Quantifying the Performance of Spatial and Temporal Early Warning Signals of Disease Elimination

Dominic Gray, a student from Norfolk State University, and Dr. John Drake from the Odum School of Ecology examined the use of temporal early warning signals in disease dynamics.

Dominic Gray, Norfolk State University

John Drake, Odum School of Ecology, University of Georgia

Early warning signals of disease emergence and elimination seek to forecast changes of state in infectious disease system. Most such signals are a result of critical slowing down and other universal patterns near bifurcations. Most work to date has focused on temporal early warning signals, which are known to be statistically inefficient and discard information contained in the spatial pattern of cases. We sought to quantify the performance of spatial indicators and compare them to temporal indicators by simulating a spatial SIR compartmental model with vaccine induced immunity over a spatially homogenous environment. We found that spatial indicators greatly outperform their temporal counterparts, suggesting that additional gains in statistical efficiency could be achieved by adopting these newer methods.

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