Tools and Techniques for Enhanced Health Surveillance in Deployed Settings
Abstract
Historically, diseases and non-battle injuries (DNBI) have had the greatest impact on mission performance. Consequently, the U.S. Department of Defense (DoD) continuously monitors health events in deployed troops, seeking to minimize the adverse effects of DNBI. For many years, military preventive medicine efforts focused on broad categories of endemic communicable diseases and non-battle injuries. As concerns surfaced about unexplained illnesses among Gulf War veterans and of possible disease clusters associated with other military operations, DoD efforts increased to better integrate occupational and environmental exposure data with health event data. In light of recent attacks in several countries involving chemical and biological agents, there was a clear need to develop or adapt surveillance systems capable of detecting patterns in health-related data that might indicate community exposures to weapons of mass destruction. The DoD addressed this need by applying enhanced surveillance techniques to the existing DNBI surveillance system. A group of epidemiologists and preventive medicine specialists established five special surveillance categories that attempt to capture health events most likely to be associated with known chemical or biological warfare threats. Analyzing deployed health event data presents several challenges. The best approach is to determine site- and population-specific comparison rates at the earliest possible time. Based on these requirements, the decision was to modify the graphs of current/past experience employed by the CDC with reporting of significant national medical event patterns. This paper focuses on deployed health event surveillance, especially on one method to help identify unrecognized attacks involving weapons of mass destruction. The described methods hold promise, but there remain a number of limitations and a need to validate and compare these techniques with other methods.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2004
- Accession Number
- ADA433573
Entities
People
- Kenneth L. Cox