Communicable
disease surveillance
Robert Allard MDCM MSc FRCPC
October 2004
Infectious disease
surveillance designs
 Traditional disease notification
 Outbreak investigation
 Cluster investigation
 Enhanced surveillance
 Sentinel surveillance
 Emerging infectious diseases
 diagnosis-based surveillance
 syndromic surveillance
 Molecular biology and surveillance
Definition
“Surveillance, when applied to a disease, means
 the continued watchfulness over the distribution and trends
of incidence
 through the systematic collection, consolidation and
evaluation of morbidity and mortality reports and other
relevant data.
 Intrinsic in the concept is the regular dissemination of the
basic data and interpretation to all who have contributed
and to all others who need to know.
 The concept, however, does not encompass direct
responsibility for control activities.”
A.D. Langmuir, 1963
COMMUNICABLE DISEASE
SURVEILLANCE or RESEARCH?
 Ongoing
 Generates hypotheses
 Incomplete data on
population
 Simpler analysis
 Rapid dissemination of
results
 Results not necessarily
generalizable
 Triggers intervention
 Time-limited
 Tests hypotheses
 Complete data on sample
 More complex analysis
 Slower dissemination of
results
 Aims at generalizability
 Looser link to intervention
Traditional disease notification
 Legal framework
 List of reportable (or notifiable) conditions
 Verification and analysis
 Investigation
 Public health intervention
 Dissemination of results
 Evaluation and updating
Legal framework
 Required for
 transmission of confidential information
 investigation
 intervention
 Varies between jurisdictions
 Québec specifics:

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no more anonymously reportable conditions
HIV-AIDS is “provincially reportable”
duty to “signal” non-reportable conditions
distinction between “surveillance” and “vigie”
surveillance ethics committee
DISEASE SELECTION CRITERIA
 Incidence
 Morbidity
 Mortality / severity / lethality
 Communicability / potential for outbreaks
 Preventability
 Changing pattern in previous 5 years
 Socioeconomic burden
 Public health response necessary
 Public perception of risk
 International and other sector consideration
Rank (Priority for Canadian government, first 12 of 43)
1988
1998
1 Measles
HIV
2 Tuberculosis
AIDS
3 AIDS
Laboratory confirmed influenza
4 Hepatitis B
Tuberculosis
5 Pertussis
Measles
6 Salmonellosis
Rabies
7 Rubella
Pertussis
8 H. influenzae
Invasive meningococcal disease
invasive disease
9 Diphtheria
Hepatitis C
10 Chickenpox
Botulism
11 Meningococcal
Poliomyelitis
infection
12 Gonococcal
Creutzfeld-Jacob Disease
infection
VALIDITY OF REPORTS
(False positives)
 Surveillance definitions
 May be different from clinical definitions
 Laboratory confirmation
 The problem of nearly eliminated diseases
 Most positives are false positives
• Poor clinical diagnostic accuracy
• Importance of eliminating alternate Dx
 Only confirmed cases enter statistics
COMPLETENESS OF REPORTING
(False negatives)
 Varies by
 Type of reporting (active, passive)
 Source of reports
 Disease
 Need not be high, provided it is stable
 More important if intervention is possible
Stages in the reporting of
shigellosis (CDC, ca. 1970)
100
90
80
70
60
50
40
30
20
10
0
Inf
Symp
Cons
Cult
Pos
Report
Inv
Neg
ROUTINE INVESTIGATION
OF REPORTED CASES
 MD, patient and/or relative are interviewed
 Not all cases can be investigated


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Intervention possible
Transmissibility is high
Case is unusual
Outbreak is suspected
ANALYSIS OF
SURVEILLANCE DATA
“Monitoring trends is the cornerstone
objective of most surveillance systems.”
Buehler, Modern Epidemiology (1998), p. 438
Standard outputs
 Periodic reports
 Mail and internet
 Monthly
 Commented
 Newsletter
 Special alerts
 fax and e-mail
 Annual report
MAIN MONTHLY SURVEILLANCE
OUTPUT, MONTREAL
2003 au 12 juil.
