3. Learning Objectives
• At the end of this session the student is
expected to: Describe epidemiological
approach to disease causation
4. Learning Objectives cont,,,
• At the end of this unit the student is expected
to:
1. Define cause of disease
2. Discuss the different risk factors for
disease
5. Concepts of Disease Occurrence
• Disease and other health events do not occur
randomly in a population, but are more likely to
occur in some members of the population than
others because of risk factors that may not be
distributed randomly in the population.
• one important use of epidemiology is to identify
the factors that place some members at greater
risk than others.
6. Causal Concepts of Disease
Definition :-Cause of disease: is an event,
condition, characteristic or a combination
of these factors which plays an important
role in producing the disease
7. Cont…
• Not all associations between exposure and
disease are causal. A cause of a disease can
be defined as a factor (characteristic,
behavior, event, etc.) that influences the
occurrence of disease.
8. The causes of disease can be
classified in to two:
• 1. Primary causes – these are the factors
which are necessary for a disease to
occur, in whose absence the disease will
not occur.
9. Cont…
• The term ”etiologic agent” can be used
instead of primary cause for Infectious
causes of diseases.
• For example “Mycobacterium tuberculosis”
is the primary cause (etiologic agent) of
pulmonary tuberculosis.
10. 2. Risk factors (contributing, predisposing, or
aggravating factors
• These are not the necessary causes of disease
but they are important for a disease to occur.
• the presence of an association does not necessarily
imply that there is a causal relationship between
the two factors
11. Cont…
• A factor associated with an increased
occurrence of a disease is risk factor for
the exposed group;
• and a factor associated with a decreased
occurrence of a disease is a risk factor for
the non exposed group.
12. The etiology of a disease is the sum total of all the
factors (primary causes and risk factors)
which contribute to the occurrence of the disease.
• It is the interaction of the agent, the host, and the
environment which determines whether or not a
disease develops, and
• this can be illustrated using the epidemiologic
triangle.
13. Exercise 1
Identify the primary causes and risk factors for
the following diseases
Disease Primary cause Environmental risk factors Host risk
factors
1.Malaria
2.TB
3.HIV/AIDS
15. Epidemiological models in
disease causation
• In recognition of the multi-factorial
nature of most diseases such as heart
disease and many cancers several
models have been proposed.
16. Cont…
• Their are several well-known disease
causation models, such as the triangle,
the wheel, and the web.
• These models help to organize ideas
about causes and about strategies to
prevent and control disease
17. cont…
• Those models emphasize that there
is no single cause, causes of disease
are interacting, disentangling the
cause is highly impossible, and
causality may be two ways (reverse
causality)
18. • In disorders with multi-factorial
causation often no specific causes are
known, many factors appear to be
important, and mechanisms of causation
are not apparent...
19. Cont…
• Models such as the Wheel of causation and
spider’s web are attempts to portray
complex causation interactions.
• The purpose of the models is to simplify
reality and make easier to grasp the
essence of the issue.
20. Cont…
• Narrow causal thinking based on single
causes can be misleading; pointing to
premature believing that a problem is
solved and can seriously distort public
health action
21. Models of cause in epidemiology
1. epidemiological triangle (Interplay of
host, agent, and environment)
The idea that disease is virtually always a
result of the interplay of the environment,
the genetic and physical make-up of the
individual, and the agent of disease,
22. Cont…
This theory applies both to diseases said to
be multi-factorial (e.g. cancers or heart
disease) and
to diseases which are by their definition a
result of a single cause, such as
tuberculosis, a drug side-effect or an
overdose.
23. Cont…
The underlying cause of the disease is a
result of the interaction of several
factors, which can be analyzed using the
components of the epidemiological
triangle
25. 1. What are elements of the host that may
affect occurrence and spread of disease?
Give some examples
2. What are elements of the agent that may
affect occurrence and spread of disease?
Give some examples
3. What are elements of the environment
that may affect occurrence and spread of
disease? Give some examples
26. Agent
examples of agent factors
• infectious micro-organism- virus,
bacteria, parasite, or other microbe Causes
of diseases:
• Virulence of organism, Serotype of organism
• Antibiotic resistance, Cigarette—tar content
27. Host
Host factors influence individual's exposure,
susceptibility or response to a causative agent.
example- age, sex, Previous disability, Genetic
inheritance ,Height and weight
race, socioeconomic status, and behaviors
(smoking, drug abuse, lifestyle, sexual practices
and contraception, eating habits) affect
exposure.
28. Environment
Environmental factors are extrinsic factors
which affect the agent and the opportunity for
exposure
examples of environmental factors
•Home overcrowding,
•Workplace hygiene, Weather
•Water composition, Food contamination
•Animal/human contact,
29. Cont…
• Physical factors:- such as climate, and
physical surrounding (e.g., maternal waiting
home, hospital)
• biologic factors:- such as insects that
transmit the agent
• socioeconomic factors :-such as crowding,
sanitation, and the availability of health
services
30. Host, Agent, Environment
Host Agent Environment
Age
Sex
Religion
SES
Exercise
Behavior
Co-morbidity
Genetics
Biologic
Microorganisms
Chemical Toxins
Physical Trauma
Nutrition
Disease vectors
Population density
Air quality
Weather
Noise
Food and water
sources
31. Host, Agent, Environment
Host Agent Environment
Age
Sex
Religion
SES
Exercise
Behavior
Co-morbidity
Genetics
Biologic
Microorganisms
Chemical Toxins
Physical Trauma
Nutrition
Disease vectors
Population density
Air quality
Weather
Noise
Food and water
sources
32. Host, Agent, Environment
Host Agent Environment
Age
Sex
Religion
SES
Exercise
Behavior
Co-morbidity
Genetics
Biologic
Microorganisms
Chemical Toxins
Physical Trauma
Nutrition
Disease vectors
Population density
Air quality
Weather
Noise
Food and water
sources
33. Cont…
• microbe to inanimate agents of disease.
The interaction of the host, agent, and
environment is rarely understood.
• For example , the effect of cigarette
smoking is substantially greater in poor
people than in rich people the reason is
unclear.
34. Cont…
It may be that there is an interaction between
• the agent (cigarettes), susceptibility due to
host factors such as nutritional status, or
• environmental factors such as air quality in
the home, in the residential neighborhood or
in the workplace.
35. wheel of causation model
• The principles behind this model are as for the
triangle, but it emphasizes the unity of the
interacting factors.
• The genetic make-up of the individual and its
expression in the body(phenotype) is shown as the
hub of the wheel, but enveloped within an
Interacting environment.
36. Cont…
• the model is applied to phenyl-keton-uria,
the genetic disorder. Pheny-lketon-uria is
an autosomal single gene disease.
• Phenylalanine hydroxylase, an enzyme
required to metabolize the dietary amino
acid phenyl-anine and turn it into tyrosine,
is deficient,
• and so phenylalanine accumulates in the
blood. Brain damage is the outcome.
37. • Early diagnosis, usually through screening, and
dietary manipulation can prevent the disease.
• The cause of this disease could be said to be a
faulty gene .
• More accurately, and to clinical and public
health benefit, the cause of the disease could
be considered as a combination of a faulty
gene, exposure to a chemical and biological
environment
Cont…
38. Cont…
• which provides a diet containing a high amount
of phenyl-alanine (about 15 per cent of the
protein of most natural foods),
• and in the case of failure of diagnosis and
dietary advice, a social environment unable to
protect the child from the consequences of a
gene disorder.
39. Cont…
• Physical environment:
– availability of healthcare
– facilities for diagnosis
• Social environment:
– social support to sustain
– dietary change
• Chemical & biological environment:
– diet content
40. The model emphasizes the unity of the gene and host within an
interactive environmental envelope .The overlap between
environmental components emphasizes the arbitrary distinctions
Wheel of causation -Physical
environment
social
environment
Chemical &
biological
environment
geggge
Gene/
host
41. Cont…
• In disorders with multifactorial causation often
no specific causes are known, many factors
appear to be important, and mechanisms of
causation are not apparent.
• The complexity of these diseases is not
adequately captured by the wheel, and triangle
concepts (which remain useful however) and is
better portrayed by the metaphor of the spider’s
web
42. web of causation
• The web is shown as a highly schematized
diagram, more like an electronic circuit or
an underground transport map.
• Such portrayals tend to underestimate the
complexity and overestimate the state of
understanding.
43. web of causation cont…
• emphasizes the interconnections among
the postulated causes. This model, more
than the others, indicates the potential
for the disease to influence the causes
and not just the other way around.
44. Cont…
• For example, lack of exercise may be one
of the causes of heart disease and
osteoporosis but these diseases can also
cause people to stop exercising (reverse
causality).
45. CONT…
The metaphor of the web permits the still
broader causal question: where is the
spider that spun the web?
The question can be answered at a number
of levels, for example, evolutionary biology,
social structures, and role of industries.
46. Cont…
• The relatively simple analysis of heart
disease causation using the web concept
begins to illustrate the great complexity
of this disease
47. web of causation cont…
In the 1960s, another causal paradigm—the
web of causation—gained popularity because it
was more useful for understanding the causes of
noninfectious diseases.
Consider, for example, lead poisoning, The
causal web shows that its occurrence can be
explained by a complex web of many
interconnected factors, including both host and
environmental determinants.
48.
