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Surveillance of human disease:
potentials and pitfalls
Dr Alex G Stewart
(with help from Dr Sam Ghebrehewet and Dr Evdokia Dardamissis)
Cheshire and Merseyside Health Protection Unit
NWZG
July 2012
Salmonella bareilly 2010
Farrington algorithm:
no overall exceedance for
Salmonella
No Window cases, weeks 30-50, 2010
UK Salmonella Bareilly outbreak
© Crown Copyright. All rights reserved.
Health Protection
Agency, 100016969
No Window
Regional Epidemiology Unit, North West. July, 2011
Surveillance:
foundational
Public Health Function
Wider workforce, healthy settings, policy development
Population health protection
Communicable diseases, Environment, Emergency Planning
Nature of pathogens/hazards
Microbiology, transmission, pathology
Toxicology, haematology, environmental sciences
Disease prevention
(through immunisation)
surveillance
Public health response to
cases of specific diseases
HPA
structures
Objectives of Surveillance
“If you can’t explain it simply, you don’t understand it
well enough.”
Albert Einstein (Physicist, 1879–1955)
Objectives of surveillance
• detecting acute changes (outbreaks / epidemics)
• identifying & quantifying patterns (increased STIs)
• observing changes in agents and hosts (‘Flu)
• detecting changes in health practice (C Section)
• disease investigation & control (meningitis)
• health service planning (births, TB)
• evaluation of prevention / controls (HIV in pregnancy)
• study natural history / epi of disease (Cx cancer)
• provide info & baseline data (eradication of measles)
Principles & Practice
“It is the mark of an educated mind to rest satisfied
with the degree of precision which the nature of the
subject admits and not to seek exactness where only
an approximation is possible.”
Aristotle (Philosopher, 384–322 BC)
Epidemiological Surveillance
Definition:
 ‘Collection, collation & analysis of data
& prompt dissemination of information to those who need
to know so that action can result’ (Langmuir, 1963)
Action further specified by CDC, Atlanta as ‘planning,
implementation, and evaluation of public health practice’
To enable action, surveillance should be ‘ongoing,
practicable, consistent, timely and have sufficient
accuracy and completeness’ (Comm Dis Ctrl Handbook, p246)
Langmuir, A. 1963. The surveillance of communicable disease of national
importance. New England Journal of Medicine 268:182-192
Principles of surveillance
• systematic collection of data
• analysis of data to produce statistics
• interpretation of statistics to provide intelligence
• distribution of intelligence to those who will act
• continuing surveillance to evaluate action
Sources
“You won’t be surprised that diseases are
innumerable — count the cooks.”
Seneca (Philosopher, 4 BC – 65 AD)
Communicable disease surveilance
1801 Census
1891 London
(cholera diphtheria smallpox typhoid)
1899 E&W
1984 Public Health [Control of Disease] Act & associated
regulations (Drs)
2008 Health and Social Care Act & associated regulations
(HCW)
2012 Verbal reports accepted
140000
120000
100000
80000
60000
40000
20000
0
1913 1921 1929 1937 1945 1953 1961 1969 1977 1985 1993 2001
Diseases notifiable (to Local Authority Proper Officers) under
the Health Protection (Notification) Regulations 2010
Acute
Acute
Acute
Acute
encephalitis
meningitis
poliomyelitis
infectious
hepatitis
Anthrax
Botulism
Brucellosis
Cholera
Diphtheria
Enteric fever (typhoid
or paratyphoid)
Food poisoning
Haemolytic uraemic
syndrome (HUS)
Infectious bloody
diarrhoea
Invasive group A streptococcal disease &
scarlet fever
Legionnaires’ Disease
Leprosy
Malaria
Measles
Meningococcal septicaemia
Mumps
Plague
Rabies
Rubella
Typhus
SARS
Viral haemorrhagic fever
(VHF)
Smallpox
Whooping cough
Tetanus
Yellow fever
Tuberculosis
http://www.hpa.org.uk/Topics/InfectiousDiseases/InfectionsAZ/No
tificationsOfInfectiousDiseases/ListOfNotifiableDiseases/
Sources of data:
“Sentinel” General
Practices
Clinicians
Local Health
Protection Units
Regional
Units
Laboratories
Special surveys
Schools,
Nursing / residential
homes
National Centre
for Infections
Maternity units
Child health
Departments in PCTs
“Enhanced” surveillance
Information from notifications & lab reports minimal:
•
•
•
•
name
address
disease/organism
onset (notification)
More information collected on certain diseases
• Tuberculosis
• Meningococcal disease
• Hepatitis B
Collection
“Not everything that counts can be counted, and not
everything that can be counted counts.”
Albert Einstein (Physicist, 1879–1955)
Generic surveillance system
Wide
dissemination
Laboratory/
clinic
Policy makers
PCTs/SHA
Health practitioners
Database
Supplementary
data
Specialist
Laboratory
Data Analysis
Types of Surveillance
Active (outbreak, lab)
Passive (normal)
Sentinel (flu)
Based on secondary data analysis
(HES)
Collection – ensure:
quality, uniformity & reliability
• Definitions (standard, specific, simple, acceptable,
understandable)
• Ease of collection (simple, clear, unambiguous, imp only)
• Timeliness (pre-specified: daily, weekly…)
• Completeness (missing data)
• Motivation (legal requirements / education incentives)
Problems
Advantages and disadvantages
Josiah Charles Stamp
Economist, 1880–1941
‘When you are a bit older’ a judge in India once told an
eager young British civil servant, ‘you will not quote
Indian statistics with that assurance.