Courant
Maladie
N
Taux
2002 au 13 juil.
Cumulatif
N
Taux
Courant
N
Taux
2001 au 14 juil.
Cumulatif
N
Taux
Courant
N
Taux
Cumulatif
N
Taux
Amibiase
11
7.8
76
7.7
9
6.4
63
6.4
8
5.7
77
7.9
Botulisme
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
Brucellose
0
0.0
1
0.1
0
0.0
0
0.0
0
0.0
1
0.1
27
19.2
181
18.3
52
37.0
224
22.8
37
26.5
184
18.8
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
0.1
182
129.1
1706
172.9
201
143.2
1697
172.7
195
139.5
1598
163.3
Choléra
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
Coqueluche
3
2.1
17
1.7
6
4.3
65
6.6
7
5.0
74
7.6
Diarrhée épidémique
0
0.0
27
2.7
1
0.7
4
0.4
0
0.0
5
0.5
Encéphalite transmise par arthropodes
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
Entérite à E. coli O157:H7
0
0.0
4
0.4
2
1.4
19
1.9
9
6.4
27
2.8
Entérite à Yersinia enterocolitica
2
1.4
16
1.6
5
3.6
13
1.3
2
1.4
20
2.0
Fièvre paratyphoïde
0
0.0
3
0.3
1
0.7
2
0.2
0
0.0
4
0.4
Fièvre typhoïde
1
0.7
5
0.5
0
0.0
8
0.8
1
0.7
4
0.4
Fièvre Q
0
0.0
0
0.0
0
0.0
1
0.1
0
0.0
0
0.0
Giardiase
16
11.4
153
15.5
19
13.5
117
11.9
18
12.9
135
13.8
Campylobactériose
Chancre mou
Infection à Chlamydia trachomatis
Detail of preceding table:
“Figure 1” analysis
ANNUAL FORECASTS
Importance of explaining
the main surveillance results
Note explicative concernant les statistiques des maladies infectieuses à déclaration
obligatoire (MADO) et autres maladies infectieuses sous surveillance
Période 08 de l’année 2003 (semaines 29 à 32 13-07-2003 au 09-08-2003])
Shigellose
L’excès significatif de cas de shigellose s’explique par une éclosion parmi le
personnel d’un établissement de soins de Montréal. Quinze cas ont été
identifiés, dont treize confirmés par culture (S. sonnei) et deux reliés
épidémiologiquement à un cas confirmé. Les symptômes ont commencé entre
le 14 et le 18 juillet. De plus, quelques cas ont été déclarés dans la
communauté, dus au même agent, et apparemment reliés à un ou des
restaurants. Les organismes impliqués dans l’enquête (DSP, CUVM, MAPAQ)
ont exploré divers liens possibles entre tous ces cas. L’éclosion est maintenant
considérée comme terminée et des aliments achetés à la cafétéria semblent
être la source commune de l’infection pour les cas dans l’établissement.
Remerciements à Mme Hélène Rodrigue pour l’information.
Outbreak investigation
 Time, place, person
or
 Who, what, where, when, why (how)?
 How = by what mode of transmission?
 Three basic modes:
 Person-to-person
 Common source
 Vector-borne
DESIGNS FOR
OUTBREAK INVESTIGATIONS
 Descriptive
 Common exposure
• Suitable when exposure is very specific
 Person to person contacts
 Case-control
 Controls are:
• Other attendees at event who remained healthy
• Population sample (often drawn by RDD)
 Case-case
 Controls are:
• Cases of other reportable diseases
• Cases of the same disease, caused
by a different strain than caused the outbreak
CLUSTERING:
temporal and spatial
Cluster:
 “A geographically bounded group of
occurrences
 of sufficient size and concentration
 to be unlikely to have occurred by chance.”