49. Cont…
•It illustrates that there are many ways to become
lead poisoned, and that these pathways or causes
may differ from person to person.
•For example, a young child may become lead
poisoned by ingesting dust that has been
contaminated with lead from crumbling paint,
industrial pollution, or automobile traffic.
•On the other hand, an adult may become lead
poisoned from workplace exposures such as bridge
work, or a hobby such as stained glass work.
50. Web Causation of lung cancer
Think through the cause of lung cancer and
applying the epidemiological web of disease
causation model.
51. The complex cause of lung cancer is better
portrayed by the metaphor of the spider’s
web of disease causation.
In order to appreciate its complexity let us
emphasize let us emphasize separately the
interconnections among the suggested causes
of lung ca.
52. Sex: Top public enemy in western world with
significant increase in incidence dramatic increase
among females
Environmental: there are over 1200 identified
carcinogenic substances categorized into Initiaters
(eg. Benzo[o]pyrenes) Promoters (eg. Phenol
derivatives) Radioactive carcinogen substances (eg.
Polonium, C14, K40) which contributes the lung ca
development, which can be from - Industrial hazards
-High dose ionizing radiation – Asbestos dust
(Asbestos exposure 20% of the deaths is ascribed to
lung ca) and other sources of pollutions.
53. Genetic: with the same dose of carcinogenic
matter exposure (from smoking, radiation and
occupation) there is individual difference to
develop lung ca, while some people are more
prone to develop with scientifically proven
hereditary linkage (eg. chromosomal or DNA
guardian gene defect).
Individual behavior: 90% of lung cancers are
related to smoking! (Passive smoking 5%)
54. Necessary and sufficient cause
• Epidemiological thinking on causality has
been deeply influenced by the concepts
of necessary and sufficient cause, which
are easily confused.
• The fourth edition of Last’s Dictionary
tells us that a necessary cause is ‘A causal
factor whose presence is required
55. Cont…
• for the occurrence of the effect.’ Last’s
Dictionary defines sufficient cause as a
‘minimum set of conditions, factors or
events needed to produce a given
outcome
56. Cont…
• These causal models also help us to
understand the ideas of necessary or
sufficient causes.
57. Causal Concepts of Disease cont…
• If disease does not develop without
the factor being present, then we term
the causative factor "necessary".
• If the disease always results from the
factor, then we term the causative
factor "sufficient".
58. Causal Concepts of Disease cont…
Example:
• Tubercle bacillus is a necessary
factor for tuberculosis.
• Rabies virus is sufficient for
developing clinical rabies.
59. Causal pie
• Causal pie is one of the models that take
into account multiple factors which are
important in causation of disease.
• In the causal pie model, the factors are
represented by pieces of the pie called
component causes
60. Rothman's Causal Pies: Conceptual
Scheme for Disease Causation
All factors (component causes) together form the
sufficient cause while component cause
A constitutes the necessary cause.
63. Cont…:
• Time variables
– Occurrence of disease change over time
– Seasonality
• Person variables
– age, sex, socio-economic, etc. characteristics of illness
• Place variables
– natural boundaries,, urban/rural,, altitude differences
64. Time, Place, and Person
Time and Place are used to link individuals
– Chain of transmission,
e.g., Malaria, (history of travel and time)
– During epidemic,
e.g., cases identification using case definition
• Individual risk and disease occurrence are
examined in relation to
– geographic location and calendar time
65. DESCRIPTION OF THE OCCURRENCE OF DISEASE BY
TIME
• Time is the necessary element in the definition
of every epidemiologic measure
• It is also a basic component of the concept of
Cause (Rate dimension)
• Time could be expressed in hours, days,
months, or years
• Variety of time trends may be found showing
increase or decrease in incidence
66. Place
• Geographic variation in disease occurrence
–Urban-rural differences
–Location of worksites (exposure)
–Altitude differences
–Aggregated SES difference
67. Geographical variation
• Geographical distribution of disease
– Malaria
– Schistosomiasis
– Parasitic infection
• Distribution of risk factors
– Chemicals/ radiation etc
– Health service
• History of travel to endemic areas
– Malaria
– SARS
– Avian flue etc
69. PERSON
Age Sex
Marital status Occupation
Travel Immunization status
Personal habits Presence of stress
Underlying disease
Medication Family
Nutritional status School
Socioeconomic factors Genetics
Crowding Religion
70. • Personal characteristics can affect occurrence of
disease
• Analysis of data by person may use
– Inherent characteristics (age, race, sex etc)
– Biologic characteristic (immune status)
– Acquired characteristics (Marital status)
– Activities (exercise, use of medication, nutrition
etc)
– Living status (SES)
71. Cont…
Age:
• An important variable in epidemiological studies
• Every health status is dependent to age
• Age groups may be used to compare groups
Sex:
• Associations between sex and disease are evidenced
in many disease
• Genetic, hormonal, anatomic and other inherent
difference occur between men and women
72. Cont…
Marital Status:
• A descriptive variable, which appears on medical and civil,
records almost as regularly as age and sex.
• Stratification into groups
– Single, married, divorced, widowed, is usually not a difficult problem
– lowest mortality is for married persons and highest for widowed and
divorced for both sexes
– the mortality rates for single are also higher than the married
74. Learning Objectives
At the end of this unit the student is
expected to:
• Define the natural history of disease
• identify its different stages
• Describe the levels of disease prevention
75. Natural History of Diseases
The natural history of disease refers to the
progression of a disease process in an individual
over time, in the absence of intervention.
• The process begins with exposure to the causative
agent capable of causing disease. Without medical
intervention, the process ends with recovery
disability, or death.
77. Natural History of Diseases cont…
• Most diseases have a characteristic
natural history, although the time frame
and specific manifestations of disease
may vary from individual to individual.
• The usual course of a disease may be
halted at any point in the progression by
preventive and therapeutic measures, host
factors, and other influences.
78. Natural history of disease
• The course of the disease in the absence of any
intervention is called natural history of disease.
• Each disease has its own life history. The stage in
the natural history disease will help as to
understand the intervention measures that could
be undertaken to prevent or control the disease.
79. Cont,,,
• For example, untreated infection with HIV
causes a spectrum of clinical problems
beginning at the time of sero conversion
(primary HIV) and terminating with AIDS and
usually death.
• It is now recognized that it may take 10 years
or more for AIDS to develop after sero-
conversion
80. Cont,,,
• The process begins with the appropriate exposure to
or accumulation of factors sufficient for the disease
process to begin in a susceptible host.
• For infectious disease, the exposure is a
microorganism. For cancer, the exposure may be a
factor that initiates the process, such as asbestos
fibers or components in tobacco smoke (for lung
cancer), or one that promotes the process such as
estrogen (for endometrial cancer).
81. Natural history of disease cont…
The different stages in the natural history of the
disease includes
1. Stage of susceptibility:
• This is a stage in which disease has not
developed but the ground work has been laid
by the presence of risk factors that favor its
occurrence
Example:
- Unvaccinated child is susceptible for measles
- Obesity is a risk factor for DM & heart disease
82. Natural history of disease cont…
2. Presymptomatic disease (sub clinical stage):
• In this stage, there is no clinical manifestation of
disease.
• The patient does not know that he has any disease
• In some infectious disease the agent enters and
multiplies in the body with out any sign and
symptom.
Example: Ova of intestinal parasite in the stool of
apparently health child
• The sub clinical stage of disease may lead to the
clinical stage or the individual may recover with out
developing sign and symptom
83. Natural history of disease cont…
3. Clinical stage:
• In this stage the person has sign and symptom of the
disease.
• There is various grade of illness with different out
comes depending on the agent-host infection.
• Some diseases are short and mild out comes.
• E.g. common cold, others are very series leading to
complication and death.
• E.g. rabies leads to death; poliomyelitis can lead to
permanent disability or death.
84. Natural history of disease cont…
4. Stage of disability:
• Some diseases run their course and then resolve
completely either spontaneously or under the
influence of therapy.
• There are conditions which give sequel of defect
for a short time or long duration leaving the
person disabled to a grate or leaser effect.
Disability can be defined in various ways; in a
community survey it usually means any limitation
of person activities including their roles as
parents, wage earning and members of any social
activities
85. Natural history of disease cont…
• NB- Natural recovery with out any
intervention cans occur at any stage in the
progression the disease. This might be due to
adaptation of the individual with having the
strong immune system.
86. Level of prevention
Level of prevention
• Epidemiology plays a central role in disease
prevention by identifying those modifiable
causes.
• There are three/four important ways that
health workers can prevent the development
of disease.
87. Primordial prevention
• The aim is to avoid the emergence and
establishment of the social, economic, and
cultural patterns of living that are known to
contribute to an elevated risk of disease
• Target total population and selected group
• Ex. smoking, environmental pollution
88. Level of prevention cont…
Primary prevention
• The main objective of primary prevention is
Promoting health, preventing exposure and
prevents disease.
• Primary prevention keeps the disease process
from becoming established by eliminating
causes of disease or increasing resistance to
the disease.
89. cont…
PRIMERY PREVENTION:-Examples are
activities include a healthy diet; regular exercise;
avoidance of smoking; sunscreen use;
immunizations against infectious diseases;
policies to maintain a clean supply of water, air,
and food; and safe home and work environments.
