Epidemiology ppt

Gollis University
Department of Clinical
Laboratory
Course outline
Course Title: Epidemiology
Instructor: Sa’ad Ahmed Abdiwali
(BSc, MPH)
Dean of Public Health, Nutrition and
Laboratory
Credit Hours: 4 / 64 contact hours/

A. Course Overview
• This course provides knowledge in epidemiology
for medical students as an introductory course in
community medicine or Public Health.
Epidemiology is a basic discipline essential to
both clinical and community medicines. It also
helps to develop the way of thinking about health
and disease.

Course overview…
• The course deals especially with basic concepts in
Public Health, epidemiology, infectious disease
process, sources of data for community health,
measures of morbidity and mortality, epidemic
investigation, epidemiological surveillance, and
screening and program evaluation.

B.Course Objectives
At the end of the course, the student will be able to know:
1.The definition, scope, use ,strength and limitation of
Epidemiology
2. The basic concepts of epidemiology and infectious diseases
3.The differences between descriptive and analytic epidemiology
4. common sources of community health data
5. Measurements of morbidity and mortality
6. How to investigate and manage epidemics

7. The nature and use of surveillance in the
prevention and control of major infectious
diseases
8. The significance of screening and diagnostic
tests ,and concepts of validity and reliability
9.The levels of prevention regarding the
avoidance and control of diseases at different
levels.

C. Course Contents:
1. Basic Concepts in Public Health
Definitions
– Differences between Community medicine or Public
health and Clinical medicine
– Methods of Community Diagnosis
Natural History of diseases and Levels of Prevention
• Definition
• Stages in the Natural History of Diseases
• Levels of Prevention

2. The Subject Matter of Epidemiology
• Definition
• History
• Scope of Epidemiology
• Purpose of Epidemiology
• Basic Assumptions in Epidemiology
• Types of Epidemiology

3. Principles of Disease Causation and Models
Definition
• Principles of disease causation
– Germ Theory
– Ecological Approach
• Models of disease causation
– Epidemiological Triangle Model
– Web of Causation Model
– The Wheel Model

4. Infectious disease Process
• Components of the Infectious Disease Process

5. Sources of Data for Community Health
• Census
• Vital Statistics
• Health Service Records
• Morbidity and Mortality Surveys

6. Measurements of Morbidity and Mortality
– Ratios, Proportions and Rates
– Measures of Morbidity
– Measures of Mortality
– Errors in Measurement and their Sources

7. Descriptive Epidemiology
• Definition
• The major characteristics in descriptive
epidemiology
• Epidemiologic study designs
• Descriptive study designs

8. Analytic Epidemiology
– Definition
– Observational analytic studies
– Experimental/Intervention studies
– Measures of Association
– Exercise
9. Evaluation of Evidence
 Analysis of cause-effect relationships

10. Epidemic Investigation and Management
• Levels of Disease occurrence
• Definition of Epidemic
• Types of Epidemic
• Investigation of Epidemic
• Management of Epidemic

11. Epidemiological Surveillance
Definition of Surveillance
• Purpose of Surveillance
• Types of Surveillance
• Steps in Surveillance
• Sources of Data

12. Screening: Program and Evaluation
• Definition
• Diseases appropriate for screening
• Criteria for establishing screening programs
• Screening tests
– Concepts of validity and reliability
– Sensitivity and Specificity
• Evaluation of screening

13. Epidemiology of selected diseases based on their public health
importance
• Epidemiology of :
» EPI targeted diseases/ Poliomyelitis, Tuberculosis,
Measles, etc..,
» ARI
» Diarrheal Diseases
» HIV/ AIDS/STI
» Malaria
» Schistosomiasis
» Leishmaniasis
» Onchocerciasis
» Human trypanosomiasis
» Yellow fever
» Relapsing fever
» Typhus
» Typhoid/enteric fever

Methods of Instruction
–Lectures
–Assignments
–Questions and Discussions
Evaluation
 Evaluation methods and percentages of Total Marks
– class participation and attendance: 10%
– Assignments 10%
– Tests/Quiz:40%
– Final examination 40%
.

Major References/ Text books/
1. Kifle Wolde Michael, Yigzaw Kebede and
Kidist Lulu. Epidemiology for Health Science
Students, Lecture Note Series, 2003
2. Mausner and Bahm. Epidemiology; An
Introductory Text W.B.Saunders Company,
1985.
3. Madeline Fletcher. Principles and practice
of Epidemiology, Addis Ababa, Ethiopia, 1992

Chapter One :
Introduction to Epidemiology
• Epidemiology is considered as the basic science of public
health.
• It provides useful tools and methods to describe variations in
disease occurrence and identify factors that influence the
occurrence of disease among population.
• The occurrence of disease is dependent on variations in
exposure of individuals in the population to the causes of the
disease that are commonly behavioral and environmental.

Introduction …
• A less entertaining, but more conventional, definition of
epidemiology is "the study of the distribution and
determinants of health-related states in specified populations,
and the application of this study to control health problems."
A look at the key words will help to illuminate the meaning:
• Study—Epidemiology is the basic science of public health. It's
a highly quantitative discipline based on principles of statistics
and research methodologies.

Introduction…
• Distribution—Epidemiologists study the distribution of
frequencies and patterns of health events within groups in a
population. To do this, they use descriptive epidemiology,
which characterizes health events in terms of time, place, and
person.
• Determinants—Epidemiologists also attempt to search for
causes or factors that are associated with increased risk or
probability of disease. This type of epidemiology, where we
move from questions of "who," "what," "where," and "when"
and start trying to answer "how" and "why," is referred to as
analytical epidemiology.

Introduction…
• Health-related states—Although infectious diseases were
clearly the focus of much of the early epidemiological work,
this is no longer true. Epidemiology as it is practiced today is
applied to the whole spectrum of health-related events,
which includes chronic disease, environmental problems,
behavioral problems, and injuries in addition to infectious
disease.
• Populations—One of the most important distinguishing
characteristics of epidemiology is that it deals with groups of
people rather than with individual patients.

Introduction…
• Control— although epidemiology can be used simply as an
analytical tool for studying diseases and their determinants, it
serves a more active role.
• Epidemiological data steers public health decision making
and aids in developing and evaluating interventions to control
and prevent health problems.
• This is the primary function of applied, or field, epidemiology.

Introduction…
• A comparison between the practice of public health and the
more familiar practice of health care helps in describing
epidemiology.
• First, where health care practitioners collect data on an
individual patient by taking a medical history and conducting
a physical exam, epidemiologists collect data about an entire
population through surveillance systems or descriptive
epidemiological studies.
• The health care practitioner uses his or her data to make a
differential diagnosis.

Introduction…
• The epidemiologist's data is used to generate hypotheses
about the relationships between exposure and disease.
• Both disciplines then test the hypotheses, the health care
practitioner by conducting additional diagnostic studies or
tests, the epidemiologist by conducting analytical studies such
as cohort or case-control studies. The final step is to take
action.
• The health care practitioner prescribes medical treatment,
and the epidemiologist, some form of community
intervention to end the health problem and prevent its
recurrence.

Introduction…
• These facts have been known and some important
environmental exposures that influence disease occurrence
identified since the time of Hippocrates.
• The importance of epidemiology has increased in modern
public health practice,
• The data collection and analytical techniques are being
constantly revised to meet the challenges of obtaining the
necessary information for proper planning of health
interventions.

Basic Concepts...
Definition
• Health is a difficult concept to define. Traditionally,
health was equated with survival, or absence of
death.
• In fact, mortality is still used as a measure of
health. The next stage was to see health as the
absence of disease. This definition is still the most
widely used in practice.

Basic concepts cont..
• Nearly everyone agrees that health is more than the absence
of disease, and many attempts have been made to come up
with a broader definition.
• The World Health Organization (WHO) in 1947 defined health
as “a state of complete physical, mental, and social well-
being and not merely the absence of disease or infirmity”.
• This definition emphasizes the multidimensionality of health
and the existence of positive health, and it serves as an ideal.

• The Ottawa Charter for Health Promotion (World
Health Organization, 1986), as described in
Epidemiologic Methods for Health Policy by Spasoff
R, states that “to reach a state of complete physical,
mental and social well-being, an individual or group
must be able to identify and to realize aspirations, to
satisfy needs, and to change or cope with the
environment.

• Health is seen as a resource for everyday life.
• Health is a positive concept emphasizing social and
personal resources, as well as physical capacities”.
• This is consistent with the call in the WHO’s Health
for All declaration for all people to attain a level of
health “that will permit them to lead a socially and
economically productive life”.

Health is a multifaceted concept. It consists of:
• Physical health
• Mental health
• Social health
• Emotional health
• Spiritual health and
• Occupational health
These concepts have a continuous interaction with
each other.

• Physical health: Efficient bodily functioning,
resistance to disease and the physical capacity to
respond to varied events.
• Mental health: Capacity to cope with life situations,
grow in awareness and consciousness.
• Social health: Good relations with others, a
supportive culture and successful adaptation to the
environment.

• Emotional health: The ability to control emotions
and express them comfortably and appropriately.
• Spiritual health: The ability to discover and articulate
a personal purpose in life, learn how to experience
love, joy, peace and fulfillment.
• Occupational health: Feelings of comfort and
accomplishment related to one's daily tasks.

Basic Concepts …
Clinical medicine versus community medicine:
• Knowledge about human health and disease arises
from basic sciences (e.g., biochemistry, physiology,
pathology), clinical sciences (e.g., medicine, surgery,
obstetrics and gynecology, pediatrics) and population
medicine (e.g., epidemiology, biostatistics, health
service management and planning).

Basic Concepts …
• In different settings, population medicine is also
referred to as community medicine, preventive
medicine, or social medicine, or, more traditionally,
as public health.
• Clinical medicine is concerned with diagnosing and
treating diseases in individual patients, while
community medicine is concerned with diagnosing
the health problems of a community, and with
planning and managing community health services.

Basic Concepts …
• In 1920, Winslow defined Public health as a science
and an art of preventing disease, prolonging life, and
promoting health and efficiency through organized
community effort for sanitation, control of
communicable disease, health education, etc.
• It necessitates a systematic way of studying both the
patterns of occurrence of disease in a community
and the patterns of delivery of medical care.

Basic Concepts …
• Information about the illnesses prevalent in the community
also contributes to diagnosis.
• Assessment of the level of occurrence of disease in a
population is dependent on the accuracy of the diagnosis
made on individual patients and on the completeness with
which reportable diseases are made known to public health
authorities.
• This indicates that the two approaches (clinical and
community medicine) are complementary to each other.

Basic Concepts …
• Information on the health and disease of a defined
community is gathered through Community Diagnosis.
• Community Diagnosis is defined as the process of
identification and detailed description of the most important
health problems of a given community.
• As patient’s history, physical findings and laboratory data are
the basis for making a clinical diagnosis there are some
methods that allow the making of community diagnosis.

Basic Concepts …
Methods of Community Diagnosis:
1. Discussion with community leaders and health workers
2. Survey of available health records
3. Field survey, Conducting study on a sampled population or total
population
4. Compilation and analysis of the data.
• It is impossible to address all the identified problems at the same time
because of resource scarcity. Therefore the problems should be put in the
order of priority using a set criterion.

Basic Concepts …
Criteria for priority setting:
• Magnitude (amount or frequency) of the problem
• Severity (to what extent is the problem disabling, fatal)
•
• Feasibility (availability of financial and material resource,
effective control method)
• Community concern (whether it is a felt problem of the
community)
• Government concern (policy support, political commitment)

Basic Concepts …
Summary:
• in clinical medicine, the procedure consists of history taking,
physical examination and laboratory investigation on
individual patient to make diagnosis that is followed by
treatment and follow up.
• In community medicine the community diagnosis is first
made through field survey, record review and discussion with
the community members.
• This is followed by intervention on selected priority problems.
The intervention programs are monitored continuously and
evaluated periodically.

Basic Concepts …
Disease, Illness and Sickness
• Disease, illness and sickness are loosely interchangeable
terms but are better regarded as wholly synonymous.
• Disease is literally the opposite of ease. It is physiological or
psychological dysfunction.
• Illness is the subjective state of a person who feels aware of
not being well and Sickness is a state of social dysfunction; i.e.
a role that an individual assumes when ill.

