Difference between revisions of "OHF STEM"

Revision as of 15:43, 7 October 2008

STEM Contents

• Contents
  • What's New
  • Introduction
  • FAQ
  • Installation Guide
  • STEM Design Document
  • Welcome STEM Developers Guide
  • TUTORIALS
  • User Guide (Future)
  • OHF STEM Website
  • Disclaimer Disclaimer

What's New

September 2008...ANALYSIS PERSPECTIVE

Check out the new Analysis and Validation Tutorials. This is a new STEM Perspective that supports a variety of analysis, fitting, and comparison functions across multiple simulations and data sets.

Analysis

1. Estimating Model Parameters from External Data.

2. Epidemic Analysis

3. RMS Comparison between data sets

4. Lyapunov Analysis

Model Parameter Estimation View

Given a set of data (SI, SIR, or SEIR) as a function of time, this perspective provides an estimation of the model parameters for a standard compartment model of the corresponding type. The view provides estimates for:

* beta, the disease transmission rate
* alpha, the recovery rate
* epsilon, the incubation rate
* gamma,the immunity loss rate 

Dynamical Systems View (Lyapunov Analysis)

This view displays the rate of separation in phase space (I vs. S) of the trajectories representing two different data sets or disease models. The rate of separation is then plotted vs time in a second chart. The rate of spread of any infectious disease defines a dynamical system. The Lyapunov exponent of any dynamical system describes the rate of separation of infinitesimally close trajectories in phase space.

Cross Model Comparison (RMS Compare)

Given a data set and the results of a model (or two model generated data sets), the RMS (Root Mean Square) comparison function shows the RMS difference betweent the two as a function of time.

The Epidemic View

This view displays the aggregated data (e.g., S,E,I,R, births, and deaths) as a function of time. It also creates a summary file integrating over the data from all locations in a previously run scenario. It also shows the incidence or "newly infectious count" for the aggregated data.

OTHER IMPORTANT FEATURES ADDED IN 2008

In July...Scenarios Caching

This new feature stores data from a scenario that was loaded recently to re-use when rerunning the scenario. For example, running a scenario for the United States the first time takes some time to read the data from the file system. Using the caching feature, consecutive runs of the same scenario won't reload the data by using the already initialized scenario from the cache. This feature can be toggled using the STEM preferences (Window->Preferences->STEM->Simulation Management->Use scenarios caching). Default is to use the caching system.

In May...A Host of New Features

Among these new features are ones that allow user to

• Create and run multiple Experiments
  • Specify a set or sequence of parameters to run multiple experiments
  • Create a collection of modifiers for a model and link them to a scenario
  • Run a simulation from each newly created modifier in a series of simulations, i.e., to run in batch mode.
• Import data from comma separated variable files and "play back" surveillance data in STEM as an imported disease model
• Export the results of a simulation to comma separated variable files.

Other work was done to

• Provide a new Mixing Model for Transportation that builds on STEM’s two transportation network models
• Fix a major bug in running continent level scenarios
  • Allow users to account for both continuous traffic flow and (coming soon) time-delayed “packets” such as airplane or cargo shipments where the disease can spread on the transport node itself.
• Improve the Editors allowing better drag and drop, deletion, etc. (coming soon - email a scenario!!)
• Improve performance in graphics and other processes.
• Revalidate population data and provide better estimates for locations in 37 countries previously missing population data.

Introduction

What is the Spatiotemporal Epidemiological Modeler (STEM)?

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.

How does it work? The STEM application has built in Geographical Information System (GIS) data for almost every country in the world. It comes with data about country borders, populations, shared borders (neighbors), interstate highways, state highways, and airports. This data comes from various public sources.

STEM is designed to make it easy for developers and researchers to plug in their choice of 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 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.

The original version of STEM was available for downloading on IBM's Alphaworks. It contained easy to follow instructions and many examples (various diseases and maps of the world).

New developers who want to work on STEM can find useful tools, conventions, and design information in the Welcome STEM Developers article.

