Persons using assistive technology might not be able to fully access information in this file. For assistance, please send e-mail to: mmwrq@cdc.gov. Type 508 Accommodation and the title of the report in the subject line of e-mail.
Comparisons of Timeliness and Signal Strength for Multiple
Syndromic Surveillance Data Types --- San Diego County, July 2003--July 2004
Steven F. Magruder,1 N. Marsden-Haug,2 S. Hakre,2 J. Coberly,1 C. McClean,3 J. Johnson,3 A. Anderson,2 J. Pavlin2
1Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland; 2Walter Reed Army Institute of Research, Silver Spring, Maryland;
3San Diego County Health and Human Services Agency, San Diego, California
Disclosure of relationship: The contributors of this report have disclosed that they have no financial interest, relationship, affiliation, or other association with any organization that might represent a conflict of interest. In addition, this report does not contain any discussion
of unlabeled use of commercial products or products for investigational use.
Abstract
Introduction: San Diego County is the site of the BioNet Project, which seeks to improve the
ability of the Navy Region Southwest and San Diego County to respond to a biologic attack on its population and its
critical infrastructure by improving, integrating, and enhancing disparate military and civilian detection and characterization capabilities. BioNet is funded by the Department of Homeland Security. One component of
this project is the comparison of data sources available in San Diego County to understand their relative strengths
and weaknesses for syndromic surveillance purposes.
Objectives: This study quantitatively compared the different syndromic data sources (both military and civilian) available in San Diego County both in terms of signal strength and timeliness.
Methods: Multiple types of data were compared, including emergency medical services (EMS), school nurse, school absentee, physician outpatient encounters, over-the-counter (OTCs) pharmaceuticals, and
prescription pharmaceuticals. Three major historical disease outbreaks are used as points of comparison. The specific outbreaks are respiratory disease caused by a major wildfire event in October 2003, influenza-like illness in December 2003, and a surge of gastrointestinal illness in February 2004. Each data source is separately filtered to bring out the types of symptoms associated with each of the outbreaks. The sources are compared both before and after smoothing with a moving 7-day average, designed to eliminate certain idiosyncratic effects and to
reduce noise. Finally, the data sources were compared on the basis of timing and signal-tonoise ratio for their ability to capture these outbreaks. Additional time-series comparisons were also used to determine whether the data sources trend together during nonoutbreak periods.
Results: The disease outbreaks are each observable in multiple data sources, but the most useful data source varies with the event. EMS, military ambulatory encounters, OTCs, and school nurse reports were especially useful for different illness events. For example, EMS
data indicate the strongest signal-tonoise ratio for disease caused by wildfires; the school nurse data give an early indication of influenza; and the military ambulatory encounter data provide the strongest indication of an outbreak of gastrointestinal illness.
Conclusion: These results indicate that a system that integrates multiple syndromic data streams into a single prospective surveillance tool might enhance the ability of military and civilian authorities in San Diego County to detect biologic terrorist or other disease outbreaks in a timely fashion.
Use of trade names and commercial sources is for identification only and does not imply endorsement by the U.S. Department of
Health and Human Services.References to non-CDC sites on the Internet are
provided as a service to MMWR readers and do not constitute or imply
endorsement of these organizations or their programs by CDC or the U.S.
Department of Health and Human Services. CDC is not responsible for the content
of pages found at these sites. URL addresses listed in MMWR were current as of
the date of publication.
Disclaimer
All MMWR HTML versions of articles are electronic conversions from ASCII text
into HTML. This conversion may have resulted in character translation or format errors in the HTML version.
Users should not rely on this HTML document, but are referred to the electronic PDF version and/or
the original MMWR paper copy for the official text, figures, and tables.
An original paper copy of this issue can be obtained from the Superintendent of Documents,
U.S. Government Printing Office (GPO), Washington, DC 20402-9371; telephone: (202) 512-1800.
Contact GPO for current prices.
**Questions or messages regarding errors in formatting should be addressed to
mmwrq@cdc.gov.
