Transcript IDSP Module 7

Basic epidemiology for disease
surveillance
IDSP training module for state and
district surveillance officers
Module 7
Elements included in the module
1.
2.
3.
4.
Basic epidemiology relevant to surveillance
Ratios, proportions and rates
Incidence, prevalence and case fatality
Data presentation
• Tables
• Graphs
• Maps
Definition of epidemiology
Epidemiology is the study of the distribution
and determinants of health-related events or
states in population groups and the application
of this study to the control of health problems
(Last JM ed. Dictionary of Epidemiology, Oxford University Press, 1995)
Comparing the job of a clinician
and the job of an epidemiologist
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The clinician
Deals with patients
Takes a history
Conducts a physical
Makes a diagnosis
Proposes a treatment
Follows up the patient
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The epidemiologist
Deals with populations
Frames the question
Investigates
Draws conclusions
Gives recommendations
Evaluates programmes
The basic principles of
descriptive epidemiology
• Time
 When did the event happen?
• Place
 Where did the event happen?
• Person
 Who was affected?
3/7/04
3/5/04
3/3/04
3/1/04
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2/28/04
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2/26/04
Investigation
started
2/24/04
2/22/04
2/20/04
2/18/04
2/16/04
2/14/04
2/12/04
2/10/04
2/8/04
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2/6/04
2/4/04
2/2/04
1/31/04
1/29/04
1/27/04
1/25/04
1/23/04
1/21/04
1/19/04
1/17/04
1/15/04
1/13/04
1/11/04
1/9/04
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1/7/04
1/5/04
1/3/04
1/1/04
Number of cases and deaths
Time
Cases of acute hepatitis by date of
onset, Baripada, January-March 2004
Cases
Deaths
30
25
Strike
15
10
5
0
Place
Attack rate of acute hepatitis by zone of
residence, Baripada, Orissa, India, 2004
Attack rate
0 - 0.9 / 1000
1 - 9.9 / 1000
10 -19.9 / 1000
20+ / 1000
Underground water supply
Pump from river bed
Person
Attack rate of acute hepatitis by age and
sex, Baripada, Orissa, India, 2004
Cases
Age
Sex
Population
Attack rate
per 1000
1012
0.1
0-4
1
5-9
11
21802
2
10-14
37
74004
5
15-44
416
51358
81
45+
73
56153
13
Male
341
102683
3.3
Female
197
101646
1.9
Role of the host, the agent and the
environment in the occurrence of disease
Biologic,
Chemical,
Physical (injury, trauma)
Social
Psychological
AGENT
VECTOR
Genotype
Nutrition
Immunity
Behaviour
HOST
Sanitation
Weather
Pollution
Socio-Cultural
Political
ENVIRONMENT
Uses of epidemiology
1. Examine causation
2. Study natural history
3. Description of the health status of
population
4. Determine the relative importance of
causes of illness, disability and death
5. Evaluation of interventions
6. Identify risk factors
1. Examine causation
Genetic
factors
Good health
Environmental factors
(Biological, chemical,
physical, psychological
factors)
Ill health
Life style
related factors
2. Study natural history
Death
Good health
Sub-clinical
disease
Clinical
disease
Recovery
3. Description of the health status of
population
Prevalence of anemia among adolescent girls,
Mandla, MP, India 2005
Age in years
12-13
Hemoglobin <12 g%
Number
(%)
71
93.4
Total
76
14-15
88
93.6
94
16-17
71
97.3
73
18-19
27
77.1
31
Total
257
93.8
274
4. Determine the relative importance of
causes of illness, disability and death
Disease
Tuberculosis
Measles
Malaria
DALYs*
(000)
7577
6471
577
* Disability-adjusted life years
Mortality
(000)
421
190
20
Included in IDSP
Yes
Yes
Yes
5. Evaluation of interventions
Treatment,
Medical care
Good Health
Ill Health
Health promotion
Preventive measures
Public health services
6. Identify those sections of the
population which have the greatest risk
from specific causes of ill health
Factors associated with
anemia among pregnant women, Orissa, 2004
Characteristics
Univariate
odds ratio
(95% CI)
Adjusted odds
ratio
(95% CI)
Hookworm infestation
12 (5-29)
10 (4-24)
Consumption of IFA < 90 days
4.1 (2-8)
2.7 (1-7)
4 (3-7)
2.3 (1-4)
3.6 (2-6)
1.9 (1-4)
Education below middle school *
Number of pregnancy > 2
* Middle school = Seventh class in Orissa
Epidemiological approaches
• Descriptive epidemiology:
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What is the problem?
