In order to create effective policies and response plans for pandemics, public health officials need the ability to track how both seasonal flu and emerging strains like H1N1 can spread. If you think about it, an infectious disease spreading through a population is analogous to a storm moving across the ocean. Like weather, infectious disease can be studied and forecast using mathematical models.
For the past few years, we have been working on a new tool, the Spatio-Temporal Epidemiological Modeler or STEM, that’s designed to help public health officials and scientists model infectious disease scenarios. STEM can help us test and implement better response measures and protect populations from emerging disease. Epidemiologists have developed a wide range of mathematical tools to predict the future state of a disease in space and time. To rapidly develop new models, and to assess possible responses, we need a community of scientists and public health officials able to bring to bear freely available, open, technologies. This community should be able to reuse, share, and extend reference data and models, which allows users to rapidly build on each other’s work. Eventually, the near real-time monitoring made possible by an electronic health record will provide epidemiologists with up-to-date input for new dynamic mathematical models of infectious diseases.
In the past, the best numerical studies of epidemiology have been conducted in university research groups using custom scientific software. While this approach has produced a foundation of knowledge that can be drawn upon as the field advances, the traditional development of scientific software may be too slow to respond on a time scale relevant to unexpected pandemics. With that in mind, STEM is an open source tool that is freely available through the Eclipse Foundation. Any scientist or researcher may contribute to and build on its growing library of mathematical models, computer code, and denominator data. As a part of Eclipse, STEM also provides a platform for collaboration and open exchange of models and ideas. Written in Java, STEM is Platform independent and available in versions for Microsoft, Apple, and Linux operating systems. It already contains denominator data for the entire world and it allows users to model the entire world on a fast workstation.
We encourage you to try it out and contribute to its growing library of models. You can also read more about STEM on Eclipse and in this paper that we recently published on infectious disease modeling.