Basic Concepts …
• Many different diseases occur in the community.
Some diseases usually last a short time: days or
weeks. Examples are most diarrhoeal diseases,
measles, and pneumonia. These are called acute
diseases.
• Others last much longer, often for many months or
years. These are called chronic diseases. Examples
are tuberculosis, leprosy, diabetes, heart disease and
cancer.

Basic Concepts …
Risk Factors
• Health workers need to know how healthy people can stay healthy.
Many diseases have known causes. For example Schistosomiasis is
caused by schistosome organism and measles by measles virus.
• These diseases cannot occur without these specific causes. But the agent
alone may not be responsible for the onset of the disease. For example
in the case of schistosomiasis if somebody is not working or playing in a
cercariae infected water the infection cannot occur.
• These factors (the availability of infected water and the behaviour of the
individual) are called risk factors.

Basic Concepts …
• Risk factor is any factor associated with an increased or decreased
occurrence of disease.
• 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.
• Risk factors could be:
1. Factors related to the agent:
Strain difference
2. Factors related to the human host
Lack of specific immunity.
3. Factors related to the environment
Overcrowding, Lack of ventilation

Basic Concepts …
Risk factors may further be classified as:
• Factors susceptible to change
e.g. smoking habit, alcohol drinking habit
• Factors not amenable to change
e.g. age, sex, family history
• In order to be able to prevent disease, it is vital to identify factors that can
be changed. For some diseases, the specific causes are not known. In such
cases it is very important to identify risk factors, especially those that can
be changed and act on them.
•

• Epidemiology is mainly interested in those risk
factors that are amenable to change as its ultimate
purpose is to prevent and control disease and
promote the health of the population.
• In summary, population medicine necessitates a
systematic way of studying both the patterns of
occurrence of disease in a community and the
patterns of delivery of medical care.

Natural History of Disease and Levels of Prevention
The “natural history of disease” refers to the progression of
disease process in an individual over time, in the absence of
intervention.
• Each disease has its own life history, and thus, any general
formulation of this process is arbitrary.
• However, it is useful to develop a schematic picture of the
natural history of diseases as a frame work within which to
understand and plan intervention measures including
prevention and control of diseases.

Natural History of Disease Continues…
There are four stages in the natural history of a
disease. These are:
• Stage of susceptibility
• Stage of pre-symptomatic (sub-clinical)
disease
• Stage of clinical disease and
• Stage of disability or death

1. Stage of susceptibility
• In this stage, disease has not yet developed, but the
groundwork has been laid by the presence of factors that
favor its occurrence.
Examples:
• A person practicing casual and unprotected sex has a high
risk of getting HIV infection.
• An unvaccinated child is susceptible to measles.
• High cholesterol level increases the risk of coronary heart
disease.

2. Stage of Pre-symptomatic (sub-clinical) disease
• In this stage there is no manifest of disease but pathogenic changes
have started to occur. There are no detectable signs or symptoms. The
disease can only be detected through special tests.
Examples:
• Detection of antibodies against HIV in an apparently healthy person.
• Ova of intestinal parasite in the stool of apparently healthy children.
• The pre-symptomatic (sub-clinical) stage may lead to the clinical stage,
or may sometimes end in recovery without development of any signs or
symptoms

3. The Clinical stage
• By this stage the person has developed signs and symptoms of the
disease. The clinical stage of different diseases differs in duration,
severity and outcome. The outcomes of this stage may be recovery,
disability or death.
Examples:
• Common cold has a short and mild clinical stage and almost
everyone recovers quickly.
• Polio has a severe clinical stage and many patients develop paralysis
becoming disabled for the rest of their lives.
• Rabies has a relatively short but severe clinical stage and almost
always results in death.
• HIV/ AIDS has a relatively longer clinical stage and eventually results
in death.

4. Stage of disability or death
• Some diseases run their course and then resolve completely
either spontaneously or by treatment.
• In others the disease may result in a residual defect, leaving
the person disabled for a short or longer duration. Still,
other diseases will end in death.
• Disability is limitation of a person's activities including his
role as a parent, wage earner, etc…
Examples:
• Trachoma may cause blindness
• Meningitis may result in blindness or deafness. Meningitis
may also result in death.

Figure 1 – A schematic diagram of the natural history of diseases
and their expected outcomes.
Healthy person
Sub clinical disease
Clinical disease
Disability
Recovery
Recovery
Death

Levels of prevention
Disease Prevention
• The major purpose in investigating the epidemiology of
diseases is to learn how to prevent and control them. Disease
prevention means to interrupt or slow the progression of
disease.
• The aim is to push back the level of detection and
intervention to the precursors and risk factors of disease.
Epidemiology plays a central role in disease prevention by
identifying those modifiable causes.

Table 1- Levels of prevention in relation to
the stage of disease.
Level of
Preve
ntion
Stage of disease Aim Target
Primordial Existence of underlying condition
leading to causation.
Avoiding the emergence and
establishment of the social,
economic, and cultural patterns of
living that are known to contribute
to an elevated risk of disease.
Example: Smoking, environmental
pollution
Total population and
selected groups
Primary Specific causal factors exist. The causative agent exists but the aim
is to prevent the development of
the disease.
Example: Immunization
Total population, selected
groups and healthy
individuals
Secondary Early stage of disease The aim is to cure patients and prevent
the development of advanced
disease.
Example: Early detection and treatment
of cases of tuberculosis and STD
Patients
Tertiary Late stage of disease
(treatment and rehabilitation)
The aim is to prevent severe disability
and death
Example: Leprosy
Patients

1. Primary prevention is aimed at preventing healthy people from
becoming sick. The main objectives of primary prevention are
promoting health, preventing exposure and preventing disease.
Primary prevention keeps the disease process from becoming established by
eliminating causes of disease or increasing resistance to disease.
– Health promotion consists of general non-specific interventions that
enhance health and the body's ability to resist disease.
– Improvement of socioeconomic status, provision of adequate food,
housing, clothing, and education are good examples of health
promotion.

• Prevention of exposure is the avoidance of factors which may
cause disease if an individual is exposed to them. Examples
can be 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 exposure and biological onset.
Immunization can be taken as a good example.

Levels of prevention in relation to the stage of
disease
i. Active immunization- exposing the host to a specific antigen
against which it will manufacture its own antibodies after three
weeks interval.
ii. Passive immunization- providing the host with the antibodies
necessary to fight the disease. It is commonly given after
exposure. Example: Rabies, Tetanus.
• Note: Both active and passive immunization act after exposure has
taken place.
• Immunization does not prevent an infectious organism from invading
the immunized host, but does prevent it from establishing an infection.

Levels of prevention in relation to the stage of
disease
2. Secondary prevention - 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 secondary 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 invasive stage

Levels of prevention cont…..
3. Tertiary prevention – is targeted towards people with chronic diseases and
disabilities that cannot be cured.
Tertiary prevention is needed in some diseases because primary and
secondary prevention have failed, and in others because primary and
secondary prevention are not effective. It has two objectives:
• Treatment to prevent further disability or death and
• To limit the physical, psychological, social, and financial impact of
disability, thereby improving the quality of life.
• This can be done through rehabilitation, which is the retraining of the
remaining functions for maximal effectiveness.

Examples:
• Blindness due to vitamin A deficiency occurs when
primary prevention (adequate nutrition) and
secondary prevention (early detection of corneal
ulcers) have failed, and damage to the cornea
(keratomalacia) can not be treated.
• Tertiary prevention (rehabilitation) can help the
blind or partly blind person learn to do gainful work
and be economically self supporting.

• Diabetes mellitus is a disease that can not really be
prevented or cured i.e. primary and secondary
prevention are not effective.
• Hence, the goal of tertiary prevention in diabetics is
to control the level of their blood sugar using drugs
and/ or diet, and to treat complications promptly in
order to improve the quality of life, prevent
permanent damages such as blindness, and prevent
early death.

Chapter Two
The Subject Matter of Epidemiology (Definition, Scope, Purpose)
Definition
• Epidemiology has been defined in many ways. The word
comes from the Greek language, in which epi means upon,
demos denotes the population, and the combining form-logy
means the study of. Thus, epidemiology is the study of some
thing that affects the population.
• Usually, Epidemiology is defined as the study of the
frequency, distribution and determinants of diseases and
other health related states or events in specified populations,
and the application of this study to the promotion of health,
and to the prevention and control of health problems.

Subject Matter of Epidemiology continues..
• Epidemiology offers insight into why disease and injury affect some people
more than others, and why they occur more frequently in some locations
and times than in others.
• It is an applied science, with direct and practical applications. This
knowledge is necessary for finding the most effective ways to prevent and
treat health problems.
• It is considered the basic science of public health.
Components of the definition
• “Population” the focus of epidemiology is mainly on the population rather
than individuals.
• “Frequency” shows epidemiology to be mainly a quantitative science.
Epidemiology is concerned with the frequency of diseases and other
health related conditions. Frequency of diseases is measured by
morbidity rates and mortality rates.

• Health related conditions” are conditions which directly or indirectly affect or
influence health. These may be injuries, vital events, health related behaviors,
social factors, economic factors etc.
• “Distribution” refers to “ the geographical distribution of diseases, the distribution
in time, or/and distribution by type of persons affected.
• The part of epidemiology concerned with the frequency and distribution of
diseases by time, person and place is named Descriptive Epidemiology. It asks the
questions: how many? Where? When? What?
• “Determinants” are factors which determine whether or not a person
will get a disease.
• The part of epidemiology dealing with the causes and determinants of diseases is
Analytical Epidemiology. It asks the questions: how? Why?

History of Epidemiology
• Although epidemiological thinking has been traced to the
time of Hippocrates, who lived around 5th century B.C., the
discipline did not flourish until the 1940s.
• Hippocrates displayed an extraordinary awareness of the
impact of environment and behavior on personal well–being.
Hippocrates therefore identified forces that epidemiologists
today recognize as major determinants of human health.

 The most important advances in epidemiology is attributed to the English man
John Graunt (1620 – 1674). In his pioneering research, Graunt noted that
biological phenomena, such as births and deaths, varied in predictable and regular
ways.
 His research laid the groundwork for the disciplines of both epidemiology and
demography. He observed that male births consistently outnumbered female
births.
 Graunt also noted a relatively higher urban than rural death rate and seasonal
variation in mortality rates. His work is summarized in the “Natural and Political
Observations…. Upon the Bills of Mortality”, which was first published in England
in 1662.
 He analyzed reports of births and deaths, quantified patterns of disease in a
population, noted seasonal variation in mortality, recognized the value of routinely
collected data in providing information and noted high infant mortality rate (IMR).

• In 1747, Lind used an experimental approach to prove the cause of scurvy
by showing it could be treated effectively with fresh fruit.
• In 1839, William Farr, an English physician, established the tradition of
application of vital statistical data for the evaluation of health problems.
• In 1849, John Snow an English physician formulated and tested a
hypothesis concerning the origin of an epidemic of cholera in London.
Snow postulated that cholera was transmitted by contaminated water.
• Epidemiology is a relatively new discipline, and its scope and purposes are
widening from time to time.

Scope of Epidemiology
Originally, epidemiology was concerned with epidemics of communicable diseases and
epidemic investigations. Later it was extended to endemic communicable diseases
and non-communicable diseases.
• At present epidemiologic methods are being applied to:
• Infectious and non infectious diseases
• Injuries and accidents
• Nutritional deficiencies
• Mental disorders
• Maternal and child health
• Congenital anomalies
• Cancer
• Occupational health
• Environmental health
• Health behaviors
• Violence etc.

• Hence, epidemiology can be applied to all disease
conditions and other health related events.
Purpose of Epidemiology
• The ultimate purpose of Epidemiology is prevention and
control of disease, in an effort to improve the health status
of populations.
This is realized through:
• Elucidation of the natural history of disease
• Description of the health status of the population
• Establishing the determinants/causation of disease
• Evaluation of intervention

• Uses of Epidemiology
• Monitoring the Public Health
• Studying the natural history of disease
• Looking for causes of disease , death or disability-
aetiological agents
• Evaluating interventions and health service provision
• Planning health services
• Decision making in clinical medicine

Basic Assumptions in Epidemiology
• There are two basic assumptions in epidemiology.
These are:
• Non random distribution of diseases i.e. the distribution of disease in
human population is not random or by chance and
• Human diseases have causal and preventive factors that can be identified
through systematic investigations of different populations.
•
• Since distribution of diseases is not random or by chance, we need to
identify what factors lead to the higher level of occurrence of a disease in
one area as compared to others. Epidemiology is also based on the
assumption that diseases have causal and preventive factors and these
can be identified by studying human populations at different places and
times.

