207840 Comparison of timeliness and correlates of three Influenza surveillance systems

Sunday, November 8, 2009

Owen Simwale, MPH , Epidemiology, Walden University PhD Student*, Harisburg, PA
Joanna Olson, BS , Medicine, Hershey medical School, Hershey, PA
Introduction

Several systems are currently used to detect the level and spread of influenza activity in the U.S. The effectiveness, completeness, specificity and timeliness of these systems, including new one such as FLUSTAR and googleflu, has not been fully examined.

Background

Three surveillance systems are routinely used to monitor Influenza trends in Pennsylvania ILINet, NEDSS and RODS. A 2006 study of comparing ILI, NEDSS and RODS data showed that RODS and NEDSS data are significantly correlated. However, no study has examined the correlation, timeliness, specificity and completeness of these systems and the googleflu. In this study we examine the correlation of RODS, ILI and google flu data.

Methods

We analyzed and charted data for the 2008/2009 Influenza season to asses how the three systems compare in terms of Influenza activity, timelines and completeness of data.

Results

In multivariate analyses of preliminary data and after controlling for observed covariates, our data showed that RODS and NEDSS data trends and peaks are significantly correlated while ILI was not very correlated with either. Google flu was correlated with ILI data but not so much with RODS data. The timeliest data for predicting Influenza activity was RODS data with significant difference between googleflu and ILI.

Conclusion

Different strengths of data sets can be harnessed to make an informed picture of influenza activity. RODS has the advantage of assessing timely and large case reports while ILI and NEDSS has the advantage of being specific. Google flu can be used as a compliment to ILI.

Learning Objectives:
X Evaluate how influenza lab test data correlates with data from Influenza-Like-Illness (ILI), Emergency Department influenza syndrome and google flu. X Compare time-of-event to reporting and specificity of health event in the three systems

Keywords: Surveillance, Performance Measures

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am the Influenza Surveillance Coordinator for the State of pennsylvania
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.