Public and medical education campaigns at the
individual and community levels and
governmental legislation are among the many
ways the general public becomes aware of and
adopts behaviors and policies to prevent disease.
90. cont…
Health promotion: consists general of non specific
intervention that enhance health and the body’s
ability to resist disease
Examples:
• improvement of socioeconomic status
• provision of adequate food, housing, clothing
• provision of education and vocational trainings
91. Level of prevention cont…
Prevention of exposure: is the avoidance of factors
which may cause disease if an individual is
exposed to them.
Examples - Provision of safe and adequate water,
proper excreta disposal and vector control.
Prevention of disease:
is the prevention of disease development after
the individual has become exposed to the disease
causing factors. The timing is between the
exposure and biological onset
Example: Immunization
92. Level of prevention cont…
Secondary prevention
• It involves detecting people who already have the
disease as early as possible and treat them
• It is carried out after the biological onset of the
disease but before permanent damage sets in.
• The objective of this level of prevention is to stop
or slow the progression of disease and to prevent
or limit permanent damage.
Examples
• -prevention of blindness from trachoma
• -early detection and treatment of breast cancer to
prevent its progression to the evasive stage
93. Secondary prevention of infectious diseases may
have the added benefit of reducing or halting the
spread of disease. For example, early screening,
accompanied by counseling and drug therapies,
may reduce the spread of HIV by reducing risky
behaviors and virus levels in semen
94. The goal of tertiary prevention is to slow or block
the progression of a disease, thereby reducing
impairments and disabilities, and improving the
quality of life and survival among diseased
individuals.
It is implemented after a clinical diagnosis has
been made and may include prompt treatment,
proper follow-up and rehabilitation, and patient
education.
95. A typical example of tertiary prevention is the
•Use of drugs to prevent opportunistic infections
among HIV-infected individuals.
•Fewer life-threatening infections and fewer
difficult-to-follow treatment regimens and
hospitalizations substantially improve the quality
of life and survival among HIV-infected people.
96. •Another example of tertiary prevention is
careful control of insulin levels and patient
education to prevent retinopathy and other
complications among patients with diabetes.
• The three levels of prevention and their
impact on disease are summarized in
97. Level of prevention cont…
Tertiary prevention
• Its target is towards people with chronic disease and
disabilities that cannot be cured.
• Tertiary prevention is needed in some diseases because
primary and secondary prevention have failed, are in
others because primary and secondary are not effective
It has two objectives:
• Treatment to prevent further disability or death
• To limit the physical, psychological, social and financial
impact of disability by improving the quality of life
Examples
• - Blindness due to vitamin A deficiency
• - Diabetes mellitus
98. Level of prevention cont…
The table below shows the summery of the three levels of prevention.
Level of prevention definition Timing Objective
Primary - promotive and prevention - before the - promote health/premodral
Biological onset and prevent disease.
the disease
– prevent exposure
Secondary -early detection & treatment -after the biological - to stop/ slow
of disease on set but before progression of
on set of damage disease to limit
Permanent damage
Tertiary -limitation of disability and - after the onset of - to limit the physical,
enhance rehabilitation permanent damage social and financial
impact of disability.
100. What is screening?
It is the early detection
– of disease,
– precursors to disease, or
– susceptibility to disease
in individuals who do not have signs and
symptoms of a disease
100
101. Screening cont…
Screening is defined as follows: “The presumptive
identification of an unrecognized disease or defect
by the application of tests, examinations or other
procedures which can be applied rapidly.
Screening tests sort out apparently well persons
who probably have a disease from those who
probably do not.
102. Screening cont…
A screening test is not intended to be diagnostic.
Persons with positive or suspicious findings must
be referred to their physicians for diagnosis and
necessary treatment.
People who are found to have the disease are
then treated more effective treatment that, in
turn, will decrease the adverse effects of a disease
and improve survival.
103.
104. Characteristics of a Screening Test
In order for screening to be successful, the
screening test must be economical,
convenient, relatively free of risk and
discomfort, acceptable to a large number of
individuals, and highly valid and reliable.
105. Currently screening tests that meet these criteria
include serology tests for markers for HIV, hepatitis B,
and tuberculosis;
mammograms for the detection of breast cancer; PAP
smears for cervical cancer; blood pressure monitoring and
cholesterol screening for heart disease;
stool guaiac tests for colorectal cancer; and vision tests for
glaucoma.
The following section describes in more detail the
characteristics of a suitable screening test.
106. Diagnostic and Screening tests
• Diagnostic and screening tests are useful for a
decision to initiate or continue a therapeutic
(preventive) intervention.
Screening tests
• are tests done in individuals with no such symptoms
or sign.
• Tests done on apparently health persons
Diagnostic tests
• are tests performed in persons with signs and
symptoms of an illness.
• Tests performed in patients
106
107. Diagnostic and screening tests
May be based on
– Standardized interviews,
– Physical examinations,
– Laboratory tests,
– More sophisticated measurements
• radiography, CT scan
• electro-cardiograph,
107
108. Examples of Screening Tests
• Pap smear
• Mammogram
• Clinical breast exam
• Blood pressure determination
• Cholesterol level
• Eye examination/ visual test
• Urinalysis
109. The Screening pathway
Healthy
Disease or
precursor detectable
Symptoms develop
Advance disease
Death
Screening possible
Intervention to avert
disease development
Life prolonged
109
110. •Screening is used mainly to iify
asymptomatic individuals at an
earlier stage than if they waited for
symptoms to arise.
•An important assumption is that
earlier diagnosis will lead to earlier,
Screening cont…
111. Clinical aim of Screening
• To reduce morbidity and mortality through
early detection and treatment
• To reverse, halt, or slow the progression of a
disease to its sever form
111
112. Public Health aim of Screening
• To protect society from contagious disease
• To reduce mortality
• For rational allocation of resources
• To study on natural history of disease…
Other Use:
• Selection of healthy individuals usually for
employment
Ex. - military,
- driving license …
112
113. Screening tests
1. Validity (accuracy) of test
a. Sensitivity b. Specificity
2. Performance of screening test
a. Predictive Value Positive (PV+)
b. Predictive Value Negative (PV-)
3. Reliability
a. Percent agreement b. Cohen's Kappa
113
114. •The characteristics of a successful screening test,
examination, or procedure include low cost,
minimal risk, convenience, acceptability, and
reliability.
•The test must also have a high degree of validity,
as measured by sensitivity and specificity.
115. •Sensitivity is the probability that a test
correctly classifies individuals with preclinical
disease as positive;
•specificity is the probability that a test
correctly classifies individuals without
preclinical disease as negative.
116. •Predictive value positive is the proportion of
individuals with a positive test who have preclinical
disease;
•predictive value negative is the proportion of
individuals with a negative test who do not have
preclinical disease.
117. A high predictive value positive, (PVP)
which is crucial to the success of a screening
program, is attained by increasing the
sensitivity and specificity of the screening test,
and
-by targeting a population whose detectable
preclinical phase is fairly prevalent
118. Evaluation of Screening test
It is usually done using two-by-two table
Test Result
Disease Status (Gold Standard)
Present Absent
Positive True Positive (a) False Positive (b)
Negative False Negative (c) True Negative (d)
Two conditions are important
1. Actual occurrence of a disease (usually measured by
the best diagnostic instrument called (gold standard)
2. The new diagnostic instrument to be evaluated
118
119. Sensitivity of a Screening Test
Sensitivity: Proportion of people with a disease who
tested positive for the screening test
e
Test Result
Disease Status (Gold Standard)
Present Absent
Positive True Positive (a) False Positive (b)
Negative False Negative (c) True Negative (d)
a +c
a
Sn =
True Positive
True Positive + False Negative
Sn =
119
120. Specificity of a Screening Test
Specificity: is the proportion of people without a disease
who tested negative for the screening test
Test Result
Disease Status (Gold Standard)
Present Absent
Positive True Positive (a) False Positive (b)
Negative False Negative (c) True Negative (d)
b +d
d
Sp =
True Negative
True Negative + False Positive
Sp =
120
121. Positive Predictive Value
Positive predictive value:
• is the proportion of cases with a disease out of
people who tested positive on the screening
• It measures the yield of a screening test
Test Result
Disease Status (Gold Standard)
Present Absent
Positive True Positive (a) False Positive (b)
Negative False Negative (c) True Negative (d)
a +b
a
PV+ =
True Positive
True Positive + False Positive
PV+ =
121
122. Negative Predictive Value of a Screening Test
Negative predictive value :
is the proportion of actual non-cases among those who
tested Negative for the screening
Test Result
Disease Status (Gold Standard)
Present Absent
Positive True Positive (a) False Positive (b)
Negative False Negative (c) True negative (d)
c +d
d
pv- =
True Negative
True Negative + False Negatives
Pv- =
122
123. Predictive Value Positive (Yield)
The yield of a test result is affected by:
• Specificity of the test
• Prevalence of the disease
Test Result
Disease Status (Gold Standard)
Present Absent
Positive True Positive (a) False Positive (b)
Negative False Negative (c) True negative (d)
123
124. Example: Effect of sensitivity, specificity
and prevalence
Test Result
Disease Status (Gold
Standard)
Total
Present Absent
Positive 450 20 470
Negative 10 450 460
460 470 930
Prevalence = ?
Sensitivity= ?
Specificity= ?