Chapter Three
Principles of Disease Causation and Models
Disease Causation
• Cause of a disease: is an event, condition, or characteristic that preceded
the disease event and without which the disease event either would not
have occurred at all, or would not have occurred until some later time.
• A common characteristic of the concept of causation is the assumption of a
one-to-one correspondence between the observed cause and the effect.
Each cause is seen as necessary and sufficient in itself to produce the effect.
• A “sufficient cause,” can be defined as a set of minimal conditions and
events that inevitably produce disease; “minimal” implies that all of the
conditions or events are necessary.

Principles of Disease continues…
Principle of Causation
• There are two principles of disease causation. Namely:
1. The single germ theory and
2. The ecological approach
The Germ theory
• Luis Pasteur isolated microorganism. This discovery led to Koch's
postulate in 1877. It was a set rule for the determination of causation.
Koch's Postulate states that:
• The organism must be present in every case.
• The organism must be isolated and grown in culture.
• The organism must, when inoculated into a susceptible animal, cause the
specific disease.
• The organism must then be recovered from the animal.

The Ecological approach
• Ecology is defined as the study of the relationship of organisms to each
other as well as to all other aspects of the environment.
• Since disease arises within an ecological system, a basic tenet of
epidemiology is that an ecological approach is necessary to explain the
occurrence of disease; disease cannot be attributed to the operation of
any one factor.
• The requirement that more than one factor be present for disease to
develop is referred to as multiple causation or multifactorial etiology.
•
• In the ecological view, an agent is considered to be necessary but not
sufficient cause of disease because the conditions of the host and
environment must also be optimal for a disease to develop.
Example: Mycobacterium tubercle bacilli is a necessary but not sufficient
cause for tuberculosis

Etiology of disease: All factors that contribute to the occurrence of a disease. These
factors are related to agent, host and environment.
• I. The Agent
A. Nutritive elements, e.g.,
Excessive Cholesterol
Deficiency Vitamins, Proteins
B. Chemical Agents , e.g.,
Poison Carbon monoxide (CO)
C. Physical Agents , e.g., Radiation
D. Infectious Agents , e.g.,
Metazoa Hookworm, Schistosomiasis
Protozoa Amoeba
Bacteria M.Tb
Fungus Candidiasis
Virus Measles

II. Host Factors: Influence exposure, susceptibility or response to
agents.
• Genetic
– Age , Sex
• Physiologic state
– Pregnancy, Puberty , stress
• Immunologic condition
– Active immunity: Prior infection, immunization
– Passive immunity: Gamma globulin
• Human behavior
– Hygiene
– Diet handling

* Host factors result from the interaction of genetic endowment with the
environment.
Example:
• Blood group A has been found to be associated with higher incidence of gastric
carcinoma
• Blood group O has been found to be associated with higher incidence of duodenal
ulcer
• III. Environmental Factors: Influence the existence of the
agent, exposure, or susceptibility to agent.
• A. Biological environment
• Infectious agents
• Reservoirs (man, animal, soil)
• Vectors (flies, mosquitoes)

B. Social environment
• Socioeconomic and political organizations affect the level
of medical care.
C. Physical environment
• Heat, Light, Water, Air
• Industrial wastes
• Chemical agents of all kinds
• Indoor air pollution
It is the interaction of the above factors (agent, host, and
environment) which determines whether or not a disease
develops, and this can be illustrated using different models.

• Disease Models
• How do diseases develop? Epidemiology helps researchers
visualize disease and injury etiology through models. There
are a number of disease causation models, however, the
epidemiologic triangle, the web of causation, and the wheel
are among the best known of these models.
• The epidemiologic triangle
Agent
Host Environment

• The most familiar disease model, the epidemiologic triad
(triangle), depicts a relationship among three key factors in
the occurrence of disease or injury: agent, environment, and
host.
• An agent is a factor whose presence or absence, excess or
deficit is necessary for a particular disease or injury to occur.
• General classes of disease agents include chemicals such as
benzene, oxygen, and asbestos; microorganisms such as
bacteria, viruses, fungi, and protozoa; and physical energy
sources such as electricity and radiation.

• Many diseases and injuries have multiple agents.
• The environment includes all external factors, other than the
agent, that can influence health.
• These factors are further categorized according to whether
they belong in the social, physical, or biological
environments.

• The social environment encompasses a broad
range of factors, including laws about seat
belt, and helmet use; availability of medical
care and health insurance; cultural “dos” and
“don’ts” regarding diet; and many other
factors pertaining to political, legal, economic,
educational, communications, transportation,
and health care systems.

• The Physical environmental factors that
influence health include climate, terrain, and
pollution.
• The Biological environmental influences
include disease and injury vectors; soil,
humans and plants serving as reservoirs of
infection; and plant and animal sources of
drugs and antigens.

• The host is the actual or potential recipient or victim of disease or injury.
Although the agent and environment combine to “cause” the illness or
injury, host susceptibility is affected by personal characteristics such as
age, occupation, income, education, personality, behavior, and gender and
other genetic traits.
• Sometimes genes themselves are disease agents, as in hemophilia and
sickle cell anemia.
• The perspective of epidemiologic triad, the host, agent, and environment
can coexist harmoniously. Disease and injury occur only when there is
interaction or altered equilibrium between them.
• If an agent, in combination with environmental factors, can act on
susceptible host to create disease, then disruption of any link among
these three factors can also prevent disease.

The web of causation
• Although the epidemiologic triad has contributed to the
understanding of disease etiology, the process that actually
generates disease or leads to injury is much more complex.
• This complexity is better portrayed in a second model, the
web of causation
• The web of causation was developed especially to enhance
understanding of chronic disease, such as cardiovascular
disease.
• However, it can also be applied to the study of injury and
communicable diseases.

• The web of causation de-emphasizes the role of the agent and
highlights other factors that encourage the onset of disease.
• Using this model, scientists can diagram how factors such as
stress, diet, heredity, and physical activity relate to the onset
of the three major types of cardiovascular disease: coronary
heart disease, cerebrovascular disease (stroke), and
hypertensive disease.
• In addition, the approach reveals that each of these diseases
has a precursor, for example, hypertension, that can alert a
diagnostician to the danger of a more serious underlying
condition.

Stress Diet
Hormones Physical activity
Smoking Obesity Heredity
Blood clotting Hardening of the arteries Hypertension
Heart disease Stroke Hypertensive disease

The Wheel
• A model that uses the wheel is another approach to depict human – environment
relations.
• The wheel consists of a hub (the host or human), which has genetic makeup as its
core. Surrounding the host is the environment, schematically divided into
biological, social, and physical.
• The relative sizes of the different components of the wheel depend upon the
specific disease problem under consideration.
• For hereditary diseases, the genetic core would be relatively large. For conditions
like measles the genetic core would be of lesser importance; the state of immunity
of the host and the biological sector would contribute more heavily.
• In contrast to the web of causation, the wheel model does encourage separate
delineation of host and environmental factors, a distinction useful for
epidemiologic analyses

 Biologic Environment
Host (man)
 Genetic core
 Social Environment
 Physical Environment

Chapter Four: The Infectious Disease Process
• Infection implies that the agent has achieved entry and begun
to develop or multiply, whether or not the process leads to
disease.
• A model used to understand the infection process is called
the chain of infection . Each link must be present and in
sequential order for an infection to occur.
• Understanding the characteristics of each link provides with
methods to prevent the spread of infection. Sometimes the
chain of infection is referred as the transmission cycle.

• The infectious process of a specific disease can be
described by the following components, which
constitute of the chain of disease transmission.
1. The Agent
2. Its reservoirs
3. Its portal of exits
4. Its mode of transmission
5. Its portals of entry
6. The human host

The Infectious Disease Continues…
The Agents
• The agents in the infectious process range from viral
particles to complex multi-cellular organisms. These can
be characterized through their:
– Size
– Chemical character
– Antigenic makeup
– Ability to survive outside the host
– Ability to produce toxin etc
• Host agent interaction is characterized by infectivity,
pathogenicity, virulence or immunogenicity.

Infectious Host Susceptible Host
Transmission depends on:
• -infectious host
• -susceptible host
• -contact definition
• -infectious agent

Infectivity: The ability of an agent to invade and
multiply in a host, i.e. the ability to produce
infection
Pathogenicity: The ability to produce clinically
apparent infection.
Virulence: The proportion of clinical cases
resulting in severe clinical disease.
Immunogenicity: The infection's ability to
produce specific immunity.

Factors which can change the above properties for
infectious agents are:
• Environmental conditions: may be favorable or
unfavorable to the specific agent
• Dose of the agent: severity of disease may be related
to the amount entering the host body
• Route of infection: the same agent may cause
different levels of severity according to the route of
entry into the body
• Host factors (Age, race, nutritional status)

Pathogenic mechanisms
• Infectious agents may bring about pathologic effects
through different mechanisms.
• Some agents may use more than one mechanism at
ones, or sometimes different mechanisms may lead
to illnesses with different characteristics as a result
of infection by the same agent.

• The different mechanisms employed by infectious
pathogens are:
1. Direct tissue invasion
2. Production of a toxin
3. Immunologic enhancement or allergic reaction
4. Persistent or latent infection
5. Enhancement of host susceptibility to drugs.
6. Immune suppression

II. Reservoirs
A reservoir is an organism or habitat, in which an infectious
agent normally lives, transforms, develops and/or
multiplies.
• Reservoirs for infectious agents may be humans, animals,
plants or other inanimate objects.
Some diseases with human reservoirs are:
• Most bacterial and viral respiratory diseases
• Most staphylococcal and streptococcal infections
• STD, mumps, typhoid etc.

• All infected humans, whether showing signs and symptoms of
the disease or not, are potential sources of infection to
others.
• A person who does not have apparent clinical disease, but is
a potential source of infection to other people is called a
Carrier. Carriers may be classified as:
1. Incubatory carriers: Transmitting the disease during
incubation period, i.e. from first shedding of the agent until
the clinical onset.
Example: Measles, mumps

2. Convalescent carriers: Transmitting the disease during
convalescence period i.e. from the time of recovery to when
shedding stops.
Example: Typhoid fever
3. Asymptomatic carriers: Transmitting the disease without ever
showing manifestations of the disease.
Example: Polio, Amoebiasis
4. Chronic carriers: Transmitting the disease for a long period /
indefinite transmission.
Example: Viral Hepatitis, Typhoid fever.

Figure 3. Time Course of a Disease
in Relation to Its Clinical Expression and Communicability

Some diseases are transmitted to human beings from animals.
These diseases are called zoonoses.
Examples: Rabies, anthrax, brucellosis etc.
III. Portal of exit
• Portal of exit is the way the infectious agent leaves the
reservoir.
• Possible portals of exit include all body secretions and
discharges: Mucus, saliva, tears, breast milk, vaginal and
cervical discharges, excretions (feces and urine), blood,
and tissues.

IV. Mode of Transmission
• Modes of transmission include the various mechanisms by
which agents are conveyed to a susceptible host.
• Transmission may be direct or indirect.
1. Direct transmission
1.1. Direct contact: The contact of skin, mucosa, or conjunctiva with
infectious agents directly from person or vertebrate animal, via
touching, kissing, biting, passage through the birth canal, or during
sexual intercourse.
Example: HIV, rabies, gonorrhea

1.2 Direct projection: projection of saliva droplets
by coughing, sneezing, singing, spitting or
talking.
Example: common cold
1.3 Transplacental: Transmission from mother to
fetus.
Example: syphilis

2. Indirect transmission
2.1 Vehicle-borne: Transmission occurs through
indirect contact with inanimate objects (fomites):
bedding, toys, or surgical instruments; as well as
through contaminated food, water, IV fluids etc.
2.2 Vector-borne: The infectious agent is conveyed by
an arthropod to a host. Vectors may be biological
or mechanical.

