Risk analysis based on spatio-temporal characterization: a case study of disease risk mapping

Abstract

One of the challenges in risk analysis has been that the determinants which are identified are based on a causality-driven approach drawn largely from the correlation studies of underlying factors. These approaches not only require numerous thematic information layers - spatial and non-spatial, that may potentially represent the factors of interest, but also tend to ignore the spatial and temporal variability of the outcome itself (say, disease incidence). On the other hand, owing to the advances in surveillance and monitoring systems resulting in enhanced availability of spatially explicit data over the last 25 years, there is a need to use these effectively at understanding or explaining the phenomenon itself. In this paper, we propose a method to leverage the observed event data - both spatial and temporal characterizations of disease occurrences, to generate a risk map that will provide valuable insights into its geographical spread and to help quantify the spatial risk factor associated with it. It is evident that such a methodology will help prioritize decision-making process for better risk assessment and management including disease outbreak. Illustrative case studies of Salmonellosis disease in two states of USA are presented to demonstrate the utility of the method. It is observed that this method, per se, can be applied to other domains that exhibit similar spatio-temporal dynamic behavior.