PV+ = ?
PV- = ?
124
125. Change Sensitivity to 50%
Test Result
Disease Status (Gold
Standard)
Total
Present Absent
Positive 500
Negative 500
500 500 1000
Calculate:
PV+
PV-
125
126. Change Prevalence to 20%
Test Result
Disease Status (Gold
Standard)
Total
Present Absent
Positive 500
Negative 500
200 800 1000
Calculate:
PV+
PV-
126
127. • Select a test with high specificity
– High sensitivity >> Low false Negative ( C) >> High PV-
– High specificity >> Low false Positive ( B) >> High PV+
• Select disease with high prevalence of pre-clinical stage
• Target high risk groups for screening
Test Result
Disease Status (Gold Standard)
Present Absent
Positive True Positive (a) False Positive (b)
Negative False Negative (c) True negative (d)
127
128. Reliability
• Refers to the degree to which results obtained
can be replicated.
• Reliability can be lowered due to
• The measurement instrument
• Instability of the attribute being measured
(Intra-subject variation)
• The observers (Inter-observer)
129. Reliability
Reliability is measured using Percent agreement and
Cohen’s Kappa
1. Percent agreement is the ability of a screening
program to correctly classify individuals either as
truly affected or truly unaffected
It is proportion of correctly categorizing of individuals
among the total tested individuals
2. Cohen’s Kappa is an appropriate reliability measure
(or measure of agreement) for a screening test
which gives a categorical result
It considers agreement that may occur by chance alone
129
130. 1. Percent agreement
TP + TN
TP + FN + TN + FP
a + d
a + c + d + b
or
Test Result
Disease Status (Gold Standard)
Present Absent
Positive True Positive (a) False Positive (b)
Negative False Negative (c) True Negative (d)
Correctly diagnosed
Total tested
130
131. Cont…
• Its value usually ranges between 0 and 100%
(ie, the more it is nearer to 100%, the more both
instruments agree to each other)
• Percent agreement is directly related with increment in
proportion of true negatives and specificity of a test
• It is inversely related with prevalence of the disease
measured
131
132. Criteria for population based screening
1. Knowledge of disease
2. Feasibility of screening procedures
3. Diagnostic and treatment
4. Cost consideration
132
133. 1. Knowledge of disease
• The condition must be an important problem
(severity, prevalent)
• There should be a recognizable latent or early
symptomatic stage
(pre-clinical recognition)
• The natural history of the condition, including
development from latent to declared disease,
should be adequately understood
133
134. Natural History of a disease
Stage of
Susceptibility
Stage of
sub-clinical disease
Stage of
Clinical disease
Stage of recovery,
disability or death
Of diagnosis
Usual Time
Exposure Pathologic Onset of
changes symptoms
Time of
Screening
134
135. 2. Feasibility of screening procedures
• There should be a suitable test or examination
(High sensitivity and specificity)
• The test should be acceptable to the population
(Taking saliva test Vs taking occult blood from rectum)
• Case-finding should be a continuing process and
not a “once and for all” project
(occurrence of disease is continuous)
135
136. 3. Availability of diagnostic and treatment
• There should be an accepted treatment for patients
with recognized disease
(need of treatment that alters the occurrence of disease)
• Facilities for diagnosis and treatment should be
available
(Continuation of follow up tests and Rx is necessary)
• Follow-up tests and treatments should be readily
available
136
137. 4. Cost consideration
• Cost effectiveness of screening program is
important
(Screening programs are usually expensive)
• The cost should be economically balanced to
possible expenditure on medical care as whole
(though difficult to measure, it is usually cost
effective)
137
138. Issues….
• The more specific the test, the greater the PVP
• PVP can be increased if the prevalence of preclinical
disease in the screened population is high.
• PVP can be maximized by targeting high risk group
• The more sensitive the test the greater the PVN
138
139. Indicators for evaluating screening
• Length of survival in screen detected and
non-screen detected cases (Cohort design)
• Screening history of cases vs. healthy age
matched controls in a case-control study
• Random allocation to screening or control in
a randomized controlled trials
139
140. Different types of screening,
1. Mass screening:
– It involves the screening of the whole population.
2. Multiple or multi-phase screening:
– It involves the use of a variety of screening tests on
the same occasion.
3. Case finding or opportunistic screening;
– It is restricted to patients who consult a health
professional for some other purposes.
140
141. Combination Testing
1. Series Testing
– A test is first applied to a group. All those with
a positive result are retested.
– E.g., Serological testing for syphilis
2. Parallel Testing
– Two tests are applied together. All those with
either or both tests are considered to be
positive.
143. Potential Source of Bias in Screening
There are three types of bias in screening
1. Self-selection (volunteer) bias
2. Lead time bias (early diagnosis)
3. Length Bias (chronicity and progression)
143
144. 1. Volunteer bias
• People who choose to participate in a screening
program are more likely to differ from those
who do not volunteer
1. Volunteers tend to have better health and lower
mortality rates than general population and are
more likely to adhere to medication
2. On the other hand, those who volunteer are the
“worried well”
144
145. 2. Lead time bias
• The interval between the diagnosis of a disease at
screening and when it would have been detected
due to development of symptoms
• It represents the amount of time by which the
diagnosis has been advanced as a result of screening
• Depends on how soon the screening is performed
• If not taken into account, screened groups may
appear to survive longer than unscreened simply
because diagnosis was made earlier in the course of
disease (lead time bias)
146. 2. Lead-Time Bias
146
Detected by
screening
Asymptomatic
Pre-clinical
Symptomatic
Detected due to
symptoms
Lead time
Screen based
Symptom based
Death
148. 3. Length bias
• Refers to the over representation among
screen detected cases of those with a long
preclinical phase of disease
thus a more favorable prognosis
• Those with long preclinical phase are more
readily detectable by screening than cases
with a short preclinical phase.
• Thus length bias could lead to mistaken
conclusion that screening was beneficial
149. X onset of disease process
O time of clinical onset
o
o
o
o
o
o
x
x
x
x
x
x
screening
Rapidly
Progressive
Disease
Slowly
Progressive
Disease
Length bias
150. Exercise on disease causation model prevention
method and screening
1. Think about two or three health problems or diseases that
you observe during your community attachment.
2. Place them on the line of causation. Think through the cause
of disease X using the different model . and reconsider your
chosen health problems using the triangle of
causation(Agent, Host. and Environment)
3. Identify the primary causes and risk factors for the identified
diseases
4. Write the primary, secondary, and tertiary prevention
strategies for the diseases that could be implemented to the
identified disease
5. Is screening possible to the identified disease if yes explain
it ,if no why? Write your reason.
152. Learning Objectives
• When you have completed this session you will be able
to:
1. Describe well all types of epidemiological study designs
2. Explain the uses of the various study designs.
3. Express well the characteristics of descriptive study designs and
how hypothesis is generated.
4. Determine when to proceed with an analytic study for further test
of the hypothesis
5. Describe the characteristics and design of observational and
experimental design
152
153. Why Epidemiological Studies?
• To answer questions like:
– How big is the problem (magnitude)?
• Prevalence, incidence, mortality
– What, who and where of any health problem?
• Person characteristic of affected population
• Place characteristics (locality)
– What factors are associated with certain disease
• Specific factors related to causation
– To evaluate interventions
• Which drug is best for patients with X disease
• To evaluate any program
e t c
153
154. Categories of epidemiological studies
1. Descriptive epidemiological studies
Population as study subject
o Correlational /ecological studies
Individual as study subjects
o Case report / Case series
o Cross-sectional surveys
154
155. Cont…
2. Analytic epidemiological studies
2.1 Observational studies
o Case-control study
o Cohort study
2.2 Experimental / intervention studies
155
157. 1. Descriptive Studies
• Some studies simply describe occurrence of disease or health
related problems
– Prevalence of a disease,
– Rate of certain behaviour
• When describing these factors, it does not link with anything
• However we can identify unusual distributions or correlations
(e.g clusters)
• These insights can be used to generate interesting hypothesis
(Case series, cross-sectional, ecological)
158. Cont….
Describes the general characteristics of the
distribution of a disease in relation to person, place
and time.
Who? Where? When?
It provides valuable information
To allocate resources efficiently and
To plan effective prevention or education
programs.
158
159. Cont…
It provides the first important clues about
possible determinants of a disease
(formulation of hypothesis).
Hypothesis is formulated on an implicit
comparison ie comparison with the
expectation or experience.
159
161. 1. Correlational/ Ecological study
Uses aggregated data from entire population (as a
whole) to compare disease frequencies.
(ie it doesn’t need data from individuals)
Can be done quickly and inexpensively, often using
already available data.
The aggregate data could be
Prevalence of a health event,
Death rate,
Incidence of a health related problem
161
162. Example
Fluoride content of water and dental caries
– Proportion of people with dental caries in villages
Vs
– Fluoride content of water in villages
162
163. Rationale for ecological studies
1. Low cost and convenient
2. Measurement limitation (conditions that are
difficult to measure at individual level)
(eg environmental contact, dietary exposure,
fluoride content)
3. Other designs may be unable to measure
4. Scientists having interest on ecologic effect
163
164. Level of analysis
• Completely ecologic analysis; all variables are
ecologic measures and analysis is in a group.
