LAHVA

Linked animal-human health visual analytics

Ross Maciejewski, Benjamin Tyner, Yun Jang, Cheng Zheng, Rimma V. Nehme, David S. Ebert, William S. Cleveland, Mourad Ouzzani, Shaun J. Grannis, Lawrence T. Glickman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

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. Such an application provides researchers with the ability to visually search the data for clusters in both a statistical model view and a spatio-temporal view. Our interface provides a factor specification/filtering component to allow exploration of causal factors and spread patterns. In this paper, we will discuss the application of our linked animal-human visual analytics (LAHVA) tool to two specific case studies. The first case study is the effect of seasonal influenza and its correlation with different companion animals (e.g., cats, dogs) syndromes. Here we use data from the Indiana Network for Patient Care (INPC) and Banfield Pet Hospitals in an attempt to determine if there are correlations between respiratory syndromes representing the onset of seasonal influenza in humans and general respiratory syndromes in cats and dogs. Our second case study examines the effect of the release of industrial wastewater in a community through companion animal surveillance.

Original languageEnglish (US)
Title of host publicationVAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings
Pages27-34
Number of pages8
DOIs
StatePublished - 2007
Externally publishedYes
EventVAST IEEE Symposium on Visual Analytics Science and Technology 2007 - Sacramento, CA, United States
Duration: Oct 30 2007Nov 1 2007

Other

OtherVAST IEEE Symposium on Visual Analytics Science and Technology 2007
CountryUnited States
CitySacramento, CA
Period10/30/0711/1/07

Fingerprint

Animals
Health
Statistical methods
Emergency rooms
Monitoring
Alarm systems
Wastewater
Visualization
Specifications

ASJC Scopus subject areas

  • Computer Science(all)
  • Computer Science Applications

Cite this

Maciejewski, R., Tyner, B., Jang, Y., Zheng, C., Nehme, R. V., Ebert, D. S., ... Glickman, L. T. (2007). LAHVA: Linked animal-human health visual analytics. In VAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings (pp. 27-34). [4388993] https://doi.org/10.1109/VAST.2007.4388993

LAHVA : Linked animal-human health visual analytics. / Maciejewski, Ross; Tyner, Benjamin; Jang, Yun; Zheng, Cheng; Nehme, Rimma V.; Ebert, David S.; Cleveland, William S.; Ouzzani, Mourad; Grannis, Shaun J.; Glickman, Lawrence T.

VAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings. 2007. p. 27-34 4388993.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Maciejewski, R, Tyner, B, Jang, Y, Zheng, C, Nehme, RV, Ebert, DS, Cleveland, WS, Ouzzani, M, Grannis, SJ & Glickman, LT 2007, LAHVA: Linked animal-human health visual analytics. in VAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings., 4388993, pp. 27-34, VAST IEEE Symposium on Visual Analytics Science and Technology 2007, Sacramento, CA, United States, 10/30/07. https://doi.org/10.1109/VAST.2007.4388993
Maciejewski R, Tyner B, Jang Y, Zheng C, Nehme RV, Ebert DS et al. LAHVA: Linked animal-human health visual analytics. In VAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings. 2007. p. 27-34. 4388993 https://doi.org/10.1109/VAST.2007.4388993
Maciejewski, Ross ; Tyner, Benjamin ; Jang, Yun ; Zheng, Cheng ; Nehme, Rimma V. ; Ebert, David S. ; Cleveland, William S. ; Ouzzani, Mourad ; Grannis, Shaun J. ; Glickman, Lawrence T. / LAHVA : Linked animal-human health visual analytics. VAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings. 2007. pp. 27-34
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