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Abstract:
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In surveillance of environmental risk, there is a need to consider the linkages between various inter-related outcomes. For example, in health risk assessment, we might be interested in monitoring comorbidity or alternative markers of variation in risk. This area is closely related to syndromic surveillance where ancillary variables are used to make early predictions of adverse risk scenarios. In the spatial domain, the task is essentially the monitoring of spatial distributions of risk variables and their surrogates. The similarity to surrogate biomarker endpoints is marked. Hence, multivariate spatial models could be envisioned where prospective modeling will be the main focus. Ancillary time series also would be jointly modeled.
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