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Using syndromic surveillance systems to detect pneumonic plague
1The Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723, USA. steven.babin@jhuapl.edu
Epidemiology and Infection
|August 25, 2009
Summary
Early detection of pneumonic plague in syndromic surveillance systems is crucial. Recognizing initial gastrointestinal symptoms, not just respiratory signs, can improve outbreak identification and response for this zoonotic disease.
Area of Science:
- Public Health
- Epidemiology
- Infectious Disease Surveillance
Background:
- Syndromic surveillance systems rely on pre-diagnostic data for early disease outbreak detection.
- Understanding the initial presentation of diseases is vital for effective surveillance.
- Pneumonic plague, a zoonotic disease, poses a significant public health threat.
Purpose of the Study:
- To determine the earliest signs and symptoms of pneumonic plague for syndromic surveillance.
- To inform the design of effective syndromic surveillance queries for pneumonic plague.
- To explore the utility of integrating animal data into human disease surveillance systems.
Main Methods:
- Review of medical literature on the sequence of signs and symptoms of pneumonic plague.
- Analysis of early-stage patient presentations, focusing on gastrointestinal and respiratory indicators.
- Examination of zoonotic disease surveillance strategies, including animal data integration.
Main Results:
- Early pneumonic plague patients predominantly exhibit gastrointestinal symptoms with minimal respiratory signs.
- Failure to recognize these early gastrointestinal signs can delay detection in syndromic surveillance.
- Animal data from sources like park rangers and veterinarians may offer valuable early evidence.
Conclusions:
- Syndromic surveillance systems must account for the earliest, often non-respiratory, symptoms of pneumonic plague.
- Integrating human and animal health data can enhance the early detection of zoonotic diseases like plague.
- Literature reviews are essential for designing targeted and effective syndromic surveillance queries.
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