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The SpatioTemporal Epidemiological Modeler: An open source framework for modeling infectious and vector borne diseaseby James H. Kaufman, Stefan Edlund – IBM Research
The rise of global economies in the 21st century, the rapid national and international movement of people, and the increased reliance of developed countries on global trade all greatly increase the potential and possible magnitude of a pandemic. Global epidemics may result from global climate change, vector-borne diseases, food-borne illness, new naturally occurring pathogens, or bio-terrorist attacks. What can public health officials and scientists possibly do to protect populations from emerging disease or to implement better response measures? While the speed of modern transportation amplifies the threat, the near real time capability of modern information technology (I/T) can provide opportunities for great predictive capability and pro-active containment.
The SpatioTemporal Epidemiological Modeler (STEM) freely available through the Eclipse Foundation (http://www.eclipse.org) provides a modern “plug and play” software architecture that offers many advantages for software development. STEM represents the world as “a graph”. STEM offers toolsets for developing sophisticated simulations of disease spread. Data sets describing the geography, transportation systems, and population for the 244 countries and dependent areas, disease modeling mathematics, model comparison and cross validation tools.
As an Eclipse application, STEM is also designed to support collaborative community contribution to a growing library of data required to model existing and emerging disease threats. Recently STEM has been extended to support modeling of vector borne, zoonotic, and foodborne disease. In this talk we will describe the STEM framework and present a model of MMR vaccination developed with NHS Ealing and NIHR. We will also describe models of zoonotic and foodborne disease developed with the German Federal Institute for Risk Assessment and demonstrate new features in STEM designed to simplify rapid creation of entirely new models.