can help to better understand and combat outbreaks of infection.

One example of this is the BMBF-funded OptimAgent project, in which information systems specialists at the University of Münster are helping to develop a Germany-wide simulation framework. This system enables researchers to test intervention strategies in a virtual population and evaluate their effectiveness.

In the EpiPredict project, which was completed in 2022, a simulation platform was developed that can be used without programming knowledge, making infectious disease modeling accessible to a much wider audience.

IMMIDD is an excellent initiative to merge the technical expertise of information systems with applied infection research from other disciplines. This enables the development of user-oriented and highly relevant systems.

Institute of Theoretical Physics

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