Cloud Computing for Syndromic Surveillance

Two significant barriers to greater use of syndromic surveillance techniques are computational time and software complexity. Computational time refers to the time for many methods (for example, scan statistics and AMOEBA statistics) to create reliable results. Software complexity refers to the difficulty of setting up and configuring suites of software to collect data, analyze it, and visualize the results. Both of these barriers can be partially surmounted by the use of cloud computing resources.

Objective

To describe how use of cloud computing resources can improve the timely provision of disease surveillance analyses.