• Partially ecologic analysis; addition of some
individual variables and ecologic variables
164
166. Limitations
Unable to link an exposure to occurrence of disease
in a single individual.
Lack of the ability to control for effect of
confounders.
Data represent average exposure levels rather than
actual individual values as in ecological “fallacy” or
bias.
166
167. 2. Case reports or case series
Useful for the recognition of new diseases,
Useful for constructing of the natural history of a
disease,
Use to formulate a hypothesis and to detect an
epidemic
167
168. A. Case report:
It is the study of health profile of a single
individual using a careful and detailed report by
one or more clinicians.
It is common form that is published in articles
It is made using
Simple history,
Physical examination and
Lab. / radiologic investigation.
168
169. Cont…
Report is usually documented if there is unusual
medical occurrence, thus it may be first clue for
identification of a new disease.
It is useful in constructing a natural history of
individual disease.
It was a single case report that formulated the
hypothesis of oral contraceptive use increases
venous thrombo-embolism.
169
170. Individual case report can be expanded to a case
series, which describes characteristics of a number
of patients (usually 5-12) with a similar disease.
Similar to case report, it is usually made on cases
having new and/ or unusual disease (giving interest
to clinicians)
It is often used to detect the emergence of new
disease or an epidemics.
Eg. The first five AIDS cases in USA.
B. Case series
170
171. Cont…
Example:
Five young, previously health homosexual men were
diagnosed as having Pneumocystis carinii pneumonia at
Los Angeles hospital during a six month period from
1980 to 1981.
This form of pneumonia had been seen almost exclusively
among older men and women whose immune systems
were suppressed.
This unusual circumstance suggested that these
individuals were actually suffering with a previously
unknown disease, subsequently it was called AIDS.
171
172. Cont…
Both case report and case series are able to formulate
a hypothesis but are not able to test for presence of
valid association.
Fundamental limitation of case report is presence of a
risk factor that is simply coincidental (by chance)
It is difficult to test for association because there is no
relevant comparison group
172
173. 3. Cross-sectional surveys
Is generally called study of prevalence
Survey is conducted in a population, to find
prevalence of a disease and exposure.
Exposure and disease status are assessed
simultaneously among individuals at the same point
in time .
173
174. Cont….
Cross-sectional surveys could provide
information about the frequency of a disease by
furnishing a ‘snapshot’ at a specified time.
May be used first step in longitudinal or case
control studies.
Data are obtained Only once.
Measures of association is made using odds
ratio.
174
175. Cont…
It can be considered as analytic study, if it
assesses presence of an association.
For factors that remain unaltered overtime such
as sex, race, blood group,
it can provide a good evidence.
175
176. Limitations
Since exposure and disease status is assessed at a single
point in time, temporal relationship between exposure
and disease can not be clearly determined.
Egg and hen phenomena
Temporal relationship
176
Exposure Disease
177. Purpose/ Aim
1. To test hypothesis about causal relationship
Proof Vs Sufficient evidence
2. To search for cause and effect.
Why?? How??
3. To compare treatment regimens / prevention programs
4. To assess diagnostic tests
5. To quantify the association between exposure and outcome
Measure of association
2. Analytic epidemiological studies
177
178. Cont…
♦ It focuses on determinants of disease by testing
hypothesis.
– Try to answer questions like “why” and “how” of a disease.
♦ Hypothesis is tested using appropriate comparison
group.
♦ Two study designs,
1. Observational
2. Interventional designs.
178
179. Cont…
♦ Difference lies in the role of the investigator.
– In Observational studies, the investigator simply
observes the natural course of event
– In interventional studies, the investigator assigns
study subjects to exposure and non-exposure then
simply follows to measure for disease occurrence.
179
180. 2.1 Observational studies
Information is obtained by simple observation of the
event.
Two basic types:
a. Case control study b. Cohort study design
Major difference is in the method they start to
select comparison group
Comparison of groups is made either by difference
in disease occurrence (Cohort studies) or difference
in exposure status (Case control studies)
181. a. Case-control study
Cases (subjects having a specific disease) and controls
(subjects not having the disease) are compared for their
exposure status.
Cases are first selected then controls are selected in a similar
way and analysis is made to observe among whom the
exposure status is higher
It assess retrospectively on exposure status
It is relatively cheaper, (Time and Cost)
Measure of association is using Odds ratio
181
183. Application of Case-Control studies
• It is good to do for rare diseases or outcomes
• Better for diseases with long latency between
exposure and outcome
• It may be possible to explore a wide range of
potential exposures for a single outcome
184. Major Steps in case-control study
• Define and select cases
• Select controls
• Ascertain exposures
• Compare exposure in cases and controls
– proportions/odds ratios ....
• Test any differences for statistical significance
185. Cases
♦ It is the outcome of interest
♦ It can be
– A disease
eg. HIV status, Malaria caseness
– A behavior
eg Alcohol drinking habit, Cigarette smoking
– Occurrence of an event
eg migration
185
186. Control
• It is the comparison group
• It should be free of the disease of interest
• It should be similar to the cases in all aspects
except for the disease of interest
186
187. Design of case control
Exposed
Non-exposed
Exposed
Non-exposed
Cases
(People with
disease)
Controls
(People without
disease)
Population
Time
Direction of inquiry
Starting of Observation
187
188. b. Cohort study
Healthy subjects are classified on the basis of their
specific exposure status and are followed up for a
specific time to determine for the development of a
new disease.
Comparison between groups is made on difference in
occurrence of a new disease between the two groups
There is usually a follow up.
Relatively expensive (time, cost).
Measure of association is using Relative risk
188
189. 1. Basic elements
♦ “Disease” free at entry
♦ Selected by exposure status rather than outcome
♦ Followed up is needed to determine the incidence
of the outcome in each exposure group
♦ Compare incidence rates
– For non communicable (chronic) diseases this may take
years
190. Study population
• Study subjects should be disease free
• Define inclusion and exclusion criteria on the
exposure
– Environmental factors: smoking, air pollution,
pesticides
• Criteria can be specified by age, sex, location,
exposure and other factors
193. 2.2 Interventional/ Experimental
o Investigator assigns subjects to exposure and non-
exposure and makes follow up to measure for the
occurrence of a disease.
o It is usually prospective.
o Very expensive,
o Difficult to overcome ethical issue.
o Measure of association is using Relative risk
193
197. Types of trial
Classification
1. Based on population
Clinical Trials – unit of intervention is a patient,
site of intervention is a health care facility
Field Trials – unit of intervention is an individual,
site of intervention is the community E.g. vaccine
trial
Community Interventions – unit of
randomization may be a family or community
(‘cluster’). E.g. fluoridation of water to prevent
dental caries.
198. 2. Based on design
• A. Uncontrolled trial - no control group.
control will be past experience (history).
• B. Non-randomized controlled- there is
control group but allocation into either
group is not randomized
199. Basic Trial Concepts
Allocation of intervention
Baseline measurements Follow-up measurements
Intervention Group
Control Group
202. Data collection techniques and tools
• Data-collection techniques :-allow us to
systematically collect information about our
objects of study (people, objects, phenomena) and
about the settings in which they occur.
• In the collection of data we have to be systematic.
If data are collected haphazardly, it will be
difficult to answer our research questions in a
conclusive way.
203. Methods of data collection
Data collection
is techniques allows us to systematically collect data
about our objectives of the study
is the first and foremost step to be carried out in any
statistical analysis
we have different types of data collection methods
204. Cont’d
o Observation
o Interview
o Using available information
o Focus Group Discussion(FGD)
o In-Depth Interview (IDI)
o Postal, mail or telephone interviews
Face-to- face interview
Self - questionnaire administered
205. 1. Observation
is a technique that involves systematically selecting,
watching and recoding behaviors of people or other
phenomena and aspects of the setting in which they
occur, for the purpose of getting (gaining) specified
information
it includes all methods from simple visual observation to
the use of high level machines and measurements,
sophisticated equipment of facilities such as
radiographic machine, biochemical techniques, clinical
examinations, microbiological examinations…etc
Qualitative method
206. cont,,,
• Observation of human behavior is a much-used data
collection technique. It can be undertaken in different
ways:
• The two ways of observation
– Participant observation:
– Non-participant observation
207. Observation…
• Participant observation: The observer takes part in the
situation he or she observes. (For example, a doctor
hospitalized with a broken hip, who now observes
hospital procedures ‘from within’.)
• Non-participant observation: The observer watches the
situation, openly or concealed, but does not participate
208. Observation…
• Observations can be open (e.g., ‘shadowing’ a health
worker with his/her permission during routine
activities) or concealed (e.g., ‘mystery clients’ trying to
obtain antibiotics without medical prescription).
• Observations can give additional, more accurate
information on behavior of people than interviews or
questionnaires.
• They can also check on the information collected
through interviews especially on sensitive topics such
as alcohol or drug use, or stigmatizing diseases.
209. Observation…
• For example, whether community members share
drinks or food with patients suffering from feared
diseases (leprosy, TB, AIDS) are essential
observations in a study on stigma.
• Observations can also be made on objects. For
example, the presence or absence of a latrine and its
state of cleanliness may be observed.
210. Observation…
• If observations are made using a defined scale they
may be called measurements. Measurements usually
require additional tools.
• For example, in nutritional surveillance we measure
weight and height by using weighing scales and a
measuring board. We use thermometers for measuring
body temperature.
