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Using and Extending STEM

Markus Schwehm

Other / New & Noteworthy · Short
Wednesday, 11:30, 25 minutes | Seminarräume 1-3


The Spatiotemporal Epidemiological Modeler (STEM) is designed to be an extensible, flexible and re-usable tool for the creation of spatial and temporal models of emerging infectious diseases. In this talk we will bring this claim to the test. We will use STEM to develop a realistic model of pandemic influenza.

The “swine flu” pandemic of 2009 has puzzled researchers and public health officials all over the world. Classical pandemic influenza models predicted large outbreaks reaching around 80% of the population. Despite initially very fast outbreaks, the real pandemic reached only 20 to 40% of the population. It is not possible to model such a behavior with homogeneous mixing compartmental models like e.g. the SEIR disease model that is included with STEM. If we compare the yearly spread of seasonal influenza with the observed spread of the 2009 pandemic influenza, we can immediately see the difference – a smooth wave for seasonal influenza compared to a popping up of smaller outbreaks throughout the country for pandemic influenza. To model and understand these differences, a spatiotemporal epidemiological modeler like STEM is required.

In order to develop a realistic model for pandemic influenza within the STEM platform, we will use existing components and the extension mechanism to add more and more detail to the pandemic influenza model. We will replace the standard SEIR model with a more sophisticated influenza model that distinguishes the different possible courses of the disease as well as fundamental interventions like isolation of cases and antiviral treatment. Then we will add age structure to the model, because the heterogeneous mixing caused by different behavior of different age groups of the population was key to the understanding of the 2009 pandemic. After adding further interventions like vaccination and seasonal forcing, we extend the model further to provide planning figures for health care agencies.

In the course of this user success story – implementing a professional pandemic influenza preparedness planning tool using STEM – we will review the capabilities of STEM, explore how STEM components can be re-used and how STEM can be extended to provide currently missing functionality.

Dr. Markus Schwehm is founder and CEO of the ExploSYS GmbH, the Institute for Explorative Modeling. He offers consulting and modeling expertise for health care agencies and the pharmaceutical industry in their preparation for emerging diseases and pandemics. To model the spread of directly transmitted diseases like Smallpox, SARS or Influenza, deterministic and stochastic modelling approaches are used. For the realistic modeling of interventions, individual- and network-based discrete event simulation techniques are used. The services include parameter sensitivity studies and the optimization of intervention plans. For fast development of models and rapid delivery of results, Eclipse-based technology like EMF, GEF, BIRT and STEM is applied. His free pandemic influenza preparedness planning tool \'InfluSim\' is used by many health care agencies throughout the world. Customers are health care insititutions in Germany, Switzerland, South Korea and New Zealand.