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BioSense 2.0 Webinar:
Panel on ILI Surveillance
ILI Surveillance in Connecticut
Alan J. Siniscalchi, MPH, MS
Influenza & Bioterrorism Surveillance Coordinator
State of Connecticut Department of Public Health
& the International Society for Disease Surveillance
(ISDS) Public Health Practice Committee
Wednesday, December 4, 2013
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Presentation Objectives
1.
2.
3.
4.
To outline the types of surveillance systems designed for
detecting influenza, bioterrorism agents, and emerging
infections in Connecticut
To describe how these systems have been used to track ILI and
flu-associated morbidity and mortality throughout the state
To discuss which surveillance systems provide the best value
for use in the identification and tracking of influenza outbreaks
To emphasize the value of providing real-time data in assessing
risk, reducing exposure, and preventing disease
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Surveillance Objectives: Why should health departments
conduct ongoing surveillance for seasonal influenza &
emerging diseases?
1.
2.
3.
Situational Awareness (to detect and track emerging
agents and disease activity)
Health Professional Awareness and Asset Management
(to provide necessary information for optimal use of
vaccine supplies, etc.)
Public Education & Risk Communication (to provide
sufficient information to members of the public to enable
them to make informed choices)
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Surveillance Systems in Connecticut by Category (arranged
by group and speed of detection): How soon do you want to
know?
Group 7. Mortality Surveillance: 122 Cities, Pediatric mortality
Group 6. Traditional Laboratory Surveillance: Flu subtypes
Group 5. Reportable Disease Surveillance: State & federal
Group 4. Special Hospitalization & Laboratory Surveillance:
Flu-associated hospitalizations, GPR testing for anthrax
Group 3. Other Surveillance: Institutional outbreaks
Value: These provide important, but slow (many days after
exposure) information on the etiological agent &
characterization of the disease and risk factors.
.
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Surveillance Systems in Connecticut, cont.
Group 2. Syndromic Surveillance (early symptoms, hours – days
after exposure): These systems measure ILI before diagnosis
and laboratory confirmation, including ILINet outpatient
providers; the CT Hospital Admissions Syndromic Surveillance
(HASS) System, established in all 32 CT acute care hospital
campuses following September 11, 2001; the CT Hospital
Emergency Department Syndromic Surveillance (HEDSS)
System, in operation since 2004; BioSense & others
Value: For situational awareness & rapid identification and
tracking of severe outbreaks & epidemics.
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Surveillance Systems in Connecticut, cont.
Group 1. Remote Collection & Sensing Surveillance (dispersal,
before widespread exposure): A variety of state and federal
systems are available for real-time detection of bioterrorist
agents. Remote thermal imagining systems can be used in
airports and other transportation centers to detect
travelers with influenza and other febrile illness.
Value: Development and implementation of an expanded
network of thermal imaging and other automated remote
sensing systems would provide early detection and
management of imported cases.
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Figure 1. Laboratory Confirmed Tests by Influenza Type and Subtype
During the 2009 Influenza A (H1N1) Pandemic in Connecticut
1900
1800
Type A (H1N1) Novel 2009
Type A (Unsubtypeable)
1700
1600
Type
Type
Type
Type
1400
1300
1200
1100
1000
A (H1N1) Seasonal
A (H3N2) Seasonal
A (Unspecified)
B Seasonal
Type Unknown
900
800
700
600
500
400
300
200
100
MMWR Week (April 2009 - May 2010)
20
18
16
14
12
10
8
6
4
2
52
50
48
46
44
42
40
38
36
34
32
30
28
26
24
22
20
18
0
16
No. Tests Reported
1500
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Figure 2. CT ILINet Physician Provider % Influenza-like Illness (ILI) Visits vs. Hospital Emergency
Department Syndromic Surveillance (HEDSS) System % “Fever/Flu” ED Visits (April 2009-April 2010)
15
18
14
14
11
10
12
9
10
8
7
8
6
5
6
4
4
3
2
2
1
MMWR Weeks (April 2009 – April 2010)
ILINet Providers % ILI Visits
HEDSS % Fever/Flu ED Visits
13
11
9
7
5
3
1
51
49
47
45
43
41
39
37
35
33
31
29
27
25
23
21
19
0
17
0
15
ILINet Providers % ILI Visits
12
HEDSS % Fever/Flu ED Visits
16
13
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Figure 3: Connecticut Hospital Admissions Syndromic Surveillance (HASS) System,
Percent of total statewide admissions for pneumonia;
2011-12, 2012-13, 2013-14
12
10
Percent of total admissions
2011-12
2012-13
8
2013-14
6
4
2
0
MMWR week
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Figure 4. Temporal and Regional Trends during the Novel H1N1 Influenza Pandemic, Connecticut
Hospital Emergency Department Syndromic Surveillance (HEDSS) System: Percent of ED visits
for “fever/flu” syndrome category, April 12, 2009 – April 24, 2010
25%
Region 3
20%
Region 5
Region 4
Region 2
Region 1
15%
10%
5%
Fall 2009 H1N1 Wave
Spring 2009 H1N1 Wave
0%
15
17
19
21
23
25
27
29
31
33
35
37
39
41
43
MMWR Week
45
47
49
51
1
3
5
7
9
11
13
15
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Conclusions and Recommendations
1.
2.
3.
Various syndromic and other advanced surveillance systems all
provide valuable data useful for state and local jurisdiction
efforts to detect outbreaks, identify emerging disease, and
track influenza
The value of ED-based and other syndromic surveillance
systems in providing real-time data cannot be understated
Continued efforts to automate these systems will also reduce
the demand on increasingly limited public agency resources
and allow agencies to maintain a wide network of systems
resulting in a superior level of public health preparedness
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Acknowledgements
The CT DPH Influenza & BT Surveillance Teams (2003 - present):
Zygmunt F. Dembek, PhD, MS, MPH*; Maria T. Andrews, MPH*; Roxanne
Ryan*; Sara A. Niesobecki, MS* & other interns; Brenda Esponda, BS, BA;
Jianxin Sun, MD, PhD; Amanda Morrison, MPH*; Stephanie Petrahai, MPH*; &
Nancy Barrett, MS, MPH; Susan Petit, MPH, Heather Altier, BA; Zack Fraser,
BS; Field Epidemiologists: Jessica Brockmeyer, MPH; Kasia Frenette, MPH*;
Paul Gacek, MPH; Jaime Krasnitski, MPH; Lisa LoBianco Pippa, MPH*; Ava
Nepaul, MPH*; Katherine M. Purviance, MPH*; Kristen Soto, MPH; along with
Terry Rabatsky-Ehr, MPH; Randall S. Nelson, DVM, MPH; Pat Mshar, MPH*; &
Matthew L. Cartter, MD, MPH; Lynn Sosa-Bergeron, MD; James L. Hadler, MD,
MPH*; CDC EIS Officers; & lab support by Tim Brennan, Diane Barden, &
others; (*former team member)
Questions? alan.siniscalchi@ct.gov