• Biological vector: If the agent multiplies in the vector before
transmission.
– Salivarian Example: Malaria by the anophelus mosquito
– Stercorarian Example: Typhus by ticks or lice
• Mechanical vector: If the agent is carried by the leg or
proboscis.
• Example: Trachoma by flies
2.3 Airborne: which may occur by dust or droplet nuclei (dried
residue of aerosols)
• Example: Tuberculosis

2.4 Non vector intermediate host: hosts not playing an active
role in transporting the agent to humans.
Example: Aquatic snails in the transmission of
schistosomiasis.
• Portal of entry: the site where an infectious agent enters a
susceptible host. These are:
• The Mucosa:
• Nasal - common cold
• Conjunctival - Trachoma
• Respiratory - Tuberculosis

• Vaginal- Sexually transmitted diseases
• Urethral- Chlamydial infection
• Anal - Sexually transmitted diseases
• Injury site: Tetanus
• The skin: Hook worm infection
(Ancylostomiasis)
•
VI. Host: The susceptible human host is the final link in
the infectious process. Host susceptibility can be
seen at the individual level and at the community
level.

• At the individual level: The state of the host at any given time
is the interaction of genetic endowment with the
environment over the entire life span.
• The relative contributions of genetics and environmental
factors in the susceptibility of the host for diseases are not
always clear.
Examples:
• Genetic factors: sex, blood type, ethnicity etc.
• Environmental factors: immunity acquired as a result of past
infection

• At the community level: Host resistance at the community
(population) level is called herd immunity.
• Herd immunity can be defined as the resistance of a
community (group) to invasion and spread of an infectious
agent, based on the immunity of a high proportion of
individuals in the community.
• The high proportion of immunes prevents transmission by
highly decreasing the probability of contact between
reservoirs and susceptible hosts

• Conditions under which herd immunity best functions
1. Single reservoir (the human host): If there is other source of infection it
can transmit the infection to susceptible hosts.
2. Direct transmission (direct contact or direct projection): Herd immunity is
less effective for diseases with efficient airborne transmission.
3. Total immunity: Partially immune hosts may continue to shed the agent,
and hence increase the likelihood of bringing the infection to susceptible
hosts.
4. No shedding of agents by immune hosts (no carrier state).

5. No overcrowding: Overcrowding also
increases the likelihood of contact between
reservoirs and susceptible hosts.
However, these conditions for the operation
of herd immunity are seldom fulfilled.

TIME COURSE OF AN INFECTIOUS DISEASE
• Pre-patent Period: The time interval between biological onset
and the time of first shedding of the agent.
• Incubation Period: Interval between biological onset and clinical
onset.
• Communicable Period: The time interval during which the agent
is shed by the host.
• Latent Period: The interval between recovery and relapse in
clinical disease

Chapter Five :Sources of Data for Community Health
• There are different sources of data on health and health
related conditions in the community. Each source has
advantages and limitations.
• The information obtained from these sources is used for
health planning, programming and evaluation of health
services.
The major sources are the following.
1. Census:
• Census is defined as a periodic count or enumeration of a
population.

Sources of Data Continues….
• Census data are necessary for accurate description of
population’s health status and are principal source of
denominator for rates of disease & death.
It provides information on:
• Size and composition of a population
• The forces that determine these variability
• The trends anticipated in the future.
• There are two types of census counts. They are called de facto and de jure.
• De facto counts persons according to their location at the time of
enumeration, but excludes those who are temporarily away.
• De jure counts according to their usual place of residence and excludes
temporary visits.

In Ethiopia censuses were conducted three times, i.e., in 1984
,1994 and 1999. Data were collected on:
• Age, sex and size of the population
• Mortality, fertility
• Language, ethnicity
• Housing
From these data different health indices could be calculated.
• Crude birth rate, crude death rate, age specific mortality rate
and sex specific mortality rate are some of the examples of
the indicators that could be calculated.

• Limitation
• Conducting nationwide census is very
expensive and it generates a large amount of
data which takes a very long time to compile
and analyze. .
• It is carried out every 10 years. Therefore it
can’t assess yearly changes.

Vital statistics:
• This is a system by which all births and deaths occurring
nationwide are registered, reported and compiled centrally.
Certificate is issued for each birth and death.
• It is the source of information for the calculation of birth and
death rates. Cause specific mortality rate can also be
calculated since cause of death is recorded on death
certificates.
• The denominator however comes from census. The main
characteristics of vital statistics are:

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 a source of information.
• Continuous – it should be an ongoing process.
There is no nationwide birth and death registration system in Ethiopia.
Health Service Records: All health institutions report their activities to the
Ministry of Health.
• The Ministry compiles, analyzes the data and publishes it in the health
service directory.
• It is therefore the major source of health information in Ethiopia.

Advantages:
• Easily obtainable
• Available at low cost
• Continuous system of reporting
• Causes of illness and death available.

Limitations:
• Lack of completeness – health service coverage is only 72%.
• Lack of representative ness – a small proportion of diseased
population seeks medical advice.
• Lack of denominator – catchments are not known in majority
of cases.
• Lack of uniformity in quality
• Diagnosis varies across the level of health institutions.
• Lack of compliance with reporting.
• Irregularity and incompleteness of published compilations.

Notification of Infectious Diseases
• There are some internationally notifiable diseases.
• WHO member states report on Plague, Cholera, and Yellow fever.
Moreover, every country has its own list of notifiable diseases.
In Ethiopia, in addition to the above, the following diseases are notifiable.
• Measles,
• Poliomyelitis,
• Neonatal Tetanus
• Meningococcal Meningitis
• Diarrhea,
• Diarrhea with severe dehydration in under five children
• Bloody diarrhea
• Typhoid Fever

• Tuberculosis,
• Malaria,
• Epidemic Typhus,
• Relapsing Fever
• Viral Hemorrhagic Fever
• HIV/AIDS
• Sexually Transmitted Infection (STI)
• Onchocerciasis
• Dracunculiasis
• Pneumonia in under five children
• Leprosy
The major problems related to this source are low compliance and delays in
reporting.

Health Surveys
• These are studies conducted on a representative sample population to
obtain more comprehensive data for monitoring the health status of a
population.
There are two types of health surveys:
A. Surveys of specific diseases: These are studies conducted on each
specific disease. Examples are:
• Expanded Programme for Immunization (EPI)
• Control of Diarrheal Diseases (CDD)
• Prevention and control of HIV/AIDS
• Prevention of Blindness
• Tuberculosis / Leprosy control

B. Surveys of general health status:
 These are studies on general health status of the population.
They are based on interview, physical examination and laboratory tests.
 They are more reliable as compared to surveys of specific diseases, but more
expensive.
Advantages of surveys based on interview:
• They are more representative of the health condition of the community.
• The denominator is known.
• Data are more uniform in quality.
Limitations:
• Data accuracy is dependent on the memory and cooperation of the interviewee.
• Surveys are expensive.

Chapter Six: Measurements of Morbidity and
Mortality
• Epidemiology is mainly a quantitative science.
• Measures of disease frequency are the basic tools of
the epidemiological approach.
• Health status of a community is assessed by the
collection, compilation, analysis and interpretation of
data on illness (morbidity), on death (mortality),
disability and utilization of health services.

Measurements continues…..
• The most basic measure of disease frequency is a simple count of affected
individuals.
• Such information is useful for public health planners and administrators
for proper allocation of health care resources in a particular community.
• However, to investigate distributions and determinants of disease, it is
also necessary to know the size of the source population from which
affected individuals were counted.
• One of the central concerns of epidemiology is to find and enumerate
appropriate denominators in order to describe and to compare groups in a
meaningful and useful way.
• Such measures allow direct comparisons of disease frequencies in two or
more groups of individuals.

• The number of cases in a given community can give more
epidemiologic sense if they are related to the size of the
population.
• The number of cases with the population size can be
determined by calculating ratios, proportions, and rates.
•
• These measures provide useful information about
the probability of occurrence of health events, population at a
higher risk of acquiring the disease.
• They are also important in designing appropriate public health
interventions.

• The most important epidemiological tool used for measuring diseases is the rate;
however, ratios and proportions are also used.
• A ratio quantifies the magnitude of one occurrence or condition to another. It
expresses the relationship between two numbers in the form of x: y or
x/y X k .
• In Ratio the value of x and y may be completely independent, or x may be included
in y. Example: The ratio of males to females in Somaliland.
• A proportion quantifies occurrences in relation to the populations in
which these occurrences take place. It is a specific type of ratio in which
the numerator is included in the denominator and the result is expressed
as a percentage.
Example: The proportion of all births that was male
Male births / Male + Female births x100

Rate
• Rate is a special form of proportion that includes the dimension of time.
• It is the measure that most clearly expresses probability or risk of disease in a
defined population over a specified period of time,
• It is considered to be a basic measure of disease occurrence.
• Accurate count of all events of interest that occur in a defined population during a
specified period is essential for the calculation of rate.
• Rate = Number of events in a specific period x k
Pop at risk of these events in a specified Period
Example: The number of newly diagnosed breast cancer cases per 100,000 women.

Types of rates
There are three types of rates:
• Crude rates
• Specific rates
• Adjusted rates
• Crude rates are summary rates based on the actual number of events (births,
deaths, diseases) in the total population over a given time period.
• The crude rates that are widely used in description of populations are the crude
birth rate (CBR) and the crude death rate (CDR).
• These rates refer to the total population, and hence, may obscure the possible
difference in risk among subgroups of the total population.
• Example: the risk of death differs among different age groups

Crude death rates depend on two factors.
• The probability of dying for individuals
• The age distribution of the population
Advantages:
Actual summary rates
• Calculable from minimum information
• Widely used despite limitations
Disadvantages:
• Difficult to interpret due to variation in composition (e.g.: age)
• Obscure significant differences in risk between subgroups.

Specific rates
• Specific rates apply to specific subgroups in the population, such as a
specific age group, sex, occupation, marital status, etc.
• When calculating specific rates, except for cause-specific rates, the
denominator should be the population in that specific group (NOT the
total population).
• As a result, specific rates do not add up to a crude rate.
• ** Do not add age specific rates to get crude rate, take the weighted
average.
• Example: Infant Mortality Rate (IMR), Neonatal Mortality Rate (NMR),
Maternal Mortality Ratio (MMR)

Advantages:
• The rates apply to homogenous subgroups
• The rates are detailed and useful for epidemiological and
public health purposes.
• Disadvantages:
• It is cumbersome to compare many subgroups of two or more
populations
Adjusted rates
• Adjusted rates are summary rates that have undergone
statistical transformation, to permit fair comparison between
groups differing in some characteristics that may affect risk of
disease.

• For example: age needs adjustment due to its
marked effect on both diseases and death.
• When comparing the crude death rates of two or more
places, it is impossible to know whether the difference is due
to age composition, age specific death rate or both.
• In Age adjusted rates the difference is exclusively attributed to
differences in age specific mortality rates, since the effect of
age composition is artificially removed.

Advantages:
• Summary rates
• Permit unbiased comparison
• Easy to interpret
• Disadvantages:
• Fictitious rates
• Absolute magnitude depends on standard population
• Opposing trends in subgroups masked.
Methods of adjustment
• Direct method
• When using the direct method, the adjusted rate is derived by applying
the category specific rates observed in each of the populations to a single
standard population.

To calculate the crude death rate (CDR):
• Multiply the ASMR in each age group by the number of
people in the same group; this will give the annual number of
deaths occurring in the specific age group.
• Add the number of deaths occurring in each age group to
obtain the total number of deaths
• Then divide the total number of deaths by the total
population of each area.

To calculate the age-adjusted rate:
• Use a standard population for each age group of both areas.
Note that the populations of the groups to be compared have
to be equal when standardizing. For example use 1000 as a
standard for each age category of both population, or you
may use one population either A or B as a standard.
• Then follow the steps you took when calculating the CDR, but
this time using the standard population.

Indirect method
• This method implies the process of applying the
specific rates of a standard population to a
population of interest to yield a number of
"expected" deaths.
• A common way of carrying out indirect age
adjustment is to relate the total expected deaths
thus obtained to observed deaths through a
formula known as the standardized mortality ratio
(SMR).

• SMR = Total observed deaths in a population
Total expected deaths in that population
• If SMR > 1
More deaths are observed in the smaller population than would
be expected on the basis of rates in the larger (standard)
population.
• If SMR <1
Fewer deaths are observed than expected.
• This method is used to compare two populations, in one of
which the ASMR are not known or are excessively variable
because of small numbers.

Measurements of morbidity
Incidence:
• The incidence of a disease is defined as the number
of new cases of a disease that occur during a
specified period of time in a population at risk for
developing the disease.
• Incidence rate = Number of new cases of a disease over a period of time
Population at risk during the given period of time

• The critical element in the definition of incidence is new cases of disease.
• Incidence is a measure of events – the disease develops in a person who
did not have the disease previously. Incidence is a measure of new events
(i.e. transition from a non-diseased to a diseased state), incidence is a
measure of risk.
• The appropriate denominator for incidence rate is population at risk. For
incidence to be meaningful, any individual who is included in the
denominator must have the potential to become part of the group that is
counted in the numerator.
• Thus, if we are calculating incidence for prostate cancer, the denominator
must include only men, because women are not at risk for developing
prostate cancer.