Who is involved?
Where does the problem occurs?
When does the problem occurs?
• Analytical epidemiology:
 Attempts to analyze the causes or determinants of disease
• Intervention or experimental epidemiology:
 Clinical or community trials to answer questions about
effectiveness of control measures
Count, divide and compare:
The basis of epidemiology
1. Count the number of new AIDS cases in two cities
No. of new of AIDS cases
City A
City B
58
35
Count, divide and compare:
The basis of epidemiology
2. Divide the number of cases by the population
New AIDS cases
Number
Year
Population
City A
58
2004
25,000
City B
35
2004-5
7,000
City A: 58/25,000/ 1 year
City B: 35/7,000/ 2 years
Count, divide and compare:
The basis of epidemiology
3. Compare indicators
City A: 232/100,000/ year
City B: 250/100,000/ year
A ratio places in relation two quantities
that may be unrelated
• The quotient of two numbers
• Numerator NOT necessarily INCLUDED in the
denominator
• Allows to compare quantities of different
nature
= 5 / 2 = 2.5/1
Examples of ratio
• Number of beds per doctor

85 beds for 1 doctor
• Number of participants per facilitator
• Sex ratio:
 Male / Female
A proportion measures a
subset of a total quantity
• The quotient of two numbers
• Numerator NECESSARILY INCLUDED
in the denominator
• Quantities have to be of the same nature
• Proportion always ranges between 0 and 1
• Percentage = proportion x 100
2 / 4 = 0.5=50%
Example of proportion
• Tuberculosis cases in a district:
 400 male cases
 200 female cases
• Question
 What is the proportion of male cases among all
cases?
 What is the proportion of female cases among all
cases?
A rate measures the speed of occurrence
of health events
• The quotient of two numbers
• Defined duration of observation
• Numerator
 Number of EVENTS observed for a given time
• Denominator (includes time)
 Population at risk in which the events occur
Observed in 2004
2
----- = 0.02 / year
100
Example of rate
• Mortality rate of tetanus in country X in 1995
 Tetanus deaths: 17
 Population in 1995: 58 million
 Mortality rate = 0.029/100,000/year
• Rate may be expressed in any power of 10
 100, 1,000, 10,00, 100,000
Measures of disease frequency
• Prevalence
 Number of cases of a disease in a defined
population at specified point of time
• Incidence
 Number of new cases, episodes or events occurring
over a defined period of time
Prevalence
P=
Number of people with
the disease or condition
at a specified time
Total population at risk
X Factor
Incidence rate
I=
Number of people who get
the disease or condition
in a specified time
Total population at risk
X Factor
Case fatality ratio
• Divide
 Number of deaths
 Number of cases
• Example: Measles outbreak
 3 deaths
 145 cases
 Case fatality ratio: 2.1%
Presenting health information
• Tables
• Graphs
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Histograms
Line diagrams
Bar chart
Pie chart
Scatter plot
Map
Tables
• Data presented in columns and rows by one
or more classification variable
• Title- Concise, self explanatory explaining
clearly all information being presented
• Rows and columns should be clearly labeled
• Categories should be clearly shown
Example of one way table:
Data tabulated by one variable
Age distribution of a sample of
100 villagers
Age group (years)
Number
0-4
19
5-14
25
15-44
40
45+
16
Total
100
Example of two way table:
Data tabulated by two variable