(Knox, 1989)
WHY THE INTEREST
IN CLUSTERING?
 Cases are effects.
 If effects are clustered, their causes could
also be.
 Or they could be in fact the same cause.
 A common cause may be easier to
 identify (of all exposures, it is the one that cases share)
 remove or control.
TEMPORAL CLUSTERING
 Based on time-series (of numbers of notified cases)
 Time unit:
 Week
 Month (period)
 Favourite statistical methods:
 ARIMA or Box-Jenkins modelling
 “Figure 1” method
Box-Jenkins modelling:
the time series and the forecasts
SPATIAL CLUSTERING
 Less useful for surveillance in urban
compared to rural environments
 Very many methods exist
 Most require more or less unrealistic
assumptions
 Most promising: SaTScan (see satscan.org)
Reported dead corvid sightings
WNV-INFECTED CORVIDS (red)
SMOOTHED MAP
OF SAME INFECTED CORVIDS
(Thanks to Christian Back)
HUMAN WNV CASES
(a few days later, Sept. 19, 2003)
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SaTScan v4.0.3
_____________________________
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Program run on: Tue Sep 14 08:39:26 2004
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Purely Spatial analysis
scanning for clusters with
high rates using the Bernoulli model.
________________________________________________________________
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SUMMARY OF DATA
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Study period .........: 2004/1/4 - 2004/9/11
Number of census areas: 12153
Total population .....: 1996
Total cases ..........: 68
________________________________________________________________
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MOST LIKELY CLUSTER
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1.Location IDs included.: 24490070, 24490072, 24490071, 24490075,
24490125, 24490073, 24490074, 24490108,
24490069, 24490078, 24490076
Coordinates / radius..: (45.835072 N, 72.416458 W) / 3.35 km
Population............: 3
Number of cases.......: 3
(0.10 expected)
Overall relative risk.: 29.353
Log likelihood ratio..: 10.203094
Monte Carlo rank......: 22/1000
P-value...............: 0.022
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SECONDARY CLUSTERS
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2.Location IDs included.: 24650090, 24650089, 24650095, 24650092,
24650091, 24650103, 24650087, 24650105,
24650104, 24650094, 24650096
Coordinates / radius..: (45.601601 N, 73.716415 W) / 0.75 km
Population............: 3
Number of cases.......: 3
(0.10 expected)
Overall relative risk.: 29.353
Log likelihood ratio..: 10.203094
Monte Carlo rank......: 22/1000
P-value...............: 0.022
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3.Location IDs included.: 24570180, 24590138, 24570179, 24590137,
24590133, 24590129, 24590131, 24570089,
24590128, 24590132, 24590134, 24590130,
24590139, 24590135, 24590119, 24590136,
24590114, 24590115, 24590113
Coordinates / radius..: (45.580250 N, 73.286354 W) / 3.73 km
Population............: 3
Number of cases.......: 3
(0.10 expected)
Overall relative risk.: 29.353
Log likelihood ratio..: 10.203094
Monte Carlo rank......: 22/1000
P-value...............: 0.022
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4.Location IDs included.: 24700011, 24700010, 24700004, 24700003,
24700009, 24700007, 24700002, 24700008,
24700012, 24700058, 24700001, 24700006,
24700005, 24700013, 24700060
Coordinates / radius..: (45.294823 N, 73.843208 W) / 5.58 km
Population............: 5
Number of cases.......: 3
(0.17 expected)
Overall relative risk.: 17.612
Log likelihood ratio..: 6.904386
Monte Carlo rank......: 263/1000
P-value...............: 0.263
Clusters, week 30, 2003
Cases
Clusters, week 30, 2003
Controls
GROWING IMPORTANCE
OF ZOONOSES
 vCJD, SARS, WNV, avian influenza,
monkeypox, rabies etc.