• Another important issue in regard to the denominator is the issue of time.
For incidence to be a measure of risk we must specify a period of time and
we must know that all of the individuals in the group represented by the
denominator have been followed up for that entire period.
• The choice of time period is arbitrary: We could calculate incidence in one
week, incidence in one month, incidence in one year, incidence in 5 years,
and so on.
• Nevertheless the determination of population at risk is a major problem in
the study of disease incidences.

It may require a detailed study based on:
interviews
medical records
or serology for antibodies, which are very
expensive and time consuming.
Population fluctuation due to births, deaths,
and migration is another problem in the
calculation of the denominator.

Types of incidence
• Cumulative Incidence (CI): An incidence rate that is calculated from a
population that is more or less stable (little fluctuation over the interval
considered), by taking the population at the beginning of the time period
as denominator.
• The cumulative incidence assumes that the entire population at risk at the
beginning of the study period has been followed for the specified time
interval for the development of the outcome under investigation.
• It provides an estimate of the probability, or risk, that an individual will
develop a disease during a specified period of time.

CI = Number of new cases of a disease during a given period of time
Total population at risk
2. Incidence Density:
An incidence rate whose denominator is calculated using person-time units. Similar to other
measure of incidence, the numerator of the incidence density is the number of new cases
in the population.
The denominator, however, is the sum of each individual’s time at risk or the sum of the time
that each person remained under observation, i.e., person – time denominator.
This is particularly when one is studying a group whose members are observed for different
lengths of time.
In presenting incidence density, it is essential to specify the time units – that is, whether the rate
represents the number of cases per person – day, person – month or person – year.

Incidence density =Number of new cases during a given period x 10 n
Time each person was observed, totaled for all
• Often used in cohort studies of diseases with long incubation
or latency period.
Basic requirements for calculating incidence rates
1. Knowledge of the health status of the study population
• To be able to classify people as “diseased" and "not
diseased", there should be adequate basis for assessing the
health of the individuals in a population.

• The information necessary for this may be obtained from health service records, or
may require screening or making detailed examination of the general population.
2. Time of Onset
• Since incidence rates deal with newly developing diseases, identifying the date of
onset is necessary.
• However, this may be difficult for diseases with indefinite onsets. For example for
cancers the actual date of onset is practically impossible to identify, therefore the
date of onset is usually taken as the date of definite diagnosis.
3. Specification of Numerator: Number of persons versus number of conditions
• Sometimes one person may have more than one episode of the illness under
study; therefore it is absolutely necessary to indicate whether the numerator
addresses number of conditions or number of persons.

• Example: children may have more than one episode of diarrhea in a
one-year period. Hence, it is possible to construct two types of
incidence rates from this.
• Number of children who developed diarrhea in one-year period
Number of children at risk
• Number of episodes of diarrhea in children in one-year period
Number of children at risk
4. Specification of Denominator:
• The denominator for incidence studies should consist of a defined
population that is at risk of developing the disease under
consideration.
• It should not include those who have the disease or those who are not
susceptible to the disease

5. Period of Observation:
• Incidence rates must be stated in terms of a definite period of time.
• It can be any length of time. The time has to be long enough to ensure stability of
the numerator.
• Person-time denominator must be used for unequal periods of observation.
• This helps to weigh the contribution of each study subjects when there is attrition
because; individuals die, move away or get lost to follow up.
Prevalence rate
• 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 rates.

1. Period Prevalence rate
2. Point 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 = No. of people with the condition during a
specific period of time
Total population

• Point Prevalence rate: measures the proportion of a
population with a certain condition at a given point
in time. This is not a true rate; rather it is a simple
proportion.
• Point Prevalence rate = All persons with a specific
Condition at one point in time
Total population
**The basic requirements for prevalence study are
similar to that of incidence study except for “time of
onset”.

• Relationship between incidence and point prevalence
• Since point prevalence rate includes both new and pre-existing cases, it is
directly related to the incidence rate.
• Point prevalence rate is directly proportional both to the incidence rate
and to the average duration of the disease.
• Point Prevalence rate ~ IR x D
Uses:
• Prevalence rates are important particularly for:
• Chronic disease studies
• Planning health facilities and manpower
• Monitoring disease control programs
• Tracking changes in disease patterns over time

Incidence rate is important as:
• A fundamental tool for etiologic studies of acute and chronic
diseases
• A direct measure of risk
• High prevalence may reflect an increase in survival due to
change in virulence or in host factors or improvement in
medical care.
• Low prevalence may reflect:
• A rapidly fatal process
• Rapid cure of disease
• Low incidence

Limitations of prevalence studies
• Prevalence studies favor inclusion of chronic over
acute cases.
• Disease status and attribute are measured at the
same time; hence, temporal relations cannot be
established.
• Measurements of Mortality: mortality rates and
ratios

Measurements of Mortality: mortality rates and ratios
• Mortality rates and ratios measure the occurrence of deaths 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 done because population size fluctuates over time due to births, deaths and
migration.
•
• Below are given some formulas for the commonly used mortality rates and ratios.
• Crude Death rate (CDR) = Total no. of deaths reported during a given time interval
X 1000
• Estimated mid interval
population

• Crude Death rate (CDR) = Total no. of deaths reported during
a given time interval X 1000
Estimated mid interval population
• Age- specific mortality rate = No. of deaths in a specific age
group during a given time X1000
Estimated mid interval population of sp. age group
• Sex- specific mortality rate = No. of deaths in a specific sex
during a given time X 1000
Estimated mid interval population of same sex

• Cause- specific mortality rate = No. of deaths from a specific
cause during a given time X 100,000
Estimated mid interval population
• Proportionate mortality ratio = No. of deaths from a sp.
cause during a given time x 100
Total no. of deaths from all causes in the same time
• Case Fatality Rate (CFR) = No. of deaths from a sp. disease
during a given time x 100
No. of cases of that disease during the same time

• Fetal Death Rate = No. of fetal deaths of 28 wks or more
gestation reported during a given time
No. of fetal deaths of 28 wks or more gestation and live
births in the same time
• Perinatal Mortality Rate = No. of fetal deaths of 28 wks or
more gestation Plus no. of infant deaths under 7 days
No. of fetal deaths of 28 wks or more gestation plus the no.
of live births during the same
• Neonatal Mortality Rate = No. of deaths under 28 days of age
reported during a given time x 1000
• No. of live births reported during the same time

• Infant mortality rate (IMR) = No. of deaths under 1 yr of age during a
given time X 1000
No. of live births reported during the same time interval
• Child mortality rate (CMR) = No. of deaths of 1-4 yrs of age during a given
time X 1000
Average (mid-interval) population of same age at same time
• Under- five mortality rate = No. of deaths of 0-4 yrs of age during a given
time X 1000
Average (mid-interval) population of the same age at same time
• Maternal Mortality Ratio = No. of pregnancy associated deaths of
mothers in a given time x 100000
No. of live births in the same time

• When calculating (using) mortality rates it is important to
understand their interpretations and how they differ from
each other. For example case fatality rate; proportionate
mortality ratio, and cause specific death rates are often
confused.
• They all have the same numerator, i.e. number of deaths from
a specified cause, occurring in a specified population, over a
specified period of time.
• The case fatality rate asks the question: “what proportion of
the people with the disease die of the disease?”

The proportionate mortality ratio asks the question: "out of all the deaths occurring
in that area, what proportion are due to the cause under study?”
• The cause specific death rate asks the question: “out of the total population,
what proportion dies from a certain disease within a specified period of time?”
• **Unlike all specific rates, the cause specific death rate has the total population
as denominator.
Other commonly used indices of health:
• Crude Birth Rate (CBR) =
No. of live births reported during a time interval X 1000
Estimated mid-interval population

• General Fertility Rate = No. of live births reported during a
given time interval X 1000 Estimated no. of
women 15-44 years of age at mid interval
• LBW ratio = No. of live births of weight less than 2500 gms
during a given time x 100
No. of live births reported during the same time interval
• Attack rate = No. of new cases of a sp. disease reported
during an epidemic x k
Total population at risk during the same time

Chapter Seven: Descriptive
Epidemiology
 Descriptive epidemiology is one of the basic types of epidemiology which
is concerned with describing the frequency and distribution of diseases
and other health related conditions by time, place, and person.
 Descriptive epidemiology is a way of organizing data related to health and
health related events by person (Who), place (Where) and time (When) in
a population.
Information organized as such is easy to communicate and
provides information about:
• 1) the magnitude of the problem,
• 2) the populations at greatest risk of acquiring a particular disease, and
• 3) the possible cause (s) of the disease.

Descriptive Continues…
Person
• People can be categorized with respect to many variables.
• In Epidemiologic study it is common to specify three characteristics of a
person – age, sex and ethnic group or race.
• Age: Age is the most important determinant among the personal
variables.
• Mortality and morbidity rates of almost all conditions show some
relations to age. In general ,chronic conditions tend to increase with age.
• Before immunization against infectious disease was available, the
infections that conferred lifelong immunity, like measles, occurred mainly
in young children.

Sex:
• The most striking aspect of analysis of disease rates by sex is the contrast
between mortality and morbidity rates.
• Death rates are higher for males than females, but morbidity rates are
generally higher in females.
• The higher death rates for males throughout life may be due to sex linked
inheritance or to differences in hormonal balance, environment, or habit
pattern. Women has more episodes of illness.
• This is true for women over 45 as well as those in the reproductive years
of life.

• Ethnic group and Race: Many diseases differ
markedly in frequency, severity, or both in different
racial groups.
• Other personal variables: There are also other
personal variables that should be considered during
epidemiologic studies. This includes social class,
religion, occupation, marital status, environmental
exposure etc.

Place
• The frequency of disease is different in different
places. These differences occur because of the
natural boundaries (e.g. mountain range, rivers, and
deserts) or political boundaries.
• Natural boundaries are likely to be more useful than
political boundaries for understanding the etiology of
disease.

• An area defined by natural boundaries may have a
high or low frequency of certain diseases .Because it
is characterized by some particular environmental or
climatic conditions, such as temperature, humidity,
rainfall, altitude, mineral content of soil, or water
supply.
• Despite the relation of natural boundaries and
climate to occurrence of disease, it is often more
convenient to deal with disease statistics by political
units since data for these are more readily available.

Time
• Study of disease occurrence by time is a basic aspect of epidemiologic
analysis. Occurrence is usually expressed on a monthly or annual basis.
There are three major kinds of changes in disease occurrence over time.
1. Secular Trends. This refers to slow and gradual changes over long period of
time, such as years or decades. Such trends may occur in both infectious
and noninfectious conditions. Lung cancer is an example of diseases which
have secular trends.
2. Periodic or cyclic changes. This refers to recurrent alterations in the
frequency of diseases. Cycles may be annual or have some other
periodicity. For example measles epidemic used to occur every two to
three years.

• The most common types of periodicity are in relation to
seasonal changes, or in relation to changes in the number
of susceptible persons in a population.
• Malaria is one example of diseases with seasonal
periodicity, where peaks occur in relation to the rainy
season.
• Meningococcal meningitis is an example of diseases whose
periodicity is affected by both season and the degree of
susceptibility of the population.
3. Sporadic – refers to the occurrence of individual cases or
outbreaks of disease at irregular and unpredictable
intervals.

Epidemiologic Study Designs
Definition of design
Design is an arrangement of conditions for the
collection & analysis of data that leads to the
most accurate answer to the research
question and in the most economical way

Selection of study design
Table 5. Selection of study designs
State of knowledge of the
problem
Types of research questions Study design
Knowledge that problem exists, but
knowing little about its
characteristics of possible causes
-Who is affected?
-How do the affected people behave?
-what do they know, believe, think about
the problem?
-What is the magnitude of the problem?
-Qualitative (e.g FGD)
Or
Quantitative
(Descriptive)
Suspecting that certain factors
contribute to the problem
-Are certain factors indeed associated with
the problem?
Analytic (observational)
-Having sufficient knowledge about
the cause
-to develop & assess an
intervention that would prevent,
control, or solve the problem
-What is the effect of a particular
intervention?
-Which of the alternative strategies gives
better result?
-Are the results in proportion to time/
money spent
Intervention
(experimental)

Classification of Epidemiologic
study designs
Study Designs
Analytical
Descriptive
Case report/Series
Case report/Series
Ecological Cross Sectional

Descriptive study designs
Purpose and characteristics of descriptive study Designs
• Descriptive studies are mainly concerned with the distribution of diseases
with respect to time, place and person.
• They are useful for health managers to allocate resources.
• The information obtained from descriptive studies is important for
hypothesis generation.

