100 square miles: The Integration of Information for Understanding Risk

Music City Center 

As statisticians, we have expert knowledge of linking measured physical and population knowledge to address challenges to advance humankind. For example, environmental risk assessment examines risks to human health from environmental externalities by linking population health and demographic information with measured environmental information from multiple modalities. Different risk assessments, for example insurance risk, benefit from similar methodologies. This talk will address linking information in a hyper-local setting, which we call 100 square miles. Issues addressed include changes in temporal and geographic support, differential quality of information, complex associations, and differential sample sizes. The statistical approach explored is linked hierarchical models focusing on capturing the observational series' inherent sampling and measurement error. To the extent possible, we will strive toward understanding causal risk relationships, or at least understanding why causality is not well articulated.