Given the periodic nature of influenza activity, it is important to develop visualization tools that enable enhanced decision-making. User-Centered Design is a set of software development methodologies that primarily employ user needs to develop applications. Similarly, Usability Heuristics provide a set of rules that increase the performance of user interfaces, and ease of use. We combined some of these techniques to develop FluView Interactive, a prototype that will enable users to better understand influenza information.
Objective
The objective of this study is to report on the use of User-Centered Design and Usability Heuristics to improve visualization of influenza-related information at the national level. The intention of the prototype is to make data more accessible to different stakeholders including the general public, public health officials at the local and state level, and other experts.
Interactive tools for visualization of disease outbreaks has been improving markedly in the past few years. With the flagships Google Flutrends1 and HealthMap2 providing prime examples. These tools provide interactive access to the general public concerning the current state-of-affairs for disease outbreaks generally and specifically for influenza. For example, while browsing HealthMap I learned of a case of tuberculosis on my campus, Iowa State University. While extremely sophisticated, these tools do not utilize modern statistical algorithms for detection or forecasting. In addition, the development cost and perhaps the maintenance cost is not trivial. We aim to build a similar visualization tool that incorporates modern algorithms for detection and forecasting but has low development and maintenance cost. Due to the low cost this tool is appropriate for quick deployment in developing countries for emerging outbreaks as well as public health agencies with declining operating budgets.
Objective
To build a zero-cost tool for disease outbreak visualization, detection, and forecasting incorporating modern tools.
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Description
Our toolkit adds statistical trend analysis, interactive plots, and kernel density estimation to an existing spatio-temporal visualization platform. The goal of these tools is to provide both a quick assessment of the current syndromic levels across a large area and then allow the analyst to view the actual data for a specific region or hospital over a period of time along with an indication as to whether or not a given data point is statistically significant. The sample data used for this toolkit come from over 70 emergency rooms throughout the state of Indiana.
Objective
This paper presents a toolkit designed to aid in the assessment of disease outbreak by visualizing spatiotemporal trends and interactively displaying detailed statistical data.