• Descriptive studies can use routinely collected information. Hence, they
are less time consuming and less expensive.
Types of descriptive study designs
1. Case report and Case series
A. Case report:
• consists of a careful, detailed report by one or more clinicians
of the profile of a single patient ; more emphasis is given for
unusual findings
.

Example: Case report in 1961
• A 40-year old pre-menopausal woman developed pulmonary
embolism 5 weeks after beginning to use an oral
contraceptive preparation to treat endometriosis .
• What is unusual in this report? Pulmonary embolism is
common in older, postmenopausal women. The investigator
postulated that the drug may have been responsible for this
rare occurrence

B. Case series:
• Describes the characteristics of a number of patients with a
given disease (same diagnosis)
Example: Five young, previously healthy
homosexual men were diagnosed as having pneumocystis carinii
pneumonia at 3 Los Angeles hospitals during a 6 month period
in 1980 to 1981.
• What is unusual in this case series? Until then this form of
pneumonia had been seen almost exclusively among older
men and women whose immune systems were suppressed.

Strength and limitations of Case report and
Case series
Strength
• very useful for hypothesis generation
Limitation
• Report is based on a single or few patients
which can happen just by coincidence
• There is no comparison group

2. Ecological (Correlational) studies
• The units of analysis are populations or groups of people rather than an individual.
• Ecological studies use data from the entire population to compare disease
frequencies between different groups during the same period of time, or in the
same population at different points in time.
• Incidence and prevalence rates are commonly used to quantify disease
occurrence in groups.
• To conduct ecological studies, average exposure level of the communities is
required, not exposure status of each individual.
Example: Incidence of hypertension and average per capita salt consumption
compared between two communities.

3. Cross sectional studies (survey)
• In cross sectional studies, information about the status of an individual
with respect to the presence or absence of exposure and disease is
assessed at a point in time.
• Cross sectional studies also show the picture of social, environmental, or
other problems or events in a population.
• The point in time may be as short as few minutes or as long as two or
three months.
• The time frame of "point in time" is based on the speed of data collection.

• Cross sectional studies are useful for raising
the question of the presence of an association
rather than for testing hypothesis.
• But for factors that remain unaltered over
time such as sex, race, blood group, cross
sectional studies can provide evidence of a
valid statistical association.

Advantages of cross sectional studies:
 are a one-stop, one-time collection of data
 are less expensive & more expedient to conduct
 provide much information useful for planning health services
and medical programs
 show relative distribution of conditions, disease, injury and
disability in groups and populations
 studies are based on a sample of a major population and do
not rely on individuals that present themselves for medical
treatment

• Disadvantages of cross sectional studies
It is difficult to know which occurred first, the
exposure or the outcome. This is known as
"chicken or egg dilemma".
It may not show strong cause-effect
relationships if sample size is small.

Chapter 8: Analytic Epidemiology
Definition
• Analytic epidemiology is the second major type of epidemiology, which
is concerned with analyzing the causes or determinants of disease
Purpose and characteristics of Analytic study designs
• Analytic studies focus on the determinants (causes) of diseases.
• They are used to test hypothesis with the ultimate goal of judging
whether a particular exposure causes or prevents disease.

• One major distinguishing feature of analytic studies is the
use of controls.
Types of Analytic study designs
• There are two major categories of analytic study designs:
1. observational 2. experimental.
• In observational studies the investigator can not take an active
role in allocating people into groups and administering an
exposure to one of the groups.
• He/she simply observes what is happening or what has
happened to the groups under study.

• In experimental studies the investigators themselves allocate
the exposure.
8.1 Observational analytic studies
• Case control and cohort studies are the commonest types of
observational analytic studies.
8.1.1 Case control studies
• Subjects are selected with respect to presence or absence of
disease (outcome), and then inquiries are made about past
exposure to the factor of interest.

• Direction of inquiry
Start
with:Cases (people with disease)------ Exposed, Not exposed
•
Controls (people with out disease____Exposed, Not Exposed
Example: Is cigarette smoking a cause of lung cancer?
• Case control design: Identify people with lung cancer (cases)
and people without lung cancer (controls), then ask both
groups whether they are/were smokers.

• If cigarette smoking is a cause of lung cancer, large proportion of lung
cancer cases will give history of cigarette smoking compared to the normal
individuals (controls)
Steps in conducting case control study
Step 1: Define cases
• One of the first issues to be considered in the design of case control study
is the definition of the disease or outcome of interest.
• It is important that this represent as homogenous a disease entity as
possible.
• To help ensure that cases selected for study represent a homogenous
entity, one of the first tasks in any study is to establish strict diagnostic
criteria for the disease.

• Once the diagnostic criteria and definition of the disease have been clearly
established, the individuals with this condition can be selected from a
number of sources.
Step 2: Select cases
• The investigator should select cases on which he/she can get complete
and reliable information
Places where we can get cases:
• Hospitals (health institutions), easy & inexpensive
• Selection bias is one of the major problems
2. Population (community)—expensive and avoids selection bias

Step 3: Select controls
• Selection of controls should consider comparability,
practicability and economic impact.
• The controls should be similar with the cases except that the
cases have the disease or other outcome of interest.
Sources of controls
• Hospital controls
Advantage:
• Easily identified , readily available in sufficient number, less
cost

• More likely than healthy individuals to be aware of antecedent exposures
or events. This decreases recall bias
• They are more likely to be cooperative
Disadvantages
• They are different from healthy individuals in many ways
• If the controls are patients with diseases known to be associated with the
exposure of interest (either positively or negatively), there will be danger
of altering the direction of association or masking a true association
between the exposure and outcome.
• Hence, patients with diseases known to be associated with the exposure
of interest should be excluded from the control group.

General population controls
Advantages:
• Generalization is possible
• If cases are selected from the population, it is good to select
controls from the population too.
Disadvantage:
• Costly & time consuming
• Recall bias (may not be concerned about past exposure
since they are healthy)
• People might be less motivated to participate

Step 4: Check the exposure status of individuals
both in the cases and controls
• Information regarding the exposure status can be
obtained by interview or from different records.
Step 5: Analysis
• Prepare 2X2 table
• Calculate Odds Ratio (OR)
• Perform statistical tests to check whether there is
significant association

8.1.2 Cohort studies
Cohort study (synonyms: concurrent, follow-up, incidence,
longitudinal, prospective study):
• Subjects are selected by exposure, or determinant of interest,
and followed to see the development of the disease or other
outcome of interest
Example: Is cigarette smoking a cause of lung cancer?
• Cohort design: Identify smokers (exposed) and non smokers
(not exposed) then follow both groups over time (e.g 10
years) and check for development of lung cancer in both
groups.

• If cigarette smoking is a cause of lung cancer, large proportion of smokers
will develop lung cancer compared to the non-smokers
Types of cohort studies
• Classification is based on the temporal relationship between the initiation
of the study and the occurrence of the disease.
1. Prospective cohort study
• at the beginning of the study the outcome has not yet occurred
• is the commonest type (compared to the retrospective cohort)
• unless specified cohort study refers to the prospective type of cohort
• is regarded more reliable than the retrospective cohort

• Start with: Exposed-------Disease, No disease
•
Non- exposed------Disease, No disease
•

2. Retrospective (Historical) cohort study
• the investigation is initiated at a point in time after
both the exposure and disease have already occurred
• less costly and less time consuming
• often uses data collected for other purposes, hence
information obtained might be incomplete and non-
comparable for all subjects

Steps in conducting cohort study
Step 1: Define exposure
Step 2: Select exposed group
During selection consider:
• the frequency of the exposure in the population
• the need to obtain accurate information (exposure/outcome)
• the ease to obtain relevant information and to follow up
Step 3: Select controls (non-exposed)
• control groups should be comparable to the exposed group

Step 4: Identify sources of data for exposure and
outcome
Possible sources of exposure data:
• pre-existing records
• conducting interview
Possible sources of outcome data:
• routine surveillance
• death certificate
• periodic health examination
• hospital records etc..

• Step 5: collect data
Step 6: Analyze data
• prepare 2X2 table
• calculate Relative Risk (RR)
• perform statistical tests to check whether
there is statistical significant association

Statistical significance
• A result is statistically significant whenever
a significance test produces a P-value less than the present
value of alpha, which is conventionally 0.05.
• The implication of statistical significance at an alpha of 0.05 is
that the chance would produce such a difference between
comparison groups no more often than 5 times out of 100.
• This is taken to mean that chance is not responsible for the
out come.

Statistical significance
• The observed difference between two groups is
statistically significant, if the probability of obtaining
a difference at least as great as that observed, purely
by chance variation, is very small (below a certain cut
off point).
• That probability is called p-value!
• P-value is the actual probability of obtaining a
difference at least as great as that observed ,purely
by chance variation.

• The cut off point giving the p-value below which we can
conclude that an observed difference between the two
groups is statistically significant is referred to as the level of
significance.
• This is an arbitrary cut off point ,which is by convention
usually taken as 0.05.
• The higher the p-value (compared to the level of significance)
the greater the likelihood that the difference is due to chance
variation .
• The lower the p- value the likelihood that chance alone
cannot explain the difference; the greater the likelihood that
the difference is real.

Advantages and limitations of cohort and
case control studies
Case control Cohort
Advantages:
optimal for evaluation of rare disease
can examine multiple factors
for a single disease
Quick & inexpensive
relatively simple to carry out
guarantee the number of
persons with a disease
valuable when exposure is rare
can examine multiple effects
of a single exposure
temporal relationship is known
allows direct measurement of risk
minimize bias in ascertainment of exposure
Limitations:
inefficient in evaluation of rare exposure
can not directly compute risk
difficult to establish temporal relationship
determining exposure will
often rely on memory
inefficient in evaluation of
rare diseases
expensive
time consuming
loss to follow up create problem

8.1.3. Cross sectional study
• Even though the main purpose of cross sectional study is for
describing occurrence of disease by time, place and person,
it can be considered as both descriptive and analytic study
design.
• The data collected by cross-sectional study design can be
analyzed in two ways, either by comparing the prevalence
rate of the outcome in exposed versus non-exposed people,
or by comparing the prevalence rate of the exposure in
those with and with out the outcome.

• One feature which distinguishes cross sectional
studies from other types of observational analytic
studies is the timing of the subdivision of the study
population into comparison groups.
• In cohort and case control studies, this takes place
prior to the data collection process.
• In a cross sectional study, this takes place after the
information has been collected.

8.2. Experimental/ Intervention study
• This is an epidemiological study design that closely resembles
the controlled experiment in basic science researches, and
can produce high quality data if done properly.
• The main distinction from other types of analytic studies is
that individuals are allocated into experiment or control group
by the investigators.
• It has essentially the same design as prospective cohort study
with one very key difference, i.e, exposure status of the study
population is deliberately changed by the investigator to
observe how this alters the incidence of disease or other
features of the natural history.

• Experimental is the gold standard study design compared to
other designs.
Classification of Intervention Studies
Intervention studies can generally be considered either
therapeutic or preventive.
• Therapeutic (or secondary prevention) trials are conducted
among patients with a particular disease to determine the
ability of an agent or procedure to diminish symptoms,
prevent recurrence, or decrease risk of death from that
disease.

• A preventive (or primary prevention) trial involves
the evaluation of whether an agent or procedure
reduces the risk of developing disease among those
free from that condition at enrollment.
• While therapeutic trials are virtually always
conducted among individuals, primary prevention
measures can be studied among either individuals
(e.g. vaccine trial), or entire population (Community
trial).

