Data Visualization for Health Surveillance: Current Concepts and New Horizons

Presenters

Wayne Loschen, Johns Hopkins University Applied Physics Laboratory (JHU-APL)

Karl Soetebier, MPW, Georgia Division of Public Health

Paul Picciano, PhD, Aprima Medical Software

Frank Hardisty, Pennsylvania State University

Date and Time

Wednesday, September 23, 2009

Host

ISDS Research Committee

October 23, 2017

Interactive Detection of Spatial Clusters

Geographic visualization methods allow analysts to visually discover clusters in multivariate, spatially-referenced data. Computational and statistical cluster detection techniques can automatically detect spatial clusters of high values of a variable of interest. The authors propose that the two approaches can be complementary; and present an integration of the GeoViz Toolkit and Proclude software suites as proof-of-concept.

July 30, 2018

Monitoring Dynamic Tempo-Spatial Changes of Influenza-Like Illness During 2005-2007 through Sentinal-Physician Surveillance in Taiwan Using Ring Maps

The global health threat of highly pathogenic avian influenza H5N1 has been increasing rapidly in the world since the crosscountry outbreaks during 2003-04. In South and East Asia, the human influenza A (H3N2) was proved to be seeded there with occurring annual cases. Intensive surveillance of influenza is the most urgent strategy to avoid large-scale epidemics and high case fatality rates. Sentinel physicians’ surveillance is the most sensitive mechanism to reflect the health status of community people.

July 30, 2018

Web-Based Spatio-Temporal Display of NC DETECT Surveillance Data

NC DETECT is the Web-based early event detection and timely public health surveillance system in the North Carolina Public Health Information Network. The reporting system also provides broader public health surveillance reports for emergency department visits related to hurricanes, injuries, asthma,  vaccine-preventable diseases, environmental health and others.

July 30, 2018

Use of Informatics for Understanding Disease Activity in Community

Centre for Health Protection (CHP) plans to conduct a pilot project in developing a syndromic surveillance system using data from Emergency Departments (ED) in Hong Kong. This is part of the Communicable Disease Information System initiative, which aims at enhancing the capability of Hong Kong in the control and prevention of communicable diseases.

 

Objective

This paper describes how the CHP of Hong Kong designed and deployed an online interactive system that uses the data from ED for syndromic surveillance.

July 30, 2018

Bayesian Network Data Fusion Visualization

A Bayesian Network (BN) is a probabilistic graphical model representing dependencies and relationships. The structure of the network and conditional probabilities capture an expert’s view of a system. BN have been applied to the public health domain for research purposes, but have not been used directly by the end users of public health systems. As BN technology becomes more and more accepted in the public health domain, the data fusion visualization becomes a critical component of the overall system design.

July 30, 2018

Using Online Applications with R to Share Surveillance Data

Since 2009, the Cook County Department of Public Health (CCDPH) has created and disseminated weekly surveillance reports to share seasonal influenza data with the community and our healthcare partners. Surveillance data is formatted into tables and graphs using Microsoft Excel, pasted into a Word document, and shared via email listserv and our website in PDF format.

February 27, 2018

Pages

Contact Us

NSSP Community of Practice

Email: syndromic@cste.org

 

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