 Disease trends in other species have to be
followed and related to trends in humans
 Interdisciplinary collaboration essential
 Worrisome development,
but very stimulating work
ENHANCED SURVEILLANCE
 Priority problem identified
 Concept is elastic: traditional surveillance plus any
combination of

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

Extra resources allocated
Increased collaboration between government levels
Standardized data collection
Increased data quality control
Access to better laboratory tests
Increased analytic possibilities
Other surveillance methods
 Greater potential to guide policy making?
SENTINEL SURVEILLANCE
 Does not seek completeness
 Uses purposely selected sources of information
 Prefers sources likely to observe earliest occurrence
of phenomenon under surveillance
 May be active or passive
 Relies heavily on real-time communication
 Positive findings often trigger other forms of
surveillance
CHOICE OF SENTINELS
 Physicians
 Pharmacies
 Laboratories
 Hospitals
 Public health Units, etc.
 Combination of sources
(see http://www.cdc.gov/foodnet/surveys.htm)
SUCCESS FACTORS (?)
 Link to professional organizations
 Keep it passive
 Provide feedback and other benefits
 Surveillance objectives must be
 Relevant
 Flexible
 Suggested by participants
IMPORTED FALCIPARUM
MALARIA IN EUROPE
 European Network on Surveillance of
Imported Infectious Diseases
 About 45 hospital departments of infectious
diseases
 1659 patients seen in 1999-2000
 About 10% of all patients with malaria seen in
Europe
 Results:
 European travellers
48%
Immigrants
52%
 Country of infection: West Africa for 63%
 Chemoprophylaxis had been taken by
• 40% of travellers
• 28% of immigrants
 Lethality: 5 patients (all travellers)
 Useful results, but is it surveillance?
 Continuous collection, analysis, reporting?
 No denominators or analysis of trends
EMERGING
INFECTIOUS DISEASES
 Strategic/political aspects of the concept
 “Emerging infections are those diseases whose
incidence has increased within the past two
decades or … threatens to increase in the near
future.” (NY ACAD SCI)
 An emerging infection can be due to an agent






previously unknown
previously unknown in humans
previously unknown in a given area
previously non pathogenic or less pathogenic
previously non resistant to antibiotics
previously controlled by preventive measures
SOME EMERGING AGENTS
 1973 Rotavirus
 1977 Ebola virus
 1977 Legionellosis
 1981 HIV
 1982 E.coli O157:H7
 1982 Lyme disease
 1983 H. pylori
 1986 BSE, vCJD (prions)
 1989 Hepatitis C
 1992 Cholera O139
 1995 HHV-8
 1999 WNV
 2001 Anthrax
 2002 SARS CoV
FACTORS IN EMERGENCE
 Microbial adaptation and change
 Drug resistance
 New virulence or toxin production
 Environmental changes
 Global warming
 Deforestation
 Societal events
 Impoverishment
 War
 Immigration
 Human behaviour
 Sexual, drug use
 Travel
 Use of child care facilities
 Food production
 Globalization
 Health care
 Widespread use of antibiotics (Clostridium difficile!)
 Immunosuppressive drugs
 Public health infrastructure
 Curtailment of preventive programs
EID: diagnosis-based surveillance
 SARS: severe acute respiratory syndrome
 Originated in SE Asia in November 2002
 Single agent suspected early (SARS CoV)
 Importation to Toronto (“superspreader”)
 Canada-wide alert in April 2003
 Canadian case definition based on WHO’s
 This case definition was crucial to
 Day-to-day surveillance and control activities
 Description of outbreak
Surveillance case definition:
 Suspect Case: A person presenting with:
 Fever (over 38 degrees Celsius)
AND
 Cough or breathing difficulty
AND
 One or more of the following exposures during the 10 days prior
to the onset of symptoms:
• Close contact with a person who is a suspect or probable case
• Recent travel to an "Area with recent local transmission" of SARS
outside of Canada
• Recent travel or visit to an identified setting in Canada where
exposure to SARS may have occurred (e.g., hospital [including any
hospital with an occupied SARS unit], household, workplace, school,
etc.). This includes inpatients, employees or visitors to an institution if
the exposure setting is an institution.
