The Spatiotemporal Epidemiological Modeler (STEM) Project

About STEM

STEM Banner

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 can aid in understanding and potentially preventing the spread of such diseases.

Policymakers responsible for strategies to contain disease and prevent epidemics need an accurate understanding of disease dynamics and the likely outcomes of preventive 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.

STEM is designed to make it easy for developers and researchers to plug in their choice of models. It comes with a large number of existing compartment models and a new model building framework that allows users to rapidly extend existing models or to create entirely new models. The model building framework provides a simple graphical users interface and automatically generates all of the model code and hot injects the code into STEM at runtime. In many cases, no knowledge of Eclipse or Java is required. The STEM code generator even allows users to build models affected by changes in climate data.

Any STEM model can be run either stochastically or deterministically - simply by switching between solver plugins. Users can choose between many different numerical solvers of ordinary differential equations (including finite difference, Runge-Kutta, 4 solvers from The Apache Commons Mathematics Library, and Stochastic). The stochastic solver computes integer (individual) based transitions picking randomly from a binomial distribution (also from Apach Math). Simulation results can be output with a choice of pluggable loggers, including delimiting files, video loggers, and map loggers. STEM can be used to study quite complex models (for example a model of Dengue Fever with 51 differential equations) and can run global scale simulations. Click here for the complete STEM documentation.

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Getting Started

Resources

Downloadable Scenarios
 Please Read-me first  Installation Instructions
 Documentation  To Learn more about the downloadable scenarios please see the tutorials on the STEM wiki
 (new)Ebola Models  This single archive contains three different projects with several Ebola scenarios. Requires the latest STEM Integration build on or after Sept 26, 2014.
 Dengue Examples  This archive contains three different projects with several dengue fever models and scenarios. Requires any STEM build on or after April 2, 2014.

...more Downloadable Scenarios
Recent Publications
Alexander Falenski, Matthias Filter, Christian Thöns, Armin A. Weiser, Jan-Frederik Wigger, Matthew Davis, Judith V. Douglas, Stefan Edlund, Kun Hu, James H. Kaufman, Bernd Appel, and Annemarie Käsbohrer. A Generic Open-Source Software Framework Supporting Scenario Simulations in Bioterrorist Crises. 
Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science

Hu K, Thoens C, Bianco S, Edlund S, Davis M, Douglas J, and Kaufman JH., 21 Feb 2013  The effect of antibody-dependent enhancement, cross immunity, and vector population on the dynamics of dengue fever. 
Journal of Theoretical Biology, 319:62–74, , doi:10.1016/j.jtbi.2012.11.021

Edlund S, Davis M, Douglas JV, Kershenbaum A, Waraporn N, Lessler J, Kaufman JH. A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence. 
Malaria Journal 2012, 11:331 doi:10.1186/1475-2875-11-331.

...more Publications
Upcoming (and recent) talks
Edlund, S., Hu, K., Kaufman, J.H., Lovett, D., Van Wijgerden, J., Yagci Sokat, K., Poots, A.J Estimating the impact of measles immunization uptake in GP clinics in a North West London Borough 
Epidemics 4, Amsterdam, Holland, 11/21

Davis, M., Edlund, S., Kaufman, J.H. Extending a Spatiotemporal Epidemiological Modeling Tool for Subject Matter Experts 
Epidemics 4, Amsterdam, Holland, 11/20

S. Renly The SpatioTemporal Epidemiological Modeler 
BfR / FDA-Workshop Series on Tools for Food Defense and Safety, Berlin Sept 4-6

J.H. Kaufman and S. Edlund The SpatioTemporal Epidemiological Modeler 
Seminar at Imperial College, London. Friday 21 Jun 2013

Hu, K., et al. Modeling the Dynamics of Dengue Fever 
The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013): Washington D.C.

Edlund S., Davis, M., Kaufman, J. Extending Geospatial Data to Support Epidemiological Modeling 
ACM SIGSPATIAL GIS'12

Kaufman JH (presenter), Davis M, Douglas JV, Edlund S, Hu K, Filter M, Wigger J-F, Thoens C, Weiser AA, Kaesbohrer A, Appel B. The SpatioTemporal Epidemiological Modeler: an open source framework for modeling food-borne disease. 
ISVEE 13, Maastricht

Falenski A (presenter), Thoens C, Filter M, Kaesbohrer A, Appel B, Kaufman JH, Edlund S, Davis M, Douglas JV, Hu K. A community resource for spatial, temporal and food chain epidemiological modelling to assess risks in bio-terroristic or agro-terroristic crisis situations. 
ISVEE 13, Maastricht

...more talks