Age and sex distribution of a sample of 100 villagers
Age group (years)
Male
Female
Number
0-4
10
9
19
5-14
12
13
25
15-44
20
20
40
7
9
16
49
51
100
45+
Total
Graphs
• Charts based on length
• Bar charts (horizontal, vertical, grouped, stacked)
• Charts based on proportion
• Pie chart
• Geographic co-ordinate charts (maps)
• Spot map
• Area map
35
30
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
Incidence of malaria per 10,000
Line graph for time series
Malaria in Kurseong block, Darjeeling
District, West Bengal, India, 2000-2004
45
40
Incidence of malaria
Incidence of Pf malaria
25
20
15
10
5
0
2000
2001
2002
Months
2003
2004
Histogram to display a frequency
distribution
• Graphic representation of the frequency distribution
of a continuous variable
• Rectangles drawn in such a way that their bases lie
on a linear scale representing different intervals
• Areas are proportional to the frequencies of the
values within each of the intervals
• No spaces between columns
• No scale breaks
• Equal class intervals
• Epidemic curve is an example of histogram with
time on the x axis
Histogram
Urinary iodine excretion status, 24 N
Parganas, West Bengal, India, 2004
Percentage
80
60
40
20
0
0-19.9
20-49.9
50-99.9
100-300
Urinary Iodine Excretion levels (µg/L)
> 300
Epidemic curve
90
80
70
60
50
40
May
June
July
Week of onset
August
1st week
4th week
3rd week
2nd week
1st week
4th week
3rd week
2nd week
1st week
4th week
2nd week
1st week
4th week
3rd week
2nd week
10
0
3rd week
30
20
1st week
Number of cases
Acute hepatitis by week of onset in 3
villages, Bhimtal block, Uttaranchal, India,
July 2005
September
Proportions of a total presenting
selected characteristics
• Breakdown of a total in proportions:
 Pie chart
• Breakdown of more than one total into
proportion:
 Juxtaposed bar charts cumulated to 100%
Pie chart for the breakdown of a total in proportions
Types of unintentional injuries,
Tiruchirappalli, Tamil Nadu, India, 2003
Incidence:
9.6 per 100 person-month
(95% C.I. 8-11
Minor injuries
35%
Road
10%
Fall
32%
Burns
7%
Bites
16%
Cumulated bar chart for the breakdown
of many totals in proportions
Proportion (%)
Estimated and projected proportion of
deaths due to non-communicable
diseases, India, 1990-2010
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Injuries
Communicable
diseases
Non communicable
diseases
1990
2000
Year
2010
Comparing proportions across groups
• No logical order: Horizontal bar chart
 Sort according to decreasing proportions
• Logical order: Vertical bar chart
 Not a continuous variable: Do not display axis
 Continuous variable: Display axis
Horizontal bar chart
Causes of non vaccination as reported by the
mothers, Bubaneshwar, Orissa, India, 2003
Lack of awareness
Child sick
Irregularity by health staff
Lack of motivation
Lack of time
Lack of facility
Lack of money
0%
India FETP
20%
40%
60%
80%
100%
Vertical bar chart
Prevalence of hypertension by age and
sex, Aizawl, Mizoram, India, 2003
70
60
%
50
40
Male
30
Female
20
10
0
30-39
40-49
50-59
Age group (years)
60-69
70 +
Spot map
Cholera cases by residence, Kanchrapara,
N-24 Parganas, West Bengal, India, 2004
Incidence by area
Incidence of acute hepatitis by block,
Hyderabad, AP, India, March-June 2005
Attack rate per
100,000
population
0
1-19
20-49
50-99
100+
Open drain
Pipeline crossing
open sewage drain
Hypothesis generated:
Blocks with hepatitis are those
supplied by pipelines crossing
open sewage drains