 Probable Case:
 A suspect case with radiographic evidence of infiltrates
consistent with pneumonia or respiratory distress
syndrome (RDS) on chest x-ray (CXR).
OR
 A suspect case with autopsy findings consistent with the
pathology of RDS without an identifiable cause.
 Exclusion Criteria
 A suspect or probable case should be excluded if an
alternate diagnosis can fully explain their illness.
SARS EPIDEMIC CURVE, CANADA, 2003
EID: syndromic surveillance
 Observes the occurrence not of diagnosed
disease but of a pre-defined syndrome
 Syndrome = “a pattern of symptoms
indicative of some disease”, usually
unidentified
 The syndrome may be associated with one or
more disease entities
 A diagnosis is sought (for surveillance) only
when a cluster of the syndrome is detected
EXAMPLES OF SYNDROMES
FOR SURVEILLANCE
 Fever + upper or lower respiratory signs or
symptoms (plague,anthrax, ricin, staph. toxin or …)
 Fever + rash (smallpox or …)
 Fever + hemorrhages (Ebola, Marburg or …)
 Fever + GI symptoms (salmonellosis or …)
 Cranial-nerve impairment (botulism or …)
 Fever + unexplained death
OPERATIONALIZATION OF
SYNDROMIC SURVEILLANCE
 Most promising general source of information:
emergency department (or other primary care
source) presenting complaints (PC)
 Information is
 computerized on site
 transmitted periodically to central server
 scanned to extract PCs and other information
 PCs are synthesized into syndromes if possible
 Clusters of syndromes are tested for
 Significant clusters flagged for further investigation
Simple temporal analysis of HMO data
(Thanks to Richard Platt)
Simple spatial analysis of HMO data
(Thanks to Richard Platt)
MOLECULAR BIOLOGY
AND SURVEILLANCE
 Based on ability to distinguish different
strains of same agent, based on its nucleic
acid (genotype)
 Different methods, short of sequencing, can
be used
 Must be able to detect mutations that are
 Frequent enough to have produced many different
strains over the years
 Rare enough not to occur during an outbreak
DNA electrophoretic pattern
Uses of DNA “fingerprinting”
 Prove that cases in an outbreak are related
 Prove that suspected vehicle is the true common
source
 Identify outbreaks missed by traditional methods
 TB in chronic care hospitals for old people
 Help select cases and controls in a case-case study
 Cases: cases caused by the outbreak strain
 Controls: cases caused by non outbreak strains
 Goal: identify mode(s) of transmission specific to this
outbreak
Example of case-case study
 Listeriosis outbreak (meningitis, sepsis, especially in
pregnant women) in France
 Positive L. monocytogenes culture from normally
sterile site between 99/11/12 and 00/02/28
 Cases: 29 strain-associated cases
 Excluded were:
• 2 deaths
• 1 case whose status (as case) was known before interview
 Controls: 32 non strain-associated cases
 Results:
 Adjusted ORs and 95% CI
• Jellied pork tongue: 75.5 (4.7 - 1216)
• Pâté de campagne:
8.9 (1.7 - 46.1)
• Cooked ham:
7.1 (0.7 - 71.8)
 All cases had eaten at least one of the above
 Recommendation against eating the pork tongue
made on Feb. 22, 2000
 Outbreak strain in foodstuffs
 Identified in some (rillettes: OR = 1.1 [0.3 – 3.8])
 Not identified in jellied pork tongue
• No recall, as specific brand could not be incriminated
CONCLUSION:
research vs surveillance
 Collaboration between the research and
public health communities is increasing
 Research and surveillance methodologies
are converging
 The objectives of each remain different:
is one trying to answer questions
 of local interest, as rapidly as possible
 of general interest, as validly as possible