An extensible spatial and temporal epidemiological modelling system

Daniel Alexander Ford , James H Kaufman and Iris Eiron

Department of Computer Science, IBM Almaden Research Centre, San Jose, CA, 95120, USA

author email corresponding author email

International Journal of Health Geographics 2006, 5:4doi:10.1186/1476-072X-5-4


Published:	17 January 2006

Abstract

Background

This paper describes the Spatiotemporal Epidemiological Modeller (STEM) which is an extensible software system and framework for modelling the spatial and temporal progression of multiple diseases affecting multiple populations in geographically distributed locations. STEM is an experiment in developing a software system that can model complex epidemiological scenarios while also being extensible by the research community. The ultimate goal of STEM is to provide a common modelling platform powerful enough to be sufficient for all modelling scenarios and extensible in a way that allows different researchers to combine their efforts in developing exceptionally good models.

Results

STEM is a powerful modelling system that allows researchers to model scenarios with unmixed populations that are not uniformly distributed and in which multiple populations exist that are being infected with multiple diseases. It's underlying representational framework, a graph, and its software architecture allow the system to be extended by incorporating software components developed by different researchers.

Conclusion

This approach taken in the design of STEM creates a powerful platform for epidemiological research collaboration. Future versions of the system will make such collaborative efforts easy and common.