IBM ha desarrollado un modelo de simulación en el espacio y en el tiempo de epidemias denominado STEM (Spatiotemporal Epidemiological Modeler). El modelo pretende proporcionar una herramienta para comprender y prevenir la dinámica de las enfermedades infecciosas emergentes en EEUU. Utiliza tecnologías Java y GIS y está disponible para Windows y Linux. El modelo puede obtenerse gratuitamente, al menos para su evaluación, pero no se ha liberado su código fuente (una pena dada su potencial utilidad en otras áreas geográficas). De hecho, la web no aclara el tipo de licencia de este software y en cambio presenta un cuestionario para potenciales usuarios donde les interroga sobre su posible interés en obtener un tipo u otro de licencia (el objetivo es evaluar el interés de una licencia comercial). Esperemos que esta cuestión se aclare y STEM pueda tener la máxima difusión y utilidad posibles.
De la web de STEM:
What is the Spatiotemporal Epidemiological Modeler?
The Spatiotemporal Epidemiological Modeler (STEM) tool is designed to help scientists and public health officials create and use spatial and temporal models of emerging infectious diseases. These models could aid in understanding, and potentially preventing, the spread such diseases.
Policymakers responsible for creating strategies to contain diseases and prevent epidemics need an accurate understanding of disease dynamics and the likely outcomes of preventative actions. In an increasingly connected world with extremely efficient global transportation links, the vectors of infection can be quite complex. STEM facilitates the development of advanced mathematical models, the creation of flexible models involving multiple populations (species) and interactions between diseases, and a better understanding of epidemiology.
How does it work?
The STEM application has built in Geographical Information System (GIS) data for every county in the United States. It comes with data about county borders, populations, shared borders (neighbors), interstate highways, state highways, and airports. This data comes from the public U.S. census TIGER files. STEM is designed to make it easy for developers and researchers to plug in their own models. It comes with spatiotemporal Susceptible/Infectious/Recovered (SIR) and Susceptible/Exposed/Infectious/Recovered (SEIR) models pre-coded with both deterministic and stochastic engines. The parameters in any model are specified in XML configuration files. Users can easily change the weight or significance of various disease vectors (such as the weights of highways, shared borders, airports, etc). Users can also create their own unique vectors for disease. Further details are available in the user manual and design documentation.
