Spatiotemporal Epidemiological Modeler
| Company type | Free software platform |
|---|---|
| Industry | Software, Epidemiology |
| Predecessor | IBM Research (initial creator) |
| Founder | IBM Research |
Area served | Worldwide |
| Products | Epidemiological modeling software |
| Owner | Eclipse Foundation |
| Website | www |
The Spatiotemporal Epidemiological Modeler (STEM) is a free software platform provided by the Eclipse Foundation. Initially created by IBM Research, STEM serves as a versatile framework and development environment designed for constructing and applying spatial and temporal infectious disease models. It utilizes a component-based software architecture aligned with the OSGi standard, implemented through the Eclipse Equinox runtime. This modular setup offers discrete software units—known as Eclipse "plug-ins" or "extensions"—which encapsulate both code and data, allowing for independent modification, extension, reuse, or substitution.
The STEM system includes comprehensive plug-ins covering all 244 countries and territories as classified by the ISO3166 geographic standard. These plug-ins provide worldwide geographic, population, demographic information, along with fundamental epidemiological compartmental models of diseases. Additional modules capture inter-regional linkages such as adjacency and transportation networks involving roads and air routes.
Within the platform, the world is modeled as a graph structure where nodes denote geographical regions and edges signify their interconnections. Both nodes and edges carry associated data and models through the use of the Eclipse Modeling Framework (EMF). This graph-centric methodology supports model assembly: predefined country-specific subgraphs can be combined using a drag-and-drop interface, while new disease transmission pathways can be incorporated by adding connecting edges. STEM promotes collaborative efforts by allowing users to develop, share, and enhance reusable models and scenarios. As an open source initiative, it invites the creation of custom plug-ins for data sets and models, fostering community-driven improvements.