Abstract: A system and method for visually displaying and analyzing public health data for geospatial and/or time variations, including the collection of symptom data coupled with geographic and time data, filtering the symptom data based upon a selected time period and geographic range, and creating a visual result based upon statistical modeling including power transform and/or data normalization. According to at least one embodiment, the system for visually displaying and analyzing includes selecting and performing at least one aberration detection method such as applying CUSUM analysis, quantile measures, and/or bootstrapping analysis, and displaying the result to a user via a visual analytics arrangement.

Abstract: A system and method for visually displaying and analyzing public health data for geospatial and/or time variations, including the collection of symptom data coupled with geographic and time data, filtering the symptom data based upon a selected time period and geographic range, and creating a visual result based upon statistical modeling including power transform and/or data normalization. According to at least one embodiment, the system for visually displaying and analyzing includes selecting and performing at least one aberration detection method such as applying CUSUM analysis, quantile measures, and/or bootstrapping analysis, and displaying the result to a user via a visual analytics arrangement.

Abstract: Coordinated animal-human health monitoring can provide an early warning system with fewer false alarms for naturally occurring disease outbreaks, as well as biological, chemical and environmental incidents. This monitoring requires the integration and analysis of multi-field, multi-scale and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. To facilitate these investigations, we have created an application to provide a visual analytics framework for analyzing both human emergency room data and veterinary hospital data. Our integrated visual analytic tool links temporally varying geospatial visualization of animal and human patient health information with advanced statistical analysis of these multi-source data. Various statistical analysis techniques have been applied in conjunction with a spatio-temporal viewing window.