Key elements in
a surveillance system
Patrick Rolland
EPIET / EUPHEM Intro Course 2012
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Le fil rouge in surveillance?
Surveillance is
Information for action!
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Good reminder: surveillance?

Langmuir AD., 1963
“Systematic collection, consolidation, analysis
and dissemination of data on specific disease”

Thacker SB., 1996
“The final link is the application of these data
to prevention and control”
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Good reminder: surveillance loop
Objectives
Evaluation
Data collection
Action!
Data analysis
Information
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Aim and content of the lecture

Aim: To understand key elements in a surveillance
system
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From a clear understanding of the purpose
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To the right dissemination of information
Content
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Main objectives of a surveillance system
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Checklist of key elements, step by step
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Main objectives of
a surveillance system
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Main objectives
 Describe: produce information in terms of TPP
 Alert: detect epidemics or emerging events
 Evaluate: assess prevention or control measures
 And also:
 Generate hypotheses for research
 Detect changes in health practice
 Plan public health actions and resources
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But keep in mind the goal!
Surveillance is
Information for action!
By implementation of prevention
and control measures
In order to reduce morbidity
and mortality
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Incidence (per 100,000)
Describe: Time = Graph
Weekly incidence rate of flu-like
syndromes, 2009-2012, France
Source: GP network “Réseau unifié”
Week
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Describe: Place = Map
Weekly incidence rate
of acute diarrhea
(per 100,000)
1 to 7 march 2012,
France
Source: GP network
“Réseau sentinelles”
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Describe: Person = Table
Severe cases
of influenza,
winter 20112012, France
Characteristics
of persons
Source:
Intensive care
units Network
Burden
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Alert: detect an epidemic
Weekly incidence of flu-like syndromes, 2007-2012, France
Source: GP network “Réseau sentinelles”
Incidence (per 100,000)
Incidence
Threshold
Exceedence
Week
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Alert: detect an emerging phenomena
Invasive meningococcal infections
by serogroup B, C, W135 et Y, 1985-2006, France
Source: InVS, NRC for meningococci
450
BB
350
Nombre de cas déclarés
Number of cases
400
C
Y
W135
C
W 135
Y
300
250
200
150
Emergence
of W135
100
50
0
85
86
87
88
89
90
91
92
93
94
95
96
années
Year
97
98
99
00
01
02
03
04
05
06
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Evaluate: prevention/control measure
180
Vaccination
implementation
80
160
140
120
40
100
80
0
60
40
Couverture (% )
(x 1000)
of cases
Number
Notifications
(x 1000)
200
Vaccinate coverage (%)
Cases of Pertussis, England and Wales, 1940-1999
20
0
1940
1950
1960
1970
Année
Year
1980
1990
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Evaluate: prevention/control measure
Cases of legionellosis, 1988-2011, France
Source: Notifiable disease, InVS
Incidence (per 100,000)
Number of cases
No cases
Incidence
Reinforced surveillance
New investigation guide
Urine antigen testing
Year
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Key elements in a
surveillance system
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Justification of implementation
 Ask yourself two main questions:
- Should this event be under surveillance?
• High frequency?
• High severity?
• High socioeconomic cost?
- Do some prevention or control measures exist?
 And these two additional questions:
- Do we have existing data that already answer?
- Do we have resources to set up a new system?
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Health events under surveillance
 Infectious diseases
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Notifiable diseases
Health-care associated infections (HCAI)
Vaccine-preventable diseases
Food and waterborne diseases
Sexually transmitted infections (STI)
Zoonoses
Vector-borne diseases
 But also?
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Health events under surveillance
 Chronic diseases and injuries: cancers,
accidents, traumas, cardiovascular diseases, etc.
 Occupational health: cancers, musculoskeletal
disorders, respiratory diseases, mental health, etc.
 Environmental hazards: air pollution, ionizing
radiations, heat/cool waves, water/soil pollution, etc.
