Biology Reference
In-Depth Information
and fourth tabs provide information on organization readiness and available
assets needed to support Goal 3.0 “Determine appropriate response to bio
events.” The fifth tab provides trending information needed to support Level
3 SA. Additionally, the simplicity of the interface design helps promote team
and shared SA as health professional can readily access the same informa-
tion with ease and communicate this information in a similar fashion.
Present Level 2 SA information directly to support comprehension
. System
design needs to support interpreting and comprehending all incoming data.
This includes mapping and interpretation of alerts, trend data, and envi-
ronmental and organizational factors as well as being able to distinguish
between false alarms and undiagnosed or unconfirmed events. The latter is
particularly difficult as many biological events may be unfamiliar to users,
and thus may not trigger a disease alert. Instead, each reported case must
be interpreted with other information such as similarity to other cases, loca-
tion of similar cases, and response of the nearby public and government
organizations. For example, for common diseases, such as influenza, health
professionals look for alarming trends in terms of outbreak rate and mortal-
ity. They expect some cases, but need to respond quickly if reports exceed
a given threshold. Novel diseases, such as novel influenza A (H1N1), are
much more difficult to detect. It took months, several thousand reported flu
cases, and over 150 deaths before Mexican health officials realized that the
flu symptoms, which villagers in La Gloria, Mexico, were displaying, were
actually swine flu (CNNHealth 2009).
Provide assistance for Level 3 SA projections
. Many systems do not provide the
information needed to predict future states. This is a very demanding part of
SA formation and one that novices and even some experts find difficult. As
such, biosurveillance systems need to not only present data to support lower
levels of SA (detection of a possible outbreak and understanding patterns or
trends in the data), but, more important, higher levels of SA to determine the
future impact of the information (predicting the future trends and distribu-
tion of the outbreak).
Explicitly identify missing information
. One of the critical issues in system
design is letting end users know both what information is missing and what
information is being used in the analysis. For example, a biosurveillance sys-
tem may provide an alert indicating a possible outbreak of cryptosporidosis
in a major city based on a sudden large increase in pharmacy sales of antidi-
arrheal medications. However, this alert could be incorrect if two large phar-
macy chains had coupons in the paper for this type of medication and if sales
from other pharmacy chains were not recorded or used in the analysis.
Represent information timeliness
. One of the problems facing health profession-
als is information recency, that is, the timeliness of the information presented.
For example, latency of information from developing countries is often not
optimal. Thus, health professionals need support for recalculating the current
picture once they have received late data. They also need to be able to distin-
guish between new and past information and be alerted to the data's age as
