Surveillance of human disease:potentials and pitfalls
NWZG July 2012
Dr Alex G Stewart
(with help from Dr Sam Ghebrehewet and Dr Evdokia Dardamissis)
Cheshire and Merseyside Health Protection Unit
Salmonella bareilly 2010
No Window © Crown Copyright. All rights reserved. Health Protection Agency, 100016969Regional Epidemiology Unit, North West. July, 2011
No Window UK Salmonella Bareilly outbreak cases, weeks 30-50, 2010
Farrington algorithm:no overall exceedance for Salmonella
Population health protectionCommunicable diseases, Environment, Emergency Planning
Nature of pathogens/hazardsMicrobiology, transmission, pathology
Toxicology, haematology, environmental sciences
HPA structures
surv
eill
ance
Public health response to cases of specific diseases
Disease prevention (through immunisation)
Public Health FunctionWider workforce, healthy settings, policy development
Surveillance:foundational
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)
Langmuir, A. 1963. The surveillance of communicable disease of national importance. New England Journal of Medicine 268:182-192
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)
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
0
20000
40000
60000
80000
100000
120000
140000
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 encephalitis
Acute meningitis
Acute poliomyelitis
Acute 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
SARS
Smallpox
Tetanus
Tuberculosis
Typhus
Viral haemorrhagic fever (VHF)
Whooping cough
Yellow fever
http://www.hpa.org.uk/Topics/InfectiousDiseases/InfectionsAZ/NotificationsOfInfectiousDiseases/ListOfNotifiableDiseases/
Sources of data:
Clinicians
Laboratories
“Sentinel” GeneralPractices
Child health Departments in PCTs
Schools, Nursing / residential
homes
Maternity units
Local HealthProtection Units
RegionalUnits
Special surveys
National Centre for Infections
“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
Database
Laboratory/clinic
Data Analysis
PCTs/SHA
Health practitioners
Policy makers
SpecialistLaboratory
Wide dissemination
Supplementary data
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
Interpretation of data
What’s going onIs change true?
Annual measles notifications & vaccine coverage1950 to 2000
0
200
400
600
800
1950 1960 1970 1980 1990 2000
Year
No
tifi
cati
on
s ('0
00s)
0
20
40
60
80
100
Va
cc
ine
co
ve
rag
e (
%)
Source: Office for National Statistics and Department of Health
Measles vaccine
MMR vaccine
• Population changes (denominator)
• Improvement in diagnosis
• Better awareness / reporting
• Report duplication / change of system (case def.)
• Context
• Evaluate control measures
• Identify new disease and infectious agents
136 cases of infectious intestinalillness in the community
23 present to GP
6 stools submitted to the laboratory
1.4 positive lab result
1 reported to surveillance
Routine surveillance: the reporting pyramid (Wheeler JG et al, BMJ 1999; 318:1046-50)
Acute, self-limiting, no mortality, common
TB? Meningococcal disease? Ebola?
Why is surveillance important?
Cases of Syphilis reported to GUM in the NW (males)
0
50
100
150
200
250
300
350
400
450
500
1999 2000 2001 2002 2003 2004 2005
nu
mb
er o
f d
iag
no
ses
Cases of Syphilis reported to GUM in the NW (males)
0
50
100
150
200
250
300
350
400
450
500
1999 2000 2001 2002 2003 2004 2005
nu
mb
er o
f d
iag
no
ses
Cases of Syphilis reported to GUM in the NW (males by reported orientation)
0
50
100
150
200
250
300
350
400
1999 2000 2001 2002 2003 2004 2005
firs t year of diagnosis
nu
mb
er o
f d
iag
no
ses
gay
heterosexual
bisexual
Cases of Syphilis reported to GUM in the NW (males by reported orientation)
0
50
100
150
200
250
300
350
400
1999 2000 2001 2002 2003 2004 2005
firs t year of diagnosis
nu
mb
er o
f d
iag
no
ses
gay
heterosexual
bisexual
Data for 2002 is preliminary - as the number of reports rise, estimates of infants becoming HIV-infected will fall.
London
0%
5%
10%
15%
20%
25%
30%
1997 1998 1999 2000 2001 2002
Year
Exp
osed
infa
nts
beco
min
g H
IV-
infe
cted
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
HIV
-infe
cted
pre
gnan
t w
omen
di
agno
sed
befo
re d
eliv
ery
Proportion ofinfantsexposedwho becomeinfected withHIV
Proportion ofHIV-infectedpregnantwomendiagnosedbeforedelivery 1
4
4
4
Surveillance: Effectiveness of Interventions
Introduction of universal antenatal HIV testing in 1999
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
• flexible
• acceptable
• sensitive
• representative
• timely
• DID IT RESULT IN ACTION?
• WHAT WAS DONE?
• WHO DID IT??
Potentials
Develop analyses
Olympics
Improved links between systems
animal surveillance
Improved surveillance of chemical exposure
non infectious incidents
http://www.ics.uci.edu/~eppstein/pix/dianafall04/mitch/Holes-m.jpg
That’s it, folks!
“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)