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Objectives of the system
 Primary objective: To describe a health-related
event in population-based or in a specific population
 With two possible aims (sometimes both):
- To alert by early detection of epidemics or
emerging pathologies that need timely action
- To evaluate the efficiency of prevention or
control measures
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Passive and active system
 Consideration useful for discussion
 Passive: “The data come to you”
- Data collection based on existing information
- Simple, not burdensome but could be incomplete
 E.g.: notifiable diseases, deaths, emergency data
 Active: “You go towards the data”
- Data collection specially set up
- Good quality of data but required resources
 E.g. : injuries, non-notifiable infectious diseases, etc.
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E.g. of passive system
% of gastroenteritis among emergency consultations,
seasons 2010-2011 and 2011-2012, Aquitaine, France
4,0%
3,5%
3,0%
2,5%
2,0%
1,5%
1,0%
0,5%
2011-2012
Week
2010-2011
S14
S11
S08
S05
S02
S52
S49
S46
S43
S40
S37
S34
S31
S28
S25
S22
S19
0,0%
S16
Proportion of cases
4,5%
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Période de surveillance
Day
30-sept.
26-sept.
22-sept.
18-sept.
14-sept.
10-sept.
6-sept.
2-sept.
29-août
25-août
21-août
17-août
13-août
9-août
5-août
1-août
28-juil.
24-juil.
20-juil.
16-juil.
12-juil.
8-juil.
4-juil.
30-juin
//
1-juin
Number of cases
Nombre de cas d'envenimations
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E.g. of active system
Cases of envenomation by Physalia Physalis reported by
lifeguards, Aquitaine Atlantic Coast, Summer 2011, France
100
90
80
70
60
50
40
30
20
10
0
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Exhaustive vs. sentinel system
 Important consideration for data analysis
 Severe diseases or low-frequency diseases
requiring timely action
 Exhaustive system (= all providers)
E.g.: cancers registries, notifiable diseases
 High-frequency diseases or less-severe diseases
 Sentinel system (= selected providers)
E.g.: seasonal flu, occupational diseases (except
cancers)
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E.g. of exhaustive system
Cancers among women, Year 2005, Gironde, France
Source: Cancer
registry of Gironde
Autres
Sarcomes des os et des tissus mous
Rein
Pancréas
ORL
Primitif inconnu
Ovaire
Mélanomes de la peau
Col de l'utérus
Corps de l'utérus
Système nerveux central
Trachée-Bronches-Poumon
Thyroïde
Peau autre que mélanomes
Côlon-Rectum
Sein
Cancer causes
Principales localisations
29
Incidence
Mortalité
3. Skin cancer
2. Colorectal cancer
1. Breast cancer
0
200
400
600
800
Nombre de cas
Number of cases
1000
1200
1400
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E.g. of sentinel system
Prevalence of occupational diseases (except cancers),
Year 2010, Region of Aquitaine, France
Source: Sentinel Network of occupational physicians (n=92)
Male (%)
Female (%)
Total (%)
Musculoskeletal
disorders
3.4
3.5
3.4
Psychic suffering
1.0
2.1
1.5
Skin rashes and allergies
0.3
0.4
0.3
Hearing disorders
0.4
/
0.2
Total
5.2
6.0
5.6
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Case vs. syndromic system
 Case system (traditional system)
- Targets a defined health-related event
 E.g.: mesothelioma, Lyme disease, diabetes, etc..
 Syndromic system (“before diagnosis”)
- For early detection, evaluation of event impact
- Based on existing activity data, real-time
collection, analysis and interpretation data
 E.g.: emergency services, virology labs, deaths
certificates, medicine sales, absence in schools, etc.
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E.g. of case system
Occupations at risk for mesothelioma, France
Occupations
Source: Program of Mesothelioma Surveillance (1998-2012), InVS
Odds-ratio (95% CI)
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E.g. of syndromic system
% of gastroenteritis among emergency consultations,
seasons 2010-2011 and 2011-2012, Aquitaine, France
4,0%
3,5%
3,0%
2,5%
2,0%
1,5%
1,0%
0,5%
2011-2012
Week
2010-2011
S14
S11
S08
S05
S02
S52
S49
S46
S43
S40
S37
S34
S31
S28
S25
S22
S19
0,0%
S16
Proportion of cases
4,5%
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Case definition
 The “heart” of the system!