There are different ways of classifying intervention studies.
A. Classification based on the population studied
1. Clinical trial
• usually performed in clinical settings and the subjects are
patients
2 . Field trial
• used in testing medicine for preventive purpose
• subjects are healthy people e.g. vaccine trial
3. Community trial
• unit of the study is group of people/community e.g.
fluoridation of water to prevent dental caries

B. Classification based on design
1. Uncontrolled trial
• no control group
• control will be past experience (history)
2. Non-randomized controlled
• there is control group
• allocation to either group is not randomized
3. Randomized controlled
• there is control group
• there is random allocation of subjects to either group

C. Classification based on objective
1. Phase I
• trial on small subjects to test a new drug with small
dosage to determine the toxic effect
2. Phase II
• trial on small group to determine the therapeutic
effect
3. Phase III
• study on large population
• usually randomized controlled trial

Problems related to experimental studies
1.Ethical considerations prevent evaluation of many treatments
or procedures using intervention studies
Some of the ethical issues:
• Practices or substances already known to be harmful should
not be used in this study.
• Therapies known to be beneficial should not be withheld from
any affected individuals in the study population.
• Investigators have to have a complete knowledge of the
subject under study.

• The researcher must have at least informed consent from each study
participant and subjects should be left free to withdraw from the study at
any time.
• A written research protocol is a must
2. Feasibility / practical issues
– subject recruitment, getting adequate individuals to enroll into the study is
not easy.
– difficult to achieve satisfactory compliance.
• Conducting trial on a widespread practice poses difficulty in getting
sufficiently large population who are willing to undergo through a new
treatment or practice believed to be more beneficial than the old
treatment or practice for the duration of the entire study period; i.e., its
difficult to achieve satisfactory compliance from all study subjects for a
long time, particularly if study period is quite long.
• Getting an appropriate control group is also difficult sometimes.

3. Cost
Experimental studies are very expensive
• Experimental studies are often very expensive
because of the long follow-up period, which is
comparatively longer for preventive trials, and
arrangements for follow up outside the clinic
settings.

Steps in conducting experimental studies
Step 1. Identify new drug/intervention/prevention
Step 2. Identify comparison - e.g. standard treatment
or placebo
Step 3. Define eligible population/ exclusions
Step 4. Define the outcomes and how to assess them
Step 5. Write the protocol
Step 6. Obtain research ethics committee approval

Step 7. Recruit and consent required sample of
patients/subjects
• Step 8. Allocate individuals into:
A. Experimental (study group)
• group that will receive a drug, vaccine or other
procedure
B. Control group
• group that will receive no treatment, a
placebo, or standard form of therapy

• Random allocation of the subjects in to experimental and control group is
important
Advantages of randomization:
• It eliminates selection bias
• On average the study groups will be comparable (confounders will be
equally distributed controls confounding effect )
Step 9. Collect data
• Collect all relevant information including the outcome
• The knowledge of participant's treatment status might influence the
identification or reporting of relevant events.
• This can be overcome by the use of placebo.

• Placebo - is an inert agent indistinguishable from the active treatment
• Placebo effect - is the tendency of individuals to report favorable response
to any therapy regardless of the physiologic efficacy of what they received
• The quality of gold standard in intervention studies can be achieved
through randomization, use of placebo and blinding (single, double or
triple blinding can be used as needed)
• Double -blind design (study subjects and health care giver do not know
who is getting the active intervention) is to eliminate the potential for
observation bias. Of course, a concomitant limitation is that such trials are
usually more complex and difficult to conduct.

• Triple blind trial is where the study subject, the field
investigator and the health care provider do not
know who is receiving the active treatment.
• This is even more complex than the double blind
study and requires complicated procedures to
safeguard the safety of study subjects.
Step 10. Analyze the results
• Analysis is similar to cohort study
Step 11. Publish/ disseminate findings

MEASURES OF ASSOCIATION
• Epidemiologic data are often presented in the
form of two-by-two (contingency) table
• 2X2 table contains 4 cells  a, b, c, and d
• Contingency table_is used to determine
whether the distribution of one variable is
conditionally dependent (contingent) up on
the other

Measures cont…
E
X
P
O
S
U
R
E
Disease
Yes No Total
Yes a b a+b
No c d c+d
Total a+c b+d a+b+c+d
a = Number of individuals who are exposed and have the disease
b = Number of individuals who are exposed but do not have the disease
c = Number of individuals who are not exposed but have the disease
d = Number of individuals who are not exposed and do not have the disease
a+b = the total number of individuals exposed
c+d = the total number of individuals who are not exposed
a+c = the total number of individuals with the disease
b+d = the total number of individuals without the disease
a+b+c+d = total sample size of the study

• Statistical tests like Chi-square show mainly the presence or
absence of association.
• The strength of association is assessed by calculating Relative
Risk (RR), Odds Ratio (OR) or other measures of association.
• Strength of association: The degree to which variation in one
variable explains the variation in another
• The greater the strength of association between variables ,
the more completely variation in one predicts variation in the
other.

A. Relative Risk (RR) or Risk Ratio
• RR shows the magnitude of association
between exposure & disease
• RR is the ratio of the risk in the exposed group
to the risk in the un exposed group , which is
expressed as Risk exposed/ Risk unexposed

Indicates the likelihood of developing the disease in exposed group relative to those who are not exposed
RR can also be used to compare risks of death, injury, and other possible outcomes of the exposure
Incidence among exposed (Ie)
RR =
Incidence among non-exposed (Io)
a
= (a + b)
c
(c+d)

OC
Use
Bacteruria
Yes No Total
Yes 27 455 482
No 77 1831 1908
Total 104 2286 2390
Calculate RR
RR =Ie/Io Ie = 27
482
Io = 77
1908
= 1.4

• Interpretation: women who used oral contraceptive
had 1.4 times higher risk of developing bacteruria
when compared to non-users.
• In general the strength of association can be
considered:
• High - if the RR is 3.0 or more
• Moderate – if the RR is from 1.5 to 2.9
• Weak – if the RR is from 1.2 to 1.4

B.Odds Ratio (OR)
• In case control studies, it is usually not possible to
calculate the rate of development of disease in the
exposed and non-exposed group.
• Hence, it is difficult to calculate the RR.
• The RR can be estimated, however, by calculating the
ratio of the odds of exposure among the cases to
that among the controls i.e the OR

OR = a/c = ad
b/d bc
Example: : This table shows data from case control study of oral contraceptive (OC) use & myocardial infarction in pre-menopausal
female nurses
Current
OC
Use
Myocardial infarction
Yes No Total
Yes 23 304 327
No 133 2816 2949
Total 156 3120 3276
Calculate OR
OR = ad = (23) (2816) = 1.6
bc (304) (133)
Interpretation: Women who were current OC users had 1.6 times higher risk of developing myocardial
infarction when compared to non-users of OC

RR can be estimated by OR if the following conditions are fulfilled:
• The controls are representative of the general population
• The selected cases are representative of all cases
• The disease is rare
C. Attributable Risk (AR) / Risk Difference (RD)
• AR is a measure of association that provides information about the
absolute effect of the exposure or the excess risk of disease in those
exposed compared with those who are not exposed.
• AR = Incidence among exposed (Ie) minus Incidence among non-
exposed (Io)
• AR is used to quantify the risk of disease in the exposed group that can
be considered attributable to the exposure by removing the risk of
disease that would have occurred anyway due to other causes.

Example: Refer to the previous table of Case Control study on OC users and Bacteruria
to calculate AR
AR = 27 _ - 77
482 1908
=0.0156=1566 per 100,000 OC users
• Interpretation: The excess occurrence of bacteruria among
OC users attributable to their OC use is 1566 per 100,000 OC
users
•  In a population of 100,000 OC users, 5602 would be
expected to develop bacteruria, 1566 of those who developed
bacteruria being related to OC use & the remainder, 4036, to
other factors

D. Attributable Risk Percent (AR %)
• Estimates the proportion of the disease among the exposed that is
attributable to the exposure, or the proportion of the disease in the
exposed group that could be prevented by eliminating the exposure
AR % = (Ie - Io) X 100
Ie
Example: From the above Table on OC users and bacterurai we can calculate
AR% as follows
AR % =1566/105 X 100 =27.96 %
27/482
Interpretation: If OC use causes bacteruria, about 28 % of bacteruria among
women who use OC can be attributed to their OC use and can be
eliminated if they did not use oral contraceptives.

E. Population Attributable Risk (PAR)
• Public health planners want to be able to anticipate the effect of
eliminating the exposure on the population as a whole, rather than just on
the exposed part of the population.
• Even if the RR is very high, eliminating a very rare exposure would not be
expected to have much impact on the health of the population as a whole.
• PAR takes into account not only the actual incidence rate of the outcome
but also the prevalence rate of the exposure
• PAR = AR X prevalence rate of the exposure

Example: Research was conducted to assess the association between cigarette
smoking and death from lung cancer. The following findings were obtained:
AR = 89 per 100,000 per year
Prevalence rate of cigarette smoking = 20 %
Calculate PAR.
PAR = 89 per 100,000 per year X 20 %
= 17.8 per 100,000 per year
Interpretation:
• In a population of 100,000 smokers, 89 deaths from lung cancer per year could
have been avoided by preventing them from smoking (this refers to AR)
In a general population of 100,000 with a prevalence rate of cigarette smoking of 20
%, about 18 deaths from lung cancer per year would be prevented by eliminating
cigarette smoking (this refers to PAR).

• Both AR and PAR are used to estimate the effect
on disease incidence of eliminating a given risk
factor, but while AR estimates reduction in disease
incidence only in those exposed, PAR estimates
reduction in disease incidence in the population as a
whole.
• The alternative formula for PAR is:
PAR = Incidence rate in total population minus
incidence rate in non-exposed population

F. Population Attributable Risk Percent (PAR %)
PAR % = PAR X 100
Incidence rate in total population
Example: PAR = 17.8 per 100,000 per year
Mortality rate in non-smokers = 7 per 105
• Mortality rate in the total population = 24.8 per 105 per year
Calculate PAR %
PAR % = 17.8 per 105 per year X100 =71.8%
24.8 per 105 per year
• Interpretation: 72% of deaths from lung cancer occurring in the general
population could be prevented by eliminating cigarette smoking.

POSSIBLE OUTCOMES IN STUDYING THE RELATIONSHIP BETWEEN DISEASE
AND EXPOSURE
1. No association between exposure and disease
AR=0, RR=1
2. Positive association between exposure and disease (more exposure, more
disease)
AR>0, RR>
3. Negative association between exposure and disease
(more exposure, less disease)
AR<0 (negative), RR <1(fraction)

Chapter 9.Evaluation of evidence
• The existence of an
association b/n
exposure and disease
does not in it self
constitute proof of
causation .what other
alternative explanation
for the association
,other than the cause –
effect relationship?
• 1.the association may
be the result of chance.
• 2.the association may
the result of bias.
• 3.the result may b/c of
a confounding
effect….etc

Evaluation
(accuracy)
• Accuracy = Validity + Precision

Accuracy
• Validity is the extent to which data collected actually
reflect the truth.
• The concepts of sensitivity (ability to detect true
positive) and specificity (ability to detect true
negatives) can be used to characterize the validity of
a measure ("measurement validity"). Study results
are also described as "valid" when there is no
systematic misrepresentation of effect or "bias"
("validity in the estimation of effect).

Accuracy …
• Precision, on the other hand, describes the
extent to which random error (i.e., sampling
variation and the statistical characteristics of
the estimator) alters the measurement of
effects.

Role of chance
Chance
• One of the alternative explanations to the observed
association between an exposure and a disease is
chance. Since the general aim of epidemiological
studies is to make generalization about a larger
group of individuals on the basis of a sample
population it is always important to evaluate the role
of chance or sampling variability in any study which
tries to elucidate association. Evaluation of the role
of chance is mainly the domain of statistics and it
involves:

Chance
. Hypothesis Testing (Test of Statistical Significance)
• Test of statistical significance quantifies the degree to which
sampling variability may account for the observed results. The
"P value" is used to indicate the probability or likelihood of
obtaining a result at least as extreme as that observed in a
study by chance alone, assuming that there is truly no
association between exposure and outcome under
consideration (i.e., H0 is true). For medical research, the P
value < 0.05 is set conventionally to indicate statistical
significant.

P-value
• P value is a function of:
• the magnitude of the difference between the groups
• sample size
• The fact implies that even a very small difference
may be statistically significant if the sample size is
sufficiently large, and a large difference may not
achieve statistical significance if variability is
substantial due to a small sample size. Hence, one
cannot make a definite decision about the role of a
factor based only on the P value.

P-value
• Steps in testing for statistical significance
1. Assume that the exposure is not related to disease -
state the null hypotheses.
2. Compute a measure of association - relative risk or
odd ratio.
3. Calculate chi-square statistical test of significance.
4. For the value of chi-square calculated, look up its
corresponding p –value in the table of chi-squares.