211. Observation…
Advantages
Gives relatively more accurate data
Disadvantages
Investigators or observer’s own biases
Needs more resources and skilled human power
during the use of high level machines
212. 2. Interview
Are the most commonly used data collection techniques
A. Interview (Survey through interview)
a process of asking for the required information through a
prepared questionnaire
Questionnaire is a document with a list of questions to be
answered by respondents
Merit:
Gives more rooms for getting accurate information
Helps to apply skip pattern
High response rate
Demerit:
Liable to biased by the interviewer
Expensive
213. 3. Self- administered questionnaire
Questionnaire is simply forwarded to respondents
It is simple and cheap, since it can be administered to many
persons simultaneously and can be sent by Posta
Merit:
Cheaper than other methods
Demerit:
Non-response rate is high
Limited to educated respondents only
214. A written questionnaire can be administered in
different ways, such as by:
• Sending questionnaires by mail
• Gathering all or part of the respondents in one place
at one time,
• Hand-delivering questionnaires to respondents and
collecting them later.
215. 4. Using documentary sources
Clinical and other personal records, death certificates,
published mortality statistics, census publications….
Common examples of documentary sources
1. Official publications of CSA
2. Publication of MOH and other ministries
3. International publications like WHO, UNICEF…
4. Records of hospitals or any health institutions
Merit:- Easy to get and collect the data
Demerit:- Highly liable for bias
216. 5. Focus Group Discussion (FGD)
A qualitative method to obtain in-depth information on
concepts and perceptions about a certain topic through
spontaneous group discussion of approximately 6–12
persons, guided by a facilitators
Advantage:
– Excellent approach to gather information on in-depth attitudes,
and beliefs of a group
– It facilitates the exploration of collective memories
– Group dynamics might generate more ideas than individual
interviews
– Provides an excellent opportunity to probe & explore
– Participants are not required to read or write
– Unearth sensitive issues which are not commonly raised by
individuals
217. FGD…
Disadvantage:
– Requires strong facilitator to guide discussion and ensure
participation by all members,
– Doesn’t give quantitative information,
– It is difficult to organize the discussion,
– Analysis is relatively difficult.
218. 6. In-depth interview(IDI)
A qualitative method that relies on person to person
discussion
Advantage:
– Good approach to gather in-depth attitudes and beliefs
from individual respondents
– Provides an excellent opportunity to probe and explore
– Participants don’t need to be able to read and write to
respond
– Assures privacy
220. 7. key informants
• The use of key informants is another important
technique to gain access to available information.
• Key informants could be knowledgeable community
leaders or health staff at various levels and one or two
informative members of the target group.
221. 8.Other sources
• Other sources of available data are newspapers and
published case histories, e.g., patients suffering from
serious diseases, or their relatives, telling their
experiences and how they cope.
222. Common problems in data collection
Language barriers
Lack of adequate time
Expense
Inadequately trained and experienced staff
Invasion of privacy
Bias (professional, personal, seasonal…)
Cultural norms(e.g. which precludes men interviewing
women…)
223. Designing a questionnaire
1. Before beginning to design a questionnaire
Identify the major variables to be addressed
2. While developing the draft
The size of the questionnaire is as small as possible
Be clear with why the question is asked and what I will do
with the answer
Avoid time consuming, embracing or personal questions
3. Questions character and appearances..
• Questions should flow from
Simple – to – complex
General –to- specific
Impersonal –to- personal
4. Confidentiality statement should be addressed
224. Designing a questionnaire,,,
Types of questioners
1. Open ended
Offers free response for the respondents to fill with
their own words
No multiple options for the respondents
e.g. what is your marital status?
2. Closed ended
Offers the respondents a list of options
e.g. what is your marital status?
1. Single
2. Married
3. Divorced
4. Widowed
225. Designing a questionnaire…
o A questionnaire can be classified based on different issues:
Structured Vs Non-structured Questionnaire
The structured one is mainly designed for surveys.
– A series of questions are arranged in a logical order and
sequence and divided into subtopics
– Skipped pattern is important for structured questionnaire
– The data collector is expected to smoothly go through the
sequence
The non-structured one is commonly used for qualitative
studies
– It doesn’t have strict sequence of questions
– The data collector may rearrange the questions depending on
the response of the subject
226. Designing a questionnaire…
Standardized Vs Non-standardized Questionnaire
1. Standard questionnaire is developed by a well known body
and considered to be “standard” to assess a given research
question. E.g. WHO questionnaires
2. Non-standard questionnaire one is developed by the
researcher to address the research question
227. Qualitative methods data collection:
Narrative (words, phrases and sentences)
Observing
Interviews
(Focus groups) discussions
Asking open questions on a questionnaire
228. Quantitative Methods
• Data in numbers
• Comparison of categories, proportions, scores,
means, differences using Statistical Analysis
229. Quantitative data collection tools
• Self-administered (postal) questionnaires
• In person or telephone interview
questionnaires
• Accessing records (hospital or health centre)
• Physical examinations or tests
• Biospecimen collection
231. MEASUREMENTS OF MORBIDITY AND MORTALITY
The health status of a community is assessed by the
collection, analysis and interpretation of data on
sickness (morbidity), death (mortality) disability
and data on the utilization of health service.
232. Diseased
Not Diseased
1) How many people have a
disease?
2) What proportion of the
population has disease?
3) What proportion of the
population could still get the
disease?
We often want to know:
233. Cont…
•We use various tools to measure the frequency of
occurrence of disease death and disability in the
population.
•Some of the measure includes rates, ratios, and
proportions.
•Among these the rate is the most important
for measuring disease.
240. Example:
What is the ratio of females to males?
# Females
# Males
= 5 / 2 = 2.5:1 = 2.5
241. Ratio — Related Categories of Same Variable
In Country X, what is the ratio of males to females in
the age group 45-49 ?
= 76,875 males = 1.06 : 1
72,470 females
In the age group 65+?
= 64, 055 males = 0.94 : 1
67,795 females
242. Ratio — Different Variables
•A city of 4 million people has 400 clinics. Calculate
the ratio of clinics per person.
•Ratio = 400 / 4,000,000 = 0.0001 clinics / person
Multiply by 104
•Ratio = 0.0001 x 104 = 1 clinic / 10,000 persons
243. Examples: The number of male and females in 1988 in
Ethiopia were projected on the basis of the 1984 population
and housing census of Ethiopia.
Male = 23,630,753
Female = 23,674,551
Total = 47,305,304
The ratio of male to female in Ethiopia in 1988 was 0.99 / 01
I.e. M/F = Male
Female =
23,630,753 = 0.99/1 = 0.99
23,674,551
244. Proportion:
A proportion is a specific type of ratio in which
the numerator is included in the denominator
and the result value is expressed as percentage.
245. Proportion
Definition: comparison of a part
(occurrences) to a whole population in
which these occurrences take place
Numerator MUST BE INCLUDED in the
denominator
Ranges between 0 and 1 (0–100%)
Percentage = proportion x 100
248. Example: The proportion of male in the total
population in 1988 is
Male X 100
Male + Female
=
23,630,753 X 100 = 49.95 % 47,305,304
249. Proportion — Summary
• Common descriptive measure
• Numerator must be included in the
denominator
• Can be expressed as a fraction,
decimal, or percentage
250. Rate:
-Rate is a special form of proportion that
includes the dimension of time.
- It may be defined as the number of persons
with a disease per unit of population per unit
time.
-It is considered to be a basic measure of
disease occurrence.
251. To calculate a rate one requires the number of disease
(X) and the number of people who don't have the
disease (Y)
The formula of the rate is
Rate = No of events in specified period X K
Popn at risk of these events in a specified period
In the above formula for rate - K (constant)
The most often used constant are 100, 1000, 10,000,
100,000.
252. Example
The number of newly diagnosed breast cancer
cases per 100,000 women
Example: Measles cases in under five in 1995
Under five children in 1995.
253. Types of Rates
There are three types of rates
Crude rate
Specific rate
Adjusted rate
254. Crude Rates:
Are summary rates based on the
actual number of events
(birth, death, disease) in the total
population over a given period of time
255. Cont…
The widely used cruds rates are CBR,
CDR
Since the rates refers the total
population the possible different in risk
group or subgroups may be obscured.
256. Specific Rates: Specific rate apply
the specific sub groups in the
population such as a specific age
group, sex, Martial status etc.
257. Cont…
In calculating specific rate, the
denominator should be the
population in that specific group, not
the total population
Examples: IMR, NMR, MMR
258. Adjusted rates:
These are rates which have been
adjusted to correct for the age and
sex structure or other peculiarities
of the population.
259. Cont…
The adjusted rate equalizes the
difference in the population at risk
so that the rates are comparable.
260. Cont…
If you want a measurement of mortality
that can be used either to compare
different populations (states, counties,
cities, etc.)
261. Cont…
or to compare the mortality experience
over time for one area with a changing
population, it is advisable to adjust or
standardize the effects of such factors
as age and/or sex in these groups
262. - Death or incidence rates can be adjusted
for any demographic factor such as race
or any combination of factors, such as
age, sex and race.
The most commonly used adjustment - is
for age.
263. Age-adjusted rates are commonly used in
comparative mortality analyses since age
is such a prime factor in mortality,
especially with chronic diseases such as
heart disease and diabetes.