 Must be clear and simple
 Based on criteria:
clinical, biological, epidemiological
 May include:
- Classification (possible, probable, confirmed)
- TPP (Time-Place-Person) information
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E.g. for measles
definition as
notifiable
disease
Clinical criteria
Laboratory criteria
Source:
Case definitions of
notifiable diseases
Commission Decision
2008/426/EC – 28-IV-2008
Epidemiological criteria
Case classification
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart of data and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Population under surveillance
 Depends on characteristics of health-event
 E.g.: Hemolytic Uremic Syndrome (HUS)
- Rare disease that predominantly affects
children, needs timely action in outbreak
 Population under surveillance (France):
children (< 15 years) hosted in pediatric and
nephrology hospital services (N=31)
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Data providers and data sources
 Data providers: health professionals, laboratories,
health insurance funds, civil status offices, etc.
 Data sources
- Administrative: death certificates, hospital systems, etc.
- Medical: patients folders, notifiable diseases, etc.
- Biological: virology, bacteriology, toxicology samples
- Environmental: air pollution sensors, individual ionizing
radiations card for exposed workers, etc.
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E.g. data provider: NRC (France)
47 National Reference Centers and 34 Associated Laboratories
Anaérobies et Botulisme (LA)
Arbovirus (LA)
ATNC
Brucella
Borrelia (LA)
Campylobacter & Helicobacter
Charbon (LA)
Chlamydiae
Cytomégalovirus
Enterovirus
Escherichia coli & Shigella (LA)
Francisella tularensis
Gonocoques
Haemophilus influenzae
Legionella
Leishmania
Mycobactéries et résistance des mycobactéries
Paludisme (2 co-responsables)
Pneumocoques
Résistance aux antibiotiques (LA)
Rickettsia, Coxellia & Bartonella
Staphylocoques
Streptocoques
Syphilis
Trichinella
Toxoplasmose
15 NRC
and 3 AL
Arbovirus
Arbovirus & influenza virus en AG
Charbon
Borrelia
Anaérobies et Botulisme
Chimiorésistance du paludisme
en Antilles Guyane
Coqueluche et autres bordetelloses
Corynebactéries toxinogènes
Escherichia coli & Shigella
Fièvres hémorragiques virales
Leptospires
Listeria
Méningocoques
Mycologie et antifongiques
Peste et autres yersinioses
Rage
Salmonella
Résistance aux antibiotiques
Streptocoques (LA)
Virus des Hépatites B & C (LA)
Vibrions et cholera
Virus Influenza
One NRC per
infectious disease
32 NRC and 31 AL
Pasteur Institute
(Paris)
Within hospitals,
universities, other
research institutes
Virus de la rougeole
VIH
Virus Influenza
Virus entériques
Virus des hépatites A et E
Virus des hépatites B, C et Delta
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E.g. data source: ND (France)
27 notifiable diseases (ND) require surveillance and timely action
Frequent ND (n=14)
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Botulisme
Brucellose
Chikungunya
Dengue
Fièvres typhoïdes et paratyphoïdes
Hépatite aiguë A
Infections invasives à méningocoques
Légionellose
Listériose
Rougeole
Saturnisme de l’enfant mineur
MCJ et ESST
Toxi-infection alimentaire collective
Tuberculose
Infrequent ND (n=10)
•
•
•
•
•
Choléra (RSI)
Diphtérie
Fièvres hémorragiques africaines
Fièvre jaune (RSI)
Paludisme autochtone et paludisme importés
dans DOM
Peste (RSI)
Poliomyélite
Rage
Typhus exanthématique
•
•
•
•
Bioterrorism-related ND (n=3)
•
Charbon, Tularémie, Variole
4 ND require surveillance only
•
•
•
Infection à VIH quel qu’en soit le stade
Hépatite aiguë B
Tétanos
•
Mésothéliome
(entrée en 2012)
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart of data and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Nominative data on
patient and provider
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E.g. French form
for mesothelioma
notiable disease
Anonymous data on
patient diagnosis (by
clinician&pathologist)
Dates and signatures
of provider and
sanitary authority
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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E.g. of flow chart: ND (France)
Politic of Health
Patient
Public Health
High Council
Health
Regional
Agencies
Alert
Health
professionals,
laboratories,
etc.