‘The government is very keen on statistics—they collect
them, add them, raise them to the nth power, take the
cube root and prepare wonderful diagrams.
‘But what you must never forget is that every one of
those figures comes from the chowkidar, or village
watchman, who just puts down what he damn pleases.’
Data collection problems
MORTALITY
• legally required
• accuracy / limited outcome
• not reflect incidence & prevalence
• multiple causes
• delays in data
Data collection problems
MORBIDITY
• legally required (<1984 fee ?prosecution)
• professional duty (>2008)
• good for severe & rare diseases
• biased to acute infections
• timeliness
• under-notification of common diseases
• over-notification due to inaccurate diagnosis
• definitions
Data collection problems
LAB REPORTS
• accurate diagnosis
• info on organisms & toxins easy but disease?
• not reflect incidence and prevalence
• accuracy of test
• limited epi info
Analysis & Interpretation
“If it looks like a duck, and quacks like a duck, we
have at least to consider the possibility that we have
a small aquatic bird of the family Anatidae on our
hands.”
Douglas Adams (Science fiction writer, 1952–2001)
Analysis of data
• Person – age, sex, level of immunity, nutrition, lifestyle,
occupation / school, hospitalisation, SES, risk factors,
smoking alcohol…
• Place - localised outbreaks, location or
source of disease or person at time of
infection, helps define risk groups
(denominator)
• Time – number reported / week; by
season; long term trends
Annual measles notifications & vaccine coverage
Interpretation of data
Measles
vaccine
MMR
vaccine
What’s going on
Is change true?
Notifications ('000s)
800
100
80
600
60
400
40
200
• Population changes (denominator)
20
0
1950
1960
1970
1980
1990
0
2000
Vaccine coverage (%)
1950 to 2000
Year
Source: Office for National Statistics and Department of Health
• Improvement in diagnosis
• Better awareness / reporting
• Report duplication / change of system (case def.)
• Context
• Evaluate control measures
• Identify new disease and infectious agents
Routine surveillance:
the reporting pyramid
(Wheeler JG et al, BMJ 1999; 318:1046-50)
Acute, self-limiting, no
mortality, common
1 reported
to surveillance
TB? Meningococcal
disease? Ebola?
1.4 positive
lab result
6 stools submitted
to the laboratory
23 present to GP
136 cases of infectious intestinal
illness in the community
Why is surveillance important?
Cases of Syphilis reported to GUM in the NW (males)
500
450
350
300
250
200
150
100
Cases of Syphilis reported to GUM in the NW (males by
reported orientation)
50
0
1999
2000
2001
400 2002
350
number of diagnoses
number of diagnoses
400
300
2003
2004
2005
gay
heterosexual
bisexual
250
200
150
100
50
0
1999
2000
2001
2002
2003
first year of diagnosis
2004
2005
Surveillance: Effectiveness of Interventions
Introduction of universal antenatal HIV testing in 1999
London
100%
90%
25%
4
80%
70%
4
20%
60%
15%
50%
40%
10%
30%
20%
5%
HIV-infected pregnant women
diagnosed before delivery
Exposed infants becoming HIVinfected
30%
10%
0%
0%
1997
1998
1999
2000
2001
2002
4
Year
Data for 2002 is preliminary - as the number of reports rise, estimates of infants becoming HIV-infected will fall.
Proportion of
infants
exposed
who become
infected with
HIV
Proportion of
HIV-infected
pregnant
women
diagnosed
before
1
delivery
Actions
“The man who insists on seeing with perfect
clearness before he decides, never decides.”
Henri-Frederic Amiel (Philosopher, 1821–1881)
Actions with intelligence
Communication, communication, communication!
Good & regular feedback to data collectors
Regular reports:
With good distribution to interested & involved persons
Professionals (newsletters, reports, journals)
Public (prevention, diagnosis, treatment news)
Policy / decision makers
Evaluation of systems
“Life can only be understood backwards, but it must
be lived forwards.”
Soren Kierkegaard (Philosopher, 1813–1855)
Evaluation of
Epidemiological Surveillance systems
Is it
•simple
• DID IT RESULT IN ACTION?
• flexible
• WHAT WAS DONE?
• acceptable
• sensitive
• representative
• timely
• WHO DID IT?
http://www.ics.uci.edu/~eppstein/pix/dianafall04/mitch/Holes-m.jpg
Potentials
Develop analyses
Olympics
Improved links between systems
animal surveillance
Improved surveillance of chemical exposure
non infectious incidents
“There are three kinds of epidemiologist:
those who can count and those who can’t.”
Anonymous (adapted by John M. Cowden, Emerg Infect Dis.
2010 http://wwwnc.cdc.gov/eid/article/16/1/09-0030.htm)