264. Cont…
Age-adjusted death rates eliminate the
bias of age in the makeup of the
populations being compared, thereby
providing a much more reliable rate for
comparison purposes.
265. There are three major components
that are needed to perform adjusted
mortality rate calculations:
the number of deaths
the population
a "standard" population
266. Measurement of Morbidity
•Measurement of sickness (morbidity) is
more difficult than death because of the
following reasons.
Sickness may not be recognizable
• Sickness may occur repeatedly on person or
•a person may be suffered with several
•diseases, at one and the same time.
267. Measurement of Morbidity cont…
•There are two basic measures of
morbidity
Incidence rate
Prevalence rate
268. Incidence Rate
•Is the number of new cases of disease or
spells of illness over a period of time
•. The critical element in the definition of
incidence is new cases of disease
•The appropriate denominator for
incidence rate is population at risk.
269. Incidence
• The number of new events, e.g., new
cases of a disease in a defined population
within a specified period of time.
270. Cont…
Example: If we calculate the incidence for
prostate cancer the denominator must
include only men because women are not
at risk.
• Another important issue in regard to the
denominator is the issue of time we can
calculate incidence in one week, in one
month, in one year, incidence in five years.
etc.
271. Cont…
•The determination of population at risk
is a major problem in the study of
disease incidence.
• It may require a detailed study based
on interview and medical records.
•Population fluctuation is due to births,
deaths and migration this is another
problem in the calculation denominator.
272. Incidence rate
Incidence rate (Person) = # of new case of
a disease over a period of time X K
Population at risk
Incidence rate (Spells) = # of spells of
illness over period of time X K
Population at risk
273. Incidence rate cont…
For Example
A person may have been more than one cold in
a year the following two formulas may be
constructed
# of people who develop a cold in one year
Population at risk
-# of colds in one year period
People at risk
274. Incidence rate cont…
The implication of these two rates is
different.
•The first give the probability any person
will develop a cold in one year.
•But the second indicates the number of
colds to be expected among the group of
people in that year.
275. Special incidence rates
I. Attack rate
Rate used in an epidemic investigation to
find out how many of those exposed
develop the disease.
II. Attack rate=No of persons ill from the
same disease X100during specific period
No of person at risk
276. Attack Rate – Example
x = 30 people got sick, out of
y = 100 people who attended banquet
10n = 100%
Attack Rate = 30/100 = 0.30 = 30%
x = 28 people ate chicken and got sick
y = 56 people ate chicken
10n = 100%
Food-specific Attack Rate = 28/56 = 0.50 = 50%
Attack Rate (no chicken) = 2 / 44 = ____
277. Secondary attack rate=No of cases of a
disease developing during a stated time
period among those member of a closed
group who are at risk
Secondary attack rate= No of new cases
developing in a closed group after contact
with the initial (index)case or cases X100
No of susceptible persons minus the initial
case
278. Incidence: Example
• Suppose one wished to know how many
people in a given population newly develop
diabetes in a certain period of time.
• Les us say all people were screened at the
start of the study and 10% of 1000 are found
to be diabetic.
• After one year, 9 of 900 were found to be
positive. This figure (10% = 9/900) is the one
year incidence.
279. Incidence rate cont…
• Incidence rate is important as:
– A fundamental tool for etiologic
studies of acute and chronic
disease
–A direct measure of risk
280. Types of Incidence
• There are two ways of calculating
incidence: Incidence rate and incidence
risk
• Incidence rate = Incidence density
• Incidence risk = Cumulative incidence
281. Incidence Rate or Incidence Density
• The numerator is the number of new
events that occur over a defined
period of time and the denominator
is the population at risk of
experiencing the event during this
period.
282. Incidence Risk or Cumulative Incidence
• Simpler measure compared to incidence
rate
• The denominator is only those people
who are there and free of the disease in
the population at the beginning of the
study
• Less useful than incidence rate that tells
us something about the speed at which
events are occurring.
283. Incidence Rate
Synonyms:
- Incidence
- Incidence density
- Person-time rate
Units: per time period
Definition: frequency with which an event
(such as a new case of illness) occurs in a
population over a period of time
284. Incidence Rate (General Population)
2
—— = 0.002 / year
1000
Observed in 2005
• Numerator
– number of NEW EVENTS observed during specified time
• Denominator
– size of population in which events occur
– average or mid-period (e.g., mid-year) population estimate
•10n = usually per 1,000 or 10,000 or 100,000
285. 0
5
10
15
20
25
30
35
40
45
52 56 60 64 68 72 76 80 84 88 92 96 2002
Year
Rate
per
100,000
Reported Incidence of Hepatitis A, United States, 1952–2002,
by Year
Incidence Rate (General Population) – Example
286. Person-Time Rate (Cohort Study)
Form: (x / y) x 10n, where
x = number of new cases during follow-up period
y = sum of the lengths of time each study
participant was observed and at risk of
disease
10n = 1,000 or 10,000 or 100,000
287. Denominator of Person-Time Rate
Cohort (Follow-Up) Study
• Follow each person until
– Onset of disease
– Death
– Loss to follow-up
– End of study
• Add up the time each person was followed
289. Person-Time Rate – Example
1567 HIV-negative workers in Tanzania enrolled in cohort
study, and followed for 2 years. Seventeen
seroconverted. If no one were lost to follow-up or died
or seroconverted, how many person-years would you
expect?
1,567 × 2 years of observation = 3,234 PY f/u
But some were enrolled a little later, some had died, 471
were LTFU. So, only 1365.7 actual PY f/u.
Incidence Rate = 17 / 1365.7 PY
= 1.2 HIV cases / 100 PY
= 1.2 HIV cases / 100 pop / year
290. Incidence Rate – Summary
• Rate = how quickly disease occurs in a population
• Used commonly in surveillance, vital statistics
• Only new cases in numerator
• Expressed per person-years, or per person per year
• Not everything called a rate is a rate (attack rate,
case-fatality rate)
291. Definitions
Prevalence
• The number of persons with a disease or
an attribute at a specified point in time.
• When used without qualification, it
usually refers to point prevalence.
292. Prevalence: Example
• Suppose one was interested in finding out
how many people living in a given area had
HIV?
• If 100 out of 1000 people tested were positive
for HIV, will this proportion (10%) be called
incidence or prevalence?
293. Prevalence Rate
The prevalence rate measures the
number of people in a population who
have a disease at a given time. It includes
both new and old cases.
There are two types of prevalence rate.
•Period prevalence rate
•Point prevalence rate
294. Period Prevalence Rate
Period Prevalence Rate: Measures the
proportion of a population that is affected
with a certain condition during a specified
period of time.
Period prevalence rate =
# of people with condition during a Specific period of
Total Population
295. Point Prevalence Rate
• Point Prevalence Rate: Measures the
proportion of a population with a certain
condition at a given point in time.
Point Prevalence rate =
All persons with a specific condition at one point in time X100
Total Population
296. Cont…
• Prevalence (P) is related to Incidence (I) and
duration (D) by the expression of P ~ ID
• Which means prevalence varies directly with
both incidence and duration? If the incidence
and duration have been both stable over a
long period of time, then this formula
become
P = ID
297. Prevalence Rate
Number of existing (prevalent) cases of disease
present in a defined population:
New and old cases
Doesn’t directly measure risk
Numerator reflects the number of existing
(prevalent) cases of a disease:
identified at a “point” in time or
during a given period
298. Prevalence (of Disease)
Form: (x / y) x 10n, where
x = # new and pre-existing cases at point
or period of time
y = average or midpoint population
10n = depends on how common
Range: 0 – 1 (0 – 100%)
Definition: proportion of persons with a particular
disease at a specified point or period of time
299. Prevalence – Examples
# persons living with HIV infection in KZ in 2005
estimated KZ population on July 1, 2005
# persons who smoke cigarettes in KZ in 2005
estimated KZ population on July 1, 2005
300. Point vs. Period Prevalence
Point prevalence: at a point in time (snapshot)
= # existing cases of disease at to
total population at to
Period prevalence: over a specified period
= # existing cases during a period
total population during period
302. Prevalence – Summary
Prevalence provides snapshot of disease
burden or attribute in population
Numerator includes both new and pre-
existing cases
More practical than incidence for many
chronic diseases
303. Uses of Prevalence Rate
• Prevalence rates are important particularly
for
–Chronic disease studies
–Planning health facilities & manpower
–Monitoring disease control program
–Tracing chargers in disease pattern over
time.
304. Cont…
• High prevalence may reflect an increase in
survival due to:
–Change in virulence
–Change in host factor
–Improve in medical care
305. Cont…
• Low prevalence may reflect
–A rapidly fatal process
–Rapid cure of disease
– Low incidence
306. Limitation of Prevalence Studies
–Prevalence studies favor inclusion of
chronic over acute cases
–Diseases status and attribute are
measured at the same hence; temporal
relations can not be established.