Ministry
of Health
Reference
Centers
Experts Networks
Clinicians/Pathologists
Partners
National/International
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Data transmission
 Reliable and fast
- Electronic: e-mails, websites
- And: phone, fax and mail
 Low frequency
- Daily
- Weekly
- Monthly
 Secure
- Regularity, punctuality, exhaustiveness
 And don’t forget the “Zero reporting”
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Data validation and data analysis
 Data validation
- Missing data
- Duplicates
 Data quality
 Data analysis
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Indicators: frequency, severity
Methods: descriptive, analytical
Illustrations: tables, graphs and maps
Keep in mind: Time-Place-Person!
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E.g. of data analysis: time series
Daily deaths, summers 1999-2002 vs. 2003, France
Source: Syndromic Program, InVS
350
35
Temperature
1999-2002
250
25
200
20
150
15
2003
Deaths
100
10
1999-2002
50
Temperature (°C)
30
Température (°C)
Décès journaliers
Number of deaths
300
2003
5
0
0
25-juin
30-juin
05-juil
10-juil
Décès 1999_2002
15-juil
20-juil
Décès 2003
25-juil
30-juil
04-août
T moy 1999_2002
Day (25 June to 19 august)
09-août
14-août
19-août
T moy 2003
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Dissemination/communication data
 Systematic and regular
- For stakeholders, decisions makers
- For other professionals, public, medias
 Adapted
- To “Those who need to know”
- To the urgency of the situation
 Format
- Report, article, flash news, press release etc.
- But also: phone, e-mail, fax, mail
 Factor of motivation/improvement
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E.g. report at local level
“Point épidémio”
France, Bordeaux
(InVS, south west)
Weekly report on health
status of population
Topics:
Outbreaks
Seasonal pathologies
Notifiable diseases
Virology surveillance
Deaths
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E.g. report at international level
CDC (USA)
WHO (Switzerland)
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E.g. press release
At local level
(e.g. France, Bordeaux)
At international level
(e.g. Europe)
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Human and financial resources
 From the budget to the expenses
- Salaries, travels, equipments, furniture, etc.
 Useful to negotiate resources, check the
workplan, assess the cost of the system
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Data security and confidentiality
 “Critical point” in surveillance system
 Public heath data
- Often personal and private in nature
- Might directly identified individuals
 Take into account policies
and protection for
personal data
- Data collection
often under laws
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Key elements
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Justification of implementation
Objectives of the system
Types of system
Case definition
Population under surveillance
Data providers and data sources
Data elements and data collecting tools
Flow chart and data transmission
Data validation and data analysis
Dissemination and communication data
Human and financial resources
Data security and confidentiality
Evaluation of system
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Aims of evaluation
 Ask yourself the fundamental question:
 Have the objectives been met?
 And these additional questions:
- Did the system generate needed answers?
- Was the information timely?
- Was it useful for decisions makers?
- How was the information used?
- What could be done to improve the “attributes”?
- Is it useful to continue the surveillance?
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The “9” attributes of a system (1)
 Simplicity: refers to structure and ease operation
 Flexibility: ability to adapt to changing needs
 Data quality: refers to data completeness&validity
 Acceptability: willingness of persons and
organizations to participate
 Sensitivity: refers to proportion of detected
cases by the system (“A / A + C”)
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The “9” attributes of a system (2)
 PVP: refers to proportion of reported the cases that
actually have the event (“A / A + B”)
 Representativeness: ability to describe the
event over time and its distribution in the population
 Timeliness: reflects the speed between system
steps of the system
 Stability: refers to reliability and availability
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Conclusion
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Main messages
 Justification
- Relevance of the event to be under surveillance
- Existence of prevention and control measures
 Objectives and aims
 To describe – To alert – To evaluate
 To produce information for action
 In order to reduce morbidity and mortality
 Requirements
- “Good data”, involvement of stakeholders
- Regular evaluation of the system
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One useful book
3rd edition
September 2010
Lisa M. Lee
et al.
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Don’t forget the surveillance loop!
Objectives
Evaluation
Data collection
Action!
Data analysis
Information
&
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Le fil rouge in surveillance?
Surveillance is
Information for action!
&