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)