Spatial-temporal cross-correlation analysis: A new measure and a case study in infectious disease informatics

This paper aims to develop a new statistical measure to identify significant correlations among multiple events with spatial and temporal components. This new measure, K(r, t), is defined by adding the temporal dimension to Ripley's K(r) function. Empirical studies show that the use of K(r, t) can lead to a more discriminating and flexible spatial-temporal data analysis framework. This measure also helps identify the causal events whose occurrences induce those of other events.