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IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)1
Francesco Checchi
Disease Control in Humanitarian Emergencies (DCE)
Department of Epidemic & Pandemic Alert and Response (EPR)
Review of epidemiological indicators
Short course on Infectious Diseases in Humanitarian Emergencies
London, 30 March 2009
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)2
Why compute epidemiological indicators?
� Describe morbidity
� Incidence
� Prevalence
� Losses in life expectancy and quality of life
� Describe mortality
� Mortality rate
� Excess mortality
� Describe coverage or effectiveness of relief interventions
� Different stages of interventions
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)3
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)4
Types of indicators
� Proportion
� A/N, where A is part of N
� Can be expressed as %
� Ratio
� A/B, where A is not part of B
� Rate
� Speed with which events are accumulating
� New cases per person per unit time
� Lots of misnomers -> very confusing!
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)5
Some ground rules for formulating indicators
� Define condition clearly
� “Malaria” could be “P. falciparum infection”, “P. vivax infection”, or “disease due to malarial infection”
� Time-Person-Place
� “Diarrhoea affects one out of four kids…”. Try: “The point prevalence of diarrhoea (defined as more than 3 stools per day) among children aged under 59 months living in camp A is 26.3%”
� Avoid absolute figures
� Numerator and denominator
� “120 nets were distributed…” (yeah, but how many people were targeted?)
� “130 cases occurred in August…” (in the entire country? in a district? out of how many people?)
� Try to not call them all a “rate”
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)6
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)7
Why compute epidemiological indicators?
� Describe morbidity
� Incidence
� Prevalence
� Losses in life expectancy and quality of life
� Describe mortality
� Mortality rate
� Excess mortality
� Describe coverage or effectiveness of relief interventions
� Different stages of interventions
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)8
Why compute epidemiological indicators?
� Describe morbidity
� Incidence
� Prevalence
� Losses in life expectancy and quality of life
� Describe mortality
� Mortality rate
� Excess mortality
� Describe coverage or effectiveness of relief interventions
� Different stages of interventions
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)9
� Computed among population at risk
� Neonatal tetanus?
� Prostate cancer?
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)10
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)11
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)12
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)13
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)14
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)15
Prevalence
� Population = 400
� Point prevalence on 1st January 2002 ?
1st January 2001 1st January 2002
IDHE Short course | London, 30 March-3 April 2009
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Prevalence
� 4 cases among 400 persons
� Point prevalence = 4 / 400 = 0.01 = 1 %
� Period prevalence in 2001?
1st January 2001 1st January 2002
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)17
Which would you describe with incidence or prevalence?
� Bloody diarrhoea due to type 1 shigella
� Falciparum malaria
� TB
� HIV/AIDS
� Herpes simplex
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)18
Proportional morbidity (all ages), February 2004
26,7%
14,8%
8,9%
18,4%
4,6%
5,1%
9,5%
9,2%
2,8%
malaria
schistosomiasis
watery diarrhoea
bloody diarrhoea
ARI
STD
worms
circulatory problems
others
Proportionate morbidity
consultations/admissions due to all causes
consultations/admissions due to disease
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)19
Other burden of disease indicators
� Disability Adjusted Life Years (DALYs) lost
� Years of Life Lost (YLL)
� Healthy Life Years (HeaLYs) lost
� QUALYs
� Mainly useful to compare diseases and rationalise aid and research allocation
� Based on consensual but arbitrary decisions on disability weights
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)20
Why compute epidemiological indicators?
� Describe morbidity
� Incidence
� Prevalence
� Losses in life expectancy and quality of life
� Describe mortality
� Mortality rate
� Excess mortality
� Describe coverage or effectiveness of relief interventions
� Different stages of interventions
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)21
� Unit: per n persons per unit time
� Emergencies: deaths per 10 000 per day (per 10 000 person-days)
� Alternatives: deaths/1000/month, deaths/1000/year
What is a mortality rate?
deaths during period
(population present during
period x time in the period)
Crude Mortality Rate =
deaths <5 yrs during period
(population <5 yrs present x
time in the period)
Under 5 Mortality Rate =
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)22
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)23
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)24
Emergency thresholds
� “Non-crisis” CMR in Sub-Saharan Africa: 0.3 to 0.6 per 10 000 per day (Sphere: 0.44), approximately double for U5MR
� Fixed thresholds: CMR 1 per 10 000 per day, U5MR 2 per 10 000 per day
� Context-specific thresholds (Sphere, 2004): doubling from pre-crisis values
� SSA: CMR 0.9, U5MR 2.3
� Latin America: CMR 0.3, U5MR 0.4
� Everyone agrees CMR should rapidly fall below 1!
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)25
CMR versus excess death tolls
Iraqi Kurds (CDC, 1991):
� CMR peak 10.4
� 3 months, population 400,000
� 6,200 excess deaths
DRC (IRC, 2004):
� CMR 0.7
� 16 months, population 64 million
� 500,000 excess deaths (3.8m since 1998)
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)26
Why compute epidemiological indicators?
� Describe morbidity
� Incidence
� Prevalence
� Losses in life expectancy and quality of life
� Describe mortality
� Mortality rate
� Excess mortality
� Describe coverage or effectiveness of relief interventions
� Different stages of interventions
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)27
Indicators for interventions
� Coverage
� Proportion (%) of people in need of intervention who actually
receive it
� Vaccination coverage
� Proportion of malnourished children receiving nutritional
rehabilitation
� Sometimes as a ratio: e.g. people per latrine ratio
� Effectiveness
� Proportion (%) of people who experience intended positive
outcome of intervention, out of those who actually receive it
IDHE Short course | London, 30 March-3 April 2009
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Effectiveness indicators
� Specify intended benefit!
� Many possible effectiveness measures for same intervention; e.g.
IRS could achieve
� Reduction in P. falciparum prevalence in general population (outcome)
� Reduction in incidence rate of clinical malaria among children <15y old
(outcome)
� Reduction in under-five mortality rate attributable to malaria (impact)
� Reduction in child mortality due to any cause (ultimate impact)
� Efficacy versus effectiveness
� Ideal versus field conditions
� For curative interventions: cure “rate”
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)29
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)30
Indicators to monitor interventionsIndicators to monitor interventions
� Coverage is never known, must be measured
� Effectiveness can often be assumed, so coverage = proxy for impact for some interventions (ex. vaccination, bednets, vitamin A)
� Effectiveness of health services can never be assumed
inputsinputs
processesprocesses
outputsoutputs
outcomesoutcomes
impactimpact
coverage x coverage x
effectivenesseffectiveness
coveragecoverage
DEATHSDEATHS
services providedservices provided
resources brought inresources brought in
IDHE Short course | London, 30 March-3 April 2009
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Diagnostic accuracy
� Sensitivity
� Proportion of true cases that are detected
� Specificity
� Proportion of true non-cases that are correctly classified as non-
cases
IDHE Short course | London, 30 March-3 April 2009
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� Relative risk
� risk in
exposed /
risk in
unexposed
� RR>1
� Risk factor
� RR<1
� Protective
factor
IDHE Short course | London, 30 March-3 April 2009
Disease Control in Humanitarian Emergencies (DCE)33
Conclusions
� Clear time-person-place reference
� Clear definitions
� Disease/condition
� Intervention or risk factor
� Intended benefit of intervention
� Numerator and denominator whenever possible
� Avoid vague or incorrect terminology
� We have to understand each other!