The timeliness of algorithmic alerts from an emergency department sur-
veillance system based on chief complaint data was compared to the date of
the influenza season peak identified by the Centers for Disease Control and
Prevention (CDC) (Irvin, Nouhan, and Rice 2003). An alert was defined as
a value that exceeded two standard deviations greater than the historical
constant mean on two of three consecutive days. For the influenza season
investigated, emergency department chief complaints alerted 14 days earlier
than the peak in CDC influenza reports.
The use of emergency department medical records for the early detection of
influenza-like illness (ILI) was investigated for one influenza season in health
care organizations in Minnesota (Miller et al. 2004). Visual inspection of ILI
counts and influenza and pneumonia deaths indicated that ILI counts rose several
weeks before the peak in the number of deaths. A CUSUM detection algorithm
signaled a confirmed influenza outbreak one day before the first virologically
confirmed isolate. When these analyses were repeated with age-stratified data
(age >65 years), the algorithm signaled 24 days earlier (Miller et al. 2004).
The CUSUM algorithm was also used to detect trends in fever and respi-
ratory distress indicative of influenza at seven hospitals in Virginia (Yuan,
Love, and Wilson 2004). In one of these hospitals, syndromic data revealed
an increase in these syndromes 7 days earlier than an increase in sentinel
influenza surveillance (Yuan, Love, and Wilson 2004).
A syndromic surveillance system based in Colorado identified unusual
clusters of ILI using three statistical models (Ritzwoller et al. 2005). These
were the small area method (SMART; small area regression and testing),
spatiotemporal method, and a purely temporal method (spatiotemporal scan
statistic using 100% of the area). These algorithms were used to compare
the timeliness of syndromic chief complaint data with laboratory-confirmed
influenza cases. They found that, despite both data sources showing sub-
stantial increases during the same calendar week, there was a greater abso-
lute increase in syndromic surveillance episodes (Ritzwoller et al. 2005).
Heffernan and colleagues (2004) applied the temporal scan statistic to
emergency department chief complaints. The signal produced from respira-
tory and fever syndromes provided the earliest indication of community-
wide influenza activity in New York City for the 2001-2002 influenza season.
The signal occurred 14 days before an increase in the number of positive
influenza isolates and 21 days before an increase in the number of sentinel
ILI reports (Heffernan et al. 2004). However, the size of these increases and
the method for determining the presence of an increase were not described.
Benefits of the aberration detection method:
The method can be based on simple thresholds or mathematical
The method can be used to answer the fundamental question of
when an outbreak can be detected.