Lessons Learned from the
National Syndromic
Surveillance Conference
Sponsored by the
Centers for Disease Control and Prevention
NYC Department of Health and Mental Hygiene
New York Academy of Medicine
September 23-24, 2002
New York City
What is Syndromic Surveillance?
 “Passive”
Systems
Minimal burden
Designed to detect and monitor large #
usual/mild illnesses
 “Active”
Systems-
Educational Outreach Tool
Designed to detect and report small #
unusual/severe syndromes
Legal Mandate:
Who Should be Doing This?
Public
Health Practice
Local health officers shall exercise due diligence in ascertaining
the existence of outbreaks of illness or the unusual prevalence
of diseases, and shall immediately investigate the causes of
same
New York State Sanitary Code, 10 NYCRR Chapter 1, Section
2.16(a)
Research
& Development
Non-traditional data sources
Academia (training) & contractors
Authorized agents of public health departments
Privacy and
Confidentiality

Health departments have strong tradition
of maintaining security of confidentiality
information
 Public health provisions in HIPAA

Data collected under auspices of
bioterrorism surveillance de-linked from
any identifiers for non-BT surveillance
Goals
 Early
detection of large outbreaks
 Characterization
of size, spread, and
tempo of outbreaks once detected
 Monitoring
of disease trends
Potential Syndromic
Surveillance Data Sources
Day 1- feels fine
 Day 2- headaches, fever- buys Tylenol
 Day 3- develops cough- calls nurse hotline
 Day 4- Sees private doctor: “flu”
 Day 5- Worsens- calls ambulance
seen in ED
 Day 6- Admitted- “pneumonia”
 Day 7- Critically ill- ICU
 Day 8- Expires- “respiratory failure”

Potential Syndromic
Surveillance Data Sources
Day 1- feels fine
Pharmaceutical
Sales
 Day 2- headaches, feverbuys Tylenol
Nurse’s
Hotline
 Day 3- develops cough- calls
nurse
hotline
 Day 4- Sees
private
doctor:
“flu”
Managed
Care
Org
Absenteeism
 Day 5- Worsens- calls
ambulance
Ambulance
Dispatch (EMS)
seen in ED
ED Logs
 Day 6- Admitted- “pneumonia”
 Day 7- Critically
ill- ICUSurveillance
Traditional
 Day 8- Expires- “respiratory failure”

Data Transfer
EMS
Emergency Department
HHC
2
FTP
Server
Inside Firewall
4
2 (TX)
FTP
server (NJ)
Email server at
DOH (NYC)
Stand-alone PC
at DOH
manual
automatic
Data available
Data available for analysis
Pharmacy
Data requirements

Core variables
 Hospital name
 Date of visit
 Time of visit
 Age
 Sex
 Chief complaint (free text)
 Home zip code
 +/- Unique identifier
Discharge diagnosis not generally
available in timely manner
 Need to consider response protocols –
patient identification, logistics

Electronic coding of chief
complaints into clinical
syndromes
Performed in SAS
 Text-string recognition
 Mutually exclusive vs. overlapping
 Hierarchy of coding
 Iterative refinement of syndrome definition
 Entire dataset can be recoded easily –
allows for changes in definition and
addition of new syndromes

