Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting
Conventional disease surveillance mechanisms that rely on passive reporting may be too slow and insensitive to rapidly detect a large-scale infectious disease outbreak; the reporting time from a patient’s initial symptoms to specific disease diagnosis takes days to weeks. To meet this need, new surv...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Centers for Disease Control and Prevention
2004-10-01
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| Series: | Emerging Infectious Diseases |
| Subjects: | |
| Online Access: | https://wwwnc.cdc.gov/eid/article/10/10/03-0789_article |
| Summary: | Conventional disease surveillance mechanisms that rely on passive reporting may be too slow and insensitive to rapidly detect a large-scale infectious disease outbreak; the reporting time from a patient’s initial symptoms to specific disease diagnosis takes days to weeks. To meet this need, new surveillance methods are being developed. Referred to as nontraditional or syndromic surveillance, these new systems typically rely on prediagnostic data to rapidly detect infectious disease outbreaks, such as those caused by bioterrorism. Using data from a large health maintenance organization, we discuss the development, implementation, and evaluation of a time-series syndromic surveillance detection algorithm for influenzalike illness in Minnesota. |
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| ISSN: | 1080-6040 1080-6059 |