Biology Reference
In-Depth Information
Do I Need?
Does is
Mean to Me?
Do I ink
Will Happen?
Time information is
Emergency room reports
Reported incidents of
communicable diseases
Absenteeism ( work/school )
Non-prescription drug sales
Medical hot-line calls
Source/type of outbreak
Changes in outbreak by
population groups
Deviation from normal
Information salience
of data
Availability of resources
( e.g., vaccines, medical
staff )
Projected impact of the
event on available
Projected spread of
Projected severity of
Projected ability to meet
demands of outbreak
Projected response to the
Figure 4.2
Illustration of the three levels of situation awareness in biosurveillance.
As noted in the preceding discussion, Endsley's theoretical model of SA
illustrates several variables that can influence the development and main-
tenance of SA within the biosurveillance domain. SA may be affected by
the inherent complexity of the tasks involved in monitoring and respond-
ing to potential disease outbreaks as well as the design of systems available
for monitoring these public health threats. Biosurveillance personnel are
often bombarded with too much data, but not enough reliable and interpre-
table information that they can use to guide their decision making. Adding
to this complexity is that sources of information are not always obvious (as
learned in the Milwaukee cryptosporidosis outbreak) and biosurveillance
systems do not capture “soft” data such as expert opinions. In addition,
as evident in the SARS outbreak, threats of epidemics and bioterrorism
are constantly evolving, and threat profiles keep changing. As such, early
detection has been one of the greatest challenges facing current biosurveil-
lance systems.
As mentioned, individual factors that may affect SA in biosurveillance
include the diverse background, training, and experience of biosurveillance
personnel and other health professionals. Thus, a major drawback of over-
looking user requirements in their original design and creation is that bio-
surveillance systems may fail to optimally keep the human in the loop. At
the organizational level, SA may be negatively influenced by the existence of
multiple (and sometimes competing) goals of the various agencies involved.
For example, political and organizational boundaries may hinder the shar-
ing of information (e.g., GOARN was not able to perfectly communicate the
first indications of the SARS outbreak in China). Yet, as will be discussed in
the next section, possessing a similar understanding of the current informa-
tion (team and shared SA) is absolutely critical in biosurveillance.
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