ORIGINAL PAPER Interactive spatiotemporal modelling of health systems: the SEKS–GUI framework Hwa-Lung Yu Æ Alexander Kolovos Æ George Christakos Æ Jiu-Chiuan Chen Æ Steve Warmerdam Æ Boris Dev Ó Springer-Verlag 2007 Abstract This paper describes the spatiotemporal epist- ematics knowledge synthesis and graphical user interface (SEKS–GUI) framework and its application in medical geography problems. Based on sound theoretical reasoning, the interactive software library of SEKS–GUI explores heterogeneous (spatially non-homogeneous and temporally non-stationary) health attribute distributions (disease inci- dence, mortality, human exposure, epidemic propagation etc.); expresses the health system’s dependence structure using (ordinary and generalized) spatiotemporal covariance models; synthesizes core knowledge bases, empirical evi- dence and multi-sourced system uncertainty; and generates a meaningful picture of the real-world system using space– time dependent probability functions and associated maps of health attributes. The implementation stages of the SEKS–GUI library are described in considerable detail using appropriate screens. The wide applicability of SEKS–GUI is demonstrated by reviewing a selection of real-world case studies. Keywords Medical geography  Health  Disease  Epidemic  Uncertainty  BME  Interdisciplinary 1 Introduction The study of a health system’s attributes (e.g., mortality pattern, disease propagation velocity, exposure distribu- tion, and system performance indicators) is an important affair in medical geography that can play a vital role in a large number of public health situations, including popu- lation risk analysis, public awareness, health policy and decision making (Haggett 2000; Cromley and McLafferty 2002; Gatrell 2002). A health system typically involves a number of interacting agents and the associated knowledge bases (Christakos and Hristopulos 1998). In this context, some of the health attributes of interest are emergent properties that manifest the composite geographical-tem- poral organization of the system. The study of a health system may cross disciplines and is basically a knowledge synthesis affair that combines (a) a stochastic theory of space–time dependence representation under conditions of multi-sourced uncertainty with (b) an epistematics meth- odology that is the fusion of human teleology and evolu- tionary epistemology. The spatiotemporal random field (S/TRF) model of stochastics aims to study the properties of a health system as a whole and connect them to causal relations and space– time patterns under conditions of uncertainty. S/TRF tools include spatiotemporal probability density functions (PDF), ensemble averages (ordinary and generalized covariance and variogram functions), and local scale het- erogeneity characteristics (spatial and temporal orders). A detailed presentation of stochastics, in general, and the S/ TRF model, in particular, can be found in Christakos (1991, 1992), Christakos and Hristopulos (1998) discuss several of its applications in health sciences. Epistematics involves models of the processes (perceptual, intellectual and linguistic) by which knowledge and understanding are H.-L. Yu (&)  G. Christakos  S. Warmerdam  B. Dev Department of Geography, San Diego State University, San Diego, CA 92182-4493, USA e-mail: hlyu@mail.sdsu.edu A. Kolovos SAS Institute, Inc., SAS Campus Drive, Cary, NC 27513, USA J.-C. Chen Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA 123 Stoch Environ Res Risk Assess DOI 10.1007/s00477-007-0135-0