Electronic ED logs
AGE SEX TIME
15 M 01:04
1
M 01:17
42 F 03:20
4
F 01:45
62 F 22:51
48 M 13:04
26 M 06:02
66 M 17:01
CHIEF COMPLAINT
ZIP
ASSAULTED YESTERDAY, RT EYE REDDENED.11691
FEVER 104 AS PER MOTHER.
11455
11220
FEVER, COUGH, LABORED BREATHING.
11507
ASTHMA ATTACK.
10013
SOB AT HOME.
10027
C/O DIFFICULTY BREATHING.
PT. MOTTLED AND CYANOTIC.
10031
Text Recognition with SAS
IF
index(cc,"FEV")>0
or index(cc,"HIGH TEMP")>0
or index(cc,"NIGHT SWEAT")>0
or (index(cc,"CHILL")>0 and index(cc,"ACHILLES")=0)
or index(cc,"780.6") etc.
then FEVER=1;
Data Summary
EMS
ED
Call-Type
Chief
Complaint
Drug Class
Geographic Pickup Zip
Grouping
Home Zip
Hospital
Store Zip
Other
Information
Age
Gender
Follow-up
Possible
Yes
Syndromic
Grouping
Pharmacy
Data Summary
EMS
ED
Pharmacy
Daily Volume ~ 3,000
calls
Coverage
>95%
~6,500
visits
Prospective
Data
Collection
March 1998
October
2001
August 2002
Analytic
Methods
Cyclical
Regression
Scan
Statistic
CUSUM
In
development
65-70%
Scan
Statistic
~6,000 Rx
~26,000 OTC
~30%
Data Summary
EMS
ED
Syndromes
“ILI”
Respiratory
Febrile
GI
Detection
Limit
(city-wide)
~50 calls
~100 visits
Detection
Limit
(localized)
~10 calls
10-20 visits
Date
3/
7/
02
3/
14
/0
2
3/
21
/0
2
2/
7/
02
2/
14
/0
2
2/
21
/0
2
2/
28
/0
2
11
/1
/0
1
11
/8
/0
1
11
/1
5/
01
11
/2
2/
01
11
/2
9/
01
12
/6
/0
1
12
/1
3/
01
12
/2
0/
01
12
/2
7/
01
1/
3/
02
1/
10
/0
2
1/
17
/0
2
1/
24
/0
2
1/
31
/0
2
Number of ED Visits
Denominator Surveillance is
Less Sensitive than Syndromic
10000
Total Visits
1000
Fever/Respiratory
GI/ Vomiting
100
7/
5/
1
9/ 997
27
/
12 199
/2
7
0/
19
3/
9
14 7
/1
9
6/ 98
6/
1
8/ 998
29
/
11 199
/2
8
1/
19
2/
9
13 8
/1
9
5/ 99
8/
1
7/ 999
31
/
10 199
/2
9
3/
19
1/
9
15 9
/2
0
4/ 00
8/
20
7/ 00
1/
2
9/ 000
23
/
12 200
/1
0
6/
20
3/
0
10 0
/2
0
6/ 01
2/
2
8/ 001
25
/
11 200
/1
1
7/
20
2/ 01
9/
20
5/ 02
4/
2
7/ 002
27
/2
00
2
Units per 100,000 prescriptions
Selected Antibiotic and Antiviral Prescriptions
1997-2002
Lower Respiratory Antibiotics and Anti-Influenza Prescriptions
at a large pharmacy chain
25000
5000
4500
20000
4000
3500
15000
3000
2500
10000
2000
1500
5000
1000
500
0
0
Week Ending
Resp
Flu
ED Respiratory Visits, Nov-May
0.16
0.14
respiratory / other
0.12
0.10
0.08
0.06
Temporal scan
CUSUM (C3)
0.04
0.02
Influenza A
0.00
1-Nov
1-Dec
1-Jan
1-Feb
B
1-Mar
1-Apr
1-May
ED respiratory visits
11
/4
/
/1
1
20
01
11 /20
/1 01
8
11 /20
/2 01
5/
12 200
/2 1
/
12 200
/9 1
12 /20
/1 01
6
12 /20
/2 01
3
12 /20
/3 01
0/
20
1/ 01
6/
1/ 200
13 2
/
1/ 200
20 2
/
1/ 200
27 2
/2
2/ 002
3/
2/ 200
10 2
/
2/ 200
17 2
/
2/ 200
24 2
/2
0
3/ 02
3/
3/ 200
10 2
/
3/ 200
17 2
/2
00
2
11
Influenza Prescriptions as % of Total
EMS calls
Pharmacy Antiviral Rx
1.0%
Prescription Data
0.9%
0.8%
0.7%
0.6%
0.5%
0.4%
0.3%
0.2%
0.1%
0.0%
Week Beginning
Subway worker- “flu”
West Nile Virus Activity
Through September 2001
Tabletop Drills
REDEX (2001)
Test of 911-EMS System
SANDBOX (2002)
Test of ED System
Nov 12 9.17 am
Flight AA 587 Crashes in Rockaways
Respiratory Zip Code Signal (7 zips)
27 Observed / 10 Expected p<0.001
Hospital Signal
31 Observed/ 16 Expected p<0.05
10
/2
5
10 /20
/2 01
7
10 /20
/2 01
9
10 /20
/3 01
1/
2
11 00
/2 1
/2
11 00
/4 1
/2
11 00
/6 1
/2
11 00
/8 1
11 /20
/1 01
0
11 /20
/1 01
2
11 /20
/1 01
4
11 /20
/1 01
6
11 /20
/1 01
8
11 /20
/2 01
0
11 /20
/2 01
2
11 /20
/2 01
4
11 /20
/2 01
6
11 /20
/2 01
8
11 /20
/3 01
0/
2
12 00
/2 1
/2
12 00
/4 1
/2
12 00
/6 1
/2
12 00
/8 1
12 /20
/1 01
0
12 /20
/1 01
2
12 /20
/1 01
4
12 /20
/1 01
6
12 /20
/1 01
8/
20
01
Resp/None Syndromes
40
35
Rockaways
30
Rest of City
25
20
15
10
5
0
Date
Investigation

Key Questions
 True increase or natural variability?
 Bioterrorism or self-limited illness?

Available Methods
 “Drill down”
 Query clinicians/ laboratories
 Chart reviews
 Patient followup
 Increased diagnostic testing
Investigation

Checked same-day logs at 2 hospitals
Increase not sustained

Chart review in one hospital (9 cases)
 Smoke Inhalation (1 case)
 Atypical Chest Pain/ Anxious (2 cases)
 Shortness of Breath- “Psych” (1 case)
 Asthma Exacerbation (3 cases)
 URI/LRI (2 cases)
Future Directions

Research Agenda
 More evaluations- Simulation models and
“spiked” validation datasets
 Better cluster detection software
 Signal Integration
 Optimizing response protocols- Inexpensive
(and accurate) rapid diagnostics

Emergency Department Surveillance
 Chief Complaint and/or Discharge Diagnosis
 HL7 Standards
 Need standard cc->syndrome coder (SAS)
Is It Worth the Effort?