307. Factors influencing prevalence
Increased by Decreased by
• By longer duration - Shorter duration of the disease
of the disease - High case fatality
• Prolongation of life - Decrease in new case
of patients with out cure (decrease in incidence)
• Increase in new cases - in migration of health people
(increase in incidence) - out migration of cases
• In-migration of cases - out migration of susceptible people
• Out migration of healthy people
• In migration of susceptible - Improved cure rate of cases
• people improved diagnostic
• facilities (better reporting
308. Comparing Incidence and Prevalence
Incidence
• NEW cases or events
over period of time
• Useful for studying
factors that cause
disease (“risk factors”)
Prevalence
• ALL cases at
point/period of time
• Useful for measuring
size of problem and
planning
310. The measures of disease frequency used for
quantifying disease depends on what question is
being asked.
Question
1. How many people in a given
population have the disease at this point
in time?
Point
prevalence
2. How many people in a given
population ever had the disease during a
given period of time?
Period
prevalence
3. How many people in a given
population newly developed the disease
during a given period of time?
Incidence
311. Measurements of Mortality
Mortality rates and ratios measure the
occurrence of death in a population
using different ways.
Rates whose denominators are the
total population are commonly
calculated using either the mid
interval population or the average
population
312. Mortality (Death) Rate
Many types, including:
• Crude mortality rate
• Cause-specific mortality rate
• Age-specific mortality rate
• Infant mortality rate
Definition: frequency of death in a defined population
during a specified period of time
1 2 3 4
5 6 7
8 9 10
313. Measurements of Mortality
–Mortality rates and ratios measure the
occurrence of death in a population using
different ways.
–Rates whose denominators are the total
population are commonly calculated using
either the mid interval population or the
average population. This is because
population size fluctuates over time due to
births, deaths and migration.
• Some common used mortality rates are
314. Crude death rate
• Crude death rate =
Total # of death reported during a given time interval X 1000
Estimated mid interval population
315. Crude Mortality (Death) Rate
Form: (x / y) x 10n, where
x = number of deaths during specified period
y = midpoint population
10n = 1,000 or 100,000
Example:
2,448,228 deaths from all causes, US, 2003
290,810,789 estimated population, US, 1 July 2003
841.9 deaths per 100,000 population
316. Age specific mortality rate
• Age specific mortality rate =
# of deaths in a specific age group during a given time X 1000
Average (or midyear) popn in a specific age group
317. Age-Specific Mortality Rate
Form: (x / y) x 10n, where
x = # deaths in specified age group during specified
period
y = midpoint population of that age group
10n = 100,000
Example:
130,761 deaths in 25-44 year olds, US, 2003
84,243,594 estimated 25-44 y.o., US, 1 July 2003
155.2 deaths per 100,000 25-44 year olds
318.
319. Sex specific Mortality rate =
# of deaths in a specific sex in a given time X 1000
Sex specific Mortality rate
Average population in specific sex
320. Cause specific Mortality rate
Cause specific Mortality rate =
# of deaths from a specific cause During a given time X 100,000
Estimated mid internal population
•The cause specific death rate asks: "Out of the
total population, what proportions are died from a
certain disease with in a specific period of time.
Example: Proportion of deaths from malaria
out of the total population
321. Cause-Specific Mortality Rate
Form: (x / y) x 10n, where
x = number of deaths from specified cause during
specified period
y = midpoint population
10n = 100,000
Example:
685,089 deaths from heart disease, US, 2003
290,810,789 estimated population, US, 1 July 2003
235.6 deaths per 100,000 population
322. Proportional Mortality ratio
Proportional Mortality ratio =
# of deaths from specific cause during A given time X 100 Total # of
deaths from all causes during the same time
• The proportional mortality ratio asks: "Out of all
the deaths occurring in that area, what proportions
are died due to the cause under study.
• Example: Out of all the deaths occurred in a given
hospital with in specific period of time, how many of
the deaths are from HIV/AIDS related causes
323. Proportionate Mortality
Form: (x / y) x 10n, where
x = # deaths from specified cause during
specified period
y = # deaths from all causes
10n = 100
Example:
685,089 deaths from heart disease, US, 2003
2,448,288 deaths from all causes, US, 2003
Heart disease proportionate mortality = 28.0%
324. Case fatality rate (CFR)
Case fatality rate (CFR) =
# of deaths from a specific disease during a given time X 100
# of case of that disease in the same period
• The case fatality rate asks: "What proportion of
the people with the disease die of that disease.
• Example: How many TB patients are died from all
the TB patients in the specific period of time?
325. Case-Fatality Rate
Number of deaths due to disease A
Number of diagnosed cases of disease A
10n = 100 if common event, otherwise 1,000 or
100,000 or whatever
Range: 0 – 1
Definition: proportion of ill persons who die
Form:
x 10n
326. The mid interval population
• The mid interval population in the population
count at a point mid way through the specified
time period.
• Example: July 1, 1990 to the year 1990 GC
Megabit 1, 2002 for the year 2002 EC
• The average population is obtained by the
population count at the beginning and at the
end of the specified time period divided by 2
327. • Figure below shows Hierarchy of four levels
representing the population, case of disease 'X'
• cases in the population, death from disease 'X'
and death from all other causes
A)
B)
C)
D)
Population
Cases of disease ‘x’
`Deaths from disease `X
Deaths from all other cause
328. Exercise
• Following data in extracted from the record of the
pediatric ward of a hospital with in one year
duration
• Total admission (Popn) = 1,000
• Admission for diarrhea = 100
• Deaths from diarrhea = 25
• Death from all other cause = 75
• Calculate the following measures from the above
given data
• Cause - specific mortality rate from diarrhea in
children admitted to ward
• Case fatality rate
• Proportional mortality ration for diarrhea
329. In a Central Asian country with a population of six
million people, there were 60,000 deaths during the
year ending December 31, 2005. These included
3,000 deaths occurring in 9,000 people who were
sick with cholera.
Calculate:
• Crude mortality rate in 2005
• Cholera incidence rate in 2005
• Cause-specific mortality rate from cholera in 2005
• Case-fatality rate from cholera in 2005
Practice
330. Infant Mortality Rate
Form: (x / y) x 10n, where
x = number of deaths in children < 1 year,
during specified period
y = number of live births during same period
10n = 1,000
Example:
28,025 deaths in children < 1 year, US, 2003
4,089,950 live births, US, 2003
6.85 deaths per 1,000 live births
331. Infant Mortality rate (IMR)
Infant Mortality rate (IMR) =
# of deaths < 1 yr of age during a given time X 1000
# of live births reported during the same time interval
332. Infant Mortality Rate
Form: (x / y) x 10n, where
x = number of deaths in children < 1 year,
during specified period
y = number of live births during same period
10n = 1,000
Example:
28,025 deaths in children < 1 year, US, 2003
4,089,950 live births, US, 2003
6.85 deaths per 1,000 live births
333. Child Mortality rate
Child Mortality rate =
No of deaths of 1 - 4 yrs of age during a given time X 1000
Average (mid-interval) Popn of the same age at same time
334. Maternal Mortality ratio
Maternal Mortality ratio =
# of pregnancy associated deaths of a mother X 100,000
No of live births in the same time
335. Health indicators
• Health indicators: health indicators are measure
that reflects or indicates the status of health of a
person in a given population.
• Mortality rates vary in their usefulness as indicators
of health conditions.
• The crude death rate, for instance is not a reliable
indicators of the health status of population b/c it
is affected by the age composition of the popn
336. Health indicators cont…
• In the contrary the infant mortality rate is a very
sensitive indicator of the health status of a
population. Because it reflects to the first year of
life which is a very vulnerable age group
• The survival of infants very much depends on
*socioeconomic conditions and
* the quality of health service.
• Both of which are determinants of health status in
general
337. Some of the mortality rates of health
indicators are
• - Infant mortality rate
• - Maternal mortality rate
• -neonatal mortality rate
• -Post neonatal mortality rate.
338. UNIT _ FIVE
SOURCE OF DATA ON COMMUNITY
HEALTH
• There are numerous of data on morbidity
and mortality in community.
• Each has its own advantages and
disadvantages.
339. 1. Census
• It is a total count of the population at
one point in time. In census, the
population count can be two types.
De,jure and De facto
340. Census cont…
De jure:
• In these types of census populations are
counted according to their usual place of
residence.
• The count excludes, temporary residents
and visitors, but includes the Permanente
resident who is temporarily away
341. Census cont…
De facto:
• This count includes temporary residences
and visitors,
• Excludes permanent residences that are
a way on the day of the census
342. Use of census
• Census data provides information:
• size and composition of population
• the factors that determines these
variability
• the trends anticipated in the future
343. Limitations of census
• The main limitation is its cost.
• takes a very long time to compile the
large amount of data
• Can not assess early changes since it is
carried out every 10 year in most of the
countries.
344. Vital statistics
• This is a system, by which all births and
deaths occurring nationwide are
registered, reported and compiled
centrally.
• A certificate is issued for each birth and
deaths. It is source of information for the
calculation of birth and death rates.
345. The main characteristics of vital
statistics are:
• Comprehensive- all births and deaths should
be registered.
• Compulsory by law-should be enforced by law
• Compiled centrally- so that it can serve as
source of information
• Continuous- it should be an ongoing process.
There is no nation wide birth and death
registration system in Ethiopia.
346. Health service records
• All health institution reports their
activities to the ministry of health.
• The minister compiles and analyzes the
data to publish it in the health service
directory.
• So it is the major source of health
information in Ethiopia.
347. Health service records cont…
Advantages:
• Can be easily obtained.
• Available at low cost
• Continues system of reporting
• Causes of illness and death available.