The STEM code repository is hosted on the Eclipse OHF code repository.

Publications and Presentations on STEM

Ford DA, Kaufman JH, Eiron I, "An extensible spatial and temporal epidemiological modeling system," International Journal of Health Geographics 2006, 5:4 http://www.ij-healthgeographics.com/content/5/1/4 (17Jan2006)

Kaufman JH, Conant JL, Ford DA, Kirihata W, Jones B, Douglas JV, "Assessing the accuracy of spatiotemporal epidemiological models," accepted for publication in Springer Lecture Notes in Computer Science (LNCS), in press. Also to be presented at BioSecure 2008, Biosurveillance and Biosecurity Workshop, Raleigh, NC, Dec 2, 2008.

Kaufman JH, Ford DA, Mesika DA, et al., "Modelling disease spread in space and time: extending and validating an open source tool for public health," accepted for poster presentation at Epidemics: First International Conference on Infectious Disease Dynamics, Asilomar, CA, Dec 1-3, 2008.

About the STEM Team

• James H. Kaufman, Ph.D., is manager of the Healthcare Informatics project in the Department of Computer Science at the IBM Almaden Research Center. He is also a fellow of the American Physical Society. During his career at IBM Research, Dr. Kaufman has made contributions to several fields, including simulation science and magnetic device technology. His scientific contributions include work on pattern formation, conducting polymers, superconductivity, experimental studies of the Moon Illusion, as well as contributions to distributed computing and grid middleware. (kaufman@almaden.ibm.com)

• Daniel Ford, Ph.D., is a Research Staff Member in the Healthcare Informatics Department at IBM Almaden and is currently on assignment at the IBM Watson Research Center in New York. (daford@almaden.ibm.com)

• Stefan Edlund is a software engineer in the Healthcare Research team at IBM Almaden, interested in technologies for the public health domain. Stefan has over 10 years experience in IBM research, with more recent research focusing on the areas of information and content management. Stefan holds a MS degree in computer science from the Royal Institute of Technology, Stockholm. (edlund@almaden.ibm.com)

• Iris Eiron was a researcher at the IBM Almaden Research Lab before relocating to the IBM Research Lab in Haifa, Israel, where she continues to contribute to the development and implementation of a national health care information infrastructure.

• Ohad Greenshpan is part of the Healthcare and Life Sciences group at the IBM Haifa Research Labs. Mr. Greenshpan is an MSc student for Bioinformatics in Ben-Gurion university, concentrating on Protein Folding algorithms and Structural Bioinformatics. Prior to IBM, Mr. Greenshpan was a member of the Genecards team in Weizmann Institute of Science.

• Yossi Mesika is a Research Staff Member in Healthcare and Life Sciences, at the IBM Haifa Research Lab in Haifa, Israel (mesika@il.ibm.com)

• Nelson A. Perez is a software engineer for the Healthcare Informatics Research Group at IBM Almaden. Nowadays, Nelson is mostly interested in software engineering, distributed computing, social computing, and web technologies. He holds an MS degree in computer science from the University of California at Riverside (UCR).

• Roni Ram is a research staff member in the Healthcare and Life Sciences group, IBM Haifa Research Lab (HRL). She received her B.Sc. and M.Sc. in computer sciences from the Technion, Israel Institute of Technology in Haifa, Israel. Ms. Ram joined IBM HRL in 1996 and worked on several projects involving user interfaces and IP telephony. For the last three years, she has been working on interoperability among health care organizations with focus on the public health domain.

• John Thomas is a Java developer for IBM. He was previously one of the lead programmers for the IBM Almaden TSpaces project and also a member of the OptimalGrid Project at the Almaden Research Center. Mr. Thomas can be reached by e-mail (jthomas119@gmail.com)

• Judith V. Douglas supports the STEM Team in documentation and publication of their work. She holds a master's degree from the Johns Hopkins Bloomberg School of Public Health and has published extensively in healthcare informatics. She can be reached by email (judydouglas@comcast.net)