Costs
 Implementation costs can be modest
 Operational costs=time of public health staff,
investigations

Benefits
 Possibility of huge benefit if early detection
 Characterization
 Strengthening traditional surveillance
 Dual Use
“Dual Use”
Opportunity to use new syndromic
surveillance infrastructure other public
health activities as well as for bioterror
events
 Can enhance all public health efforts
 Sets higher standard for all surveillance
(e.g., laboratory)

250000
Cipro and Doxycycline
Prescriptions
Cipro
40000
Doxycycline
35000
200000
30000
25000
First anthrax case
reported, 10/4/01.
150000
20000
100000
15000
CDC recommends
doxycyline 10/28/01.
9/11
10000
50000
5000
0
7/1/2001
0
7/29/2001
8/26/2001
9/23/2001
10/21/2001
11/18/2001
12/16/2001
1/13/2002
Drug Overdose
 Epidemiology
of drug overdoses
 Detection of outbreaks
Drop Page Fields Here
Total
Average of DRUG
140
120
Day of Week
100
Sat
Fri
80
Drop More Series Fields Here
60
40
120
Average of DRUG
20
110
Day of Month
0
1
2
100
3
4
5
6
7
dayoweek
90
80
70
60
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
dayomonth
18
19
20
21
22
23
24
25
26
27
28
29
30
31
New Year’s
9/19/2002
9/5/2002
8/22/2002
8/8/2002
7/25/2002
7/11/2002
6/27/2002
6/13/2002
5/30/2002
5/16/2002
5/2/2002
4/18/2002
4/4/2002
3/21/2002
3/7/2002
2/21/2002
2/7/2002
1/24/2002
1/10/2002
12/27/2001
12/13/2001
11/29/2001
11/15/2001
11/1/2001
Suicidal Ideation/Attempts
Nov. 2001 to Sept. 19, 2002
Chart Title
0.007
0.006
0.005
0.004
0.003
0.002
0.001
0
Asthma
ED Visits and EMS Calls
7/5/2002
5/5/2002
3/5/2002
1/5/2002
11/5/2001
9/5/2001
7/5/2001
5/5/2001
3/5/2001
1/5/2001
11/5/2000
9/5/2000
7/5/2000
5/5/2000
3/5/2000
1/5/2000
11/5/1999
9/5/1999
7/5/1999
6000
5/5/1999
3/5/1999
1/5/1999
11/5/1998
9/5/1998
7/5/1998
5/5/1998
3/5/1998
1/5/1998
11/5/1997
9/5/1997
7/5/1997
Improvement in Asthma Treatment
12000
10000
8000
Acute Therapy
Chronic Therapy
4000
2000
0
8/
12
/
9/ 20 0
9
10 /20 0
/7 0
11 /20 0
/4 0
12 /20 0
12 /2/2 00
/3 0 0
0 0
1/ /2 0
27 00
2/ /20
24 0
3/ /20 1
24 0
4/ /20 1
21 0
5/ /20 1
19 0
6/ /20 1
16 0
7/ /20 1
14 0
1
8/ /20
11 01
/
9/ 20 0
8
10 /20 1
/6 0
11 /20 1
/3 0
12 /20 1
12 /1/2 01
/2 0 0
9 1
1/ /2 0
26 01
2/ /20
23 0
3/ /20 2
23 0
4/ /20 2
20 0
5/ /20 2
18 0
6/ /20 2
15 0
7/ /20 2
13 0
/2 2
00
2
Units per 100,000 prescriptions
Tobacco cessation aids sold at a large
pharmacy chain
$0.39
400
350
$1.42
increase
increase in in City
tax
State tax
NRT
300
250
200
150
100
50
0
Week Ending
So What?




Strengthened surveillance systems in place
Potential to better monitor all public health
situations
Even if there are no more bioterror attacks,
preparation can strengthen our public health
infrastructure and ability to respond
“Syndromic” surveillance vs. better surveillance
Acknowledgements
NYCDOH Syndromic Surveillance Team:
Joel Ackelsberg
Sharon Balter
Katie Bornschlegel
Bryan Cherry
Hyunok Choi
Debjani Das
Jessica Hartman
Rick Heffernan
Adam Karpati
Marci Layton
Jennifer Leng
Karen Levin
Mike Phillips
Sudha Reddy
Rich Rosselli
Polly Thomas
Don Weiss
Field teams
MIS staff
Spatial Scan
Statistic
 Developed
by Martin Kulldorff
 Flexible windows in time and space
 Probability through Monte Carlo
simulations
 Controls for multiple comparisons
 Modified for infectious disease
surveillance