P-value
• * A very small p-value means that you are
very unlikely to observe such an association if
the null hypotheses is true.

Role of bias
• Bias may be defined as any systematic error in
an epidemiologic study that results in an
incorrect estimate of the association between
exposure and risk of disease.

Bias …cont
• Types of bias may be grouped into two broad
categories:
1) Selection bias refers to any error that arises in the
process of identifying the study populations.
Selection bias can occur whenever the identification
of individual subjects for inclusion in the study on
the basis of either exposure (cohort) or disease
(case-control) status depends in some way on the
other axis of interest.

Bias
• 2) Observation or information bias includes
any systematic error in the measurement of
information on exposure or outcome.

Some recommendations to minimize bias at
the time of study design are:
• 1) Choose study design carefully. If ethical and
feasible, a randomized double blind trial has the least
potential for bias. If loss to follow-up will not be
substantial, a prospective cohort study may have less
bias than a case-control study. Controls for case-
control studies should be maximally comparable to
cases except for the variable under study.

Minimize bias…
2) Choose "hard" (i.e., objective) rather than
subjective outcomes.
3) "blind" interviewers or examiners wherever
possible.
4) Use well-defined criteria for identifying a
"case" and use closed ended questions
whenever possible.

Cont..
• 5) Collect data on variables you do not expect
to differ between the two groups. If such a
"dummy" variable regarding exposure, for
example, in a case-control study shows an
unexpected difference, it may alert you to
recall bias.

Role of confounding
Confounding
• Confounding is the mixing of the effect of an
extraneous variable with the effects of the
exposure and disease of interest.

Cont…
• or
• Confounding is distortion of the estimated
effect of an exposure on an outcome, caused
by the presence of an extraneous factor
associated both with the exposure and the
outcome.

Effect of Confounding
• Without prior knowledge of the effect of the variable
on the outcome and exposure it is very difficult to
predict the direction of effect of a suspected
confounding variable. However, the effect could be
categorized into three:
1. Totally or partially accounts for the apparent effect
2. Mask an underlying true association
3. Reverse the actual direction of the association

Control for Confounding Variables
In the design confounding could be minimized
by:
• Randomization
• Restriction
• Matching

Restriction
• Individual who fall within a specific category
or categories of the confounder will be in
included in the study. e.g if smoking is a
potential confounding factor, either smokers
only or non smokers only will be included in
study.

Matching
• The particular subjects are in such away that
the potential confounders are distributed in
an identical manner among each of the study
groups.

Criteria to assess the strength of evidence for
a cause and effect relationship.
• In the absence of experimental evidence, the
following criteria (called the Bradford-Hill
criteria) are used to assess the strength of
evidence for a cause-and-effect relationship.
1. Strength of the Association - The stronger the
association, the more likely that it is causal.

Cont…
• 2. Consistency of the Relationship - The same
association should be demonstrable in studies
with different methods, conducted by
different investigators, and in different
populations.

Cont…
3. Specificity of the Association - The
association is more likely causal if a single
exposure is linked to a single disease.
4. Temporal Relationship - The exposure to the
factor must precede the onset of the disease.

Cont…
5. Dose-response Relationship - The risk of
disease often increases with increasing
exposure to a causal agent.
6. Biological Plausibility - The hypothesis for
causation should be coherent with what is
known about the biology and the descriptive
epidemiology of the disease.

Cont…
7.prevention elimination of the exposure should
be followed by decrease in the incidence rate
of the disease.
• The above criteria are the ones most
frequently employed in trying to establish
causation. No one provides in itself a perfect
means of providing causation, and each has its
limitation.

Chapter 10 :EPIDEMIC INVESTIGATION
AND MANAGEMENT
LEVEL OF DISEASE OCCURRENCE
DISAESE OCCUR IN THE COMMUNITY at
different levels at a particular point in time,
this is called the expected level , but
sometimes they occur in excess of what is
expected.

Level of disease occurrence
• Disease occurring at expected levels may
described as:
• Endemic: the presence of disease at more or
less stable level.
• Hyper endemic: a persistently high level of
disease occurrence.
• Sporadic: occasional or irregular occurrence of
disease.

Epidemic
• Disease occurring in excess of what is
expected is may described as:
• Epidemic: this the occurrence of heath related
condition/disease in excess of the usual
frequency in a given area or among a specific
group of people over a particular period of
time.

Cont…
• Out break: this is an epidemic of shorter
duration covering a limited area.
• Cluster: this is an aggregation of cases in a
given area over a particular period without
regard to whether the number of cases is
more than expected.
• Pandemic: this is an epidemic involving
several countries or continents affecting a
large number of people.

PATTERNS OF EPIDEMICS.
• Two principal types are well recognized. These
are the common source and
propagated/progressive.
• The two types can be distinguished by
plotting an epidemic curve. An epidemic
which shows the features of both types is
referred as mixed.

Common source epidemics
• Common source epidemics are caused by
exposure of a group of people to a common
noxious influence, such as an infectious agent
or a toxin. If the exposure is brief and
simultaneous all exposed will develop the
disease within one incubation period -
referred as point, or point source
epidemic/outbreak . A rapid rise and fall of an
epidemic curve suggests a point source
epidemic.

Cont…
• If the source of an outbreak remains for a
longer time, days, weeks or longer either
continuously or intermittently, there will be
multiple exposures with variable incubation
period, this will make an epidemic curve with
no clear peak and the duration of the
outbreak will be prolonged.

Cont…
Continuous common source - makes wide peak
in the epidemic curve, because of the range of
exposures and range of incubation periods.
Intermittent common source - results in an
irregular pattern of the epidemic curve that
reflects the intermittent nature of the
exposure.

Propagated or progressive epidemics
• Outbreak of this type can occur through direct
person-to-person transmission or the transmission
could pass through a vector from infected to healthy
person.
• The epidemic curve would have a successive series of
peaks reflecting increasing numbers of cases in each
generation. The epidemic usually wanes after a few
generations, either because the number of
susceptible falls below some critical level, or because
intervention measures become effective.

. Mixed Epidemics
• Epidemics having the features of both
common source and propagated epidemics
are referred as mixed epidemics. For example
a common source outbreak may be followed
by secondary person-to-person spread.

Steps of an Epidemic Investigation
• There is no rigid step to follow during investigation of
an outbreak. Several activities could be accomplished
simultaneously. The steps to follow are set by the
individual investigator depending on the suspected
cause of the outbreak. Verification of the diagnosis
and establishment of the existence of
an epidemic are commonly among the first steps.

1. Prepare for field work
Before leaving for the field an investigator must be well
prepared to under take the investigation.
Preparations can be categorized into three:
• 1.Investigation related: Investigator must have the
appropriate scientific knowledge, supplies, and
equipment to carry out the investigation. Discuss the
situation with knowledgeable people, review
applicable literature, and collect sample
questionnaire.

Steps …
• 2. Administration related: No matter there is
urgency in handling the situation, it is useful
to observe all administrative procedures. This
include arrangement of transportation and
organizing personnel matters.

Steps…
• 3.Consultation: clarify your and your team
role in the field. Identify local contacts at the
site where the outbreak is reported and
arrange where and when to meet them.

2. Verify the existence of an epidemic
• Compare the current number of cases (or incidence)
with the past levels of disease in that community,
considering the seasonal variation in the occurrence
of the disease, to determine whether an excessive
number of cases have occurred, i.e., compare the
observed number of cases (reported as outbreak)
with the expected number of cases in the area.

Note
• Be careful, excess may not always indicate an
outbreak. The excess may be due to changes
in local reporting procedures, change in case
definition, increased interest because of local
or national awareness, or improvements in
diagnostic procedures.

3.Verify the diagnosis
• Review the clinical and laboratory findings of the
cases to establish the diagnosis. This is to ensure that
the problem has been properly diagnosed and to rule
out laboratory error as the basis for the increase in
diagnosis.
• Case definition is a standard set of criteria for
deciding whether an individual should be classified
as having the health condition of interest.

Case definition …cont
• Confirmed/definite: a case with laboratory
verification.
• Probable : a case with typical clinical features
of the disease without lab. Verification.
• Possible : a case presented with fewer of the
typical clinical features.

Case defn…
• Surveillance - identifying and counting cases.

4. Describe the epidemic with respect to
time, place, person
• Collect relevant information related to the
investigation. Information could be obtained from
the already existing records or you can obtain using a
case investigation form specifically designed for a
particular situation under investigation. Information
must be collected carefully, so that, at the end they
will enable the investigator to characterize the
outbreak with respect to time, place and person.

Describe….
• By using well established descriptive
epidemiological tools, such as the epidemic
curve and spot mapping, an outbreak can be
characterized by time, place and person.

Describe…
• Epidemic curve- plots the cases by the time of
onset and provides a time frame for the
outbreak investigation.
• Spot map- plots the cases by location and
shows the geographic spread of cases.

Cont…
• Attack rates- Calculate rates of illness in
population at risk by exposure to specific
suspected items and other relevant attributes.

5.Formulate and Test Hypotheses
• Formulate the hypotheses based on your
characterization of the epidemic by time,
place, and person. The hypotheses should
address the source of the agent, the mode of
transmission, and the exposures that caused
the disease.

Test Hypotheses…
• In an outbreak investigation, evaluation of
hypotheses can be done in two ways: either
by comparing the hypotheses with the
established fact, or by using analytic
epidemiology to quantify relationships and
explore the role of chance.

6.search for additional cases:
Locate unrecognized or unreported cases.
• Passive: inquire physicians or hospitals or
both whether they have seen similar cases.
• Active: do intensive investigation in the
community on asymptomatic persons or
contacts of the cases.

7.Analyze the Data
. Assemble all results.
. Interpret findings.
*8. Make a decision on the hypotheses tested.
• . All the findings must be consistent with one,
and only one, hypotheses.

Cont…
9. Intervention and follow-UP
10. Report of the investigation
The report should follow the usual scientific
format: introduction, background, methods,
results, discussion, and recommendations.

Managing Outbreak/epidemics
• Management of epidemics require an urgent
and intelligent use of appropriate measures
against the spread of the disease. Action to be
taken is dependent on the type of the disease
as well as the source of the outbreak , but the
following steps are commonly used.

1. Measures Directed Against the
Reservoir
• Understanding the nature of the reservoir is
necessary in the selection of an appropriate
control methods and their likelihood of
success.
• The following are examples of control
measures against disease with varies reservoir
:

Domestic animals as reservoir:
• . Immunization
• . testing of herds
• . destruction of infected animals
.Example : brucellosis and bovine tuberculosis.

Wild animals as reservoir:
• . post-exposure prophylaxis
• Example : rabies

Humans as reservoir
• • removal of the focus of infection- e.g.,
cholecystectomy in a chronic typhoid carrier.
• • Isolation of infected persons.
Not suitable in the control of diseases in which a large
proportion are in apparent infection or in which
maximal infectivity precedes overt illness.
• • Treatment to make them non-infectious: e.g.,
tuberculosis.
• • Disinfection of contaminated objects.

2. Measures that interrupt the
transmission of organisms
• * Action to prevent transmission of disease by
ingestion:
. purification of water
. pasteurization of milk
. inspection procedures designed to ensure safe
food supply.
. improve housing conditions.

Cont…
• Attempts to reduce transmission of
respiratory infections
• . chemical disinfection of air and use of
ultraviolet light. e.g tb
• Action to interrupt transmission of diseases
whose cycles involve an intermediate host
E.g. clearing irrigation farms from snails to
control schistosomiasis.

3.Measures that reduce host susceptibility
• * Active immunization, when either the altered
organism or its product is given to a person to induce
production of antibodies - EPI.
• * Passive immunization, has lesser role in the control
of communicable diseases than active immunization:
• • Transfer of maternal antibodies to the fetus
through the placenta. IgG

Passive immunization cont…
• • Prophylaxis administration of immune serum
globulin (ISG). E.g., TAT for un-immunized persons
who with penetrating wound.
• • Chemoprophylaxis:
• use of antibiotics for known contacts of cases- for
example, in tuberculosis, gonorrhea, and syphilis.
• use of chlorquine to persons traveling to malaria
endemic areas.

Chapter 11. EPIDEMIOLOGIC
SURVEILLANCE
• Surveillance- a French word which means
watching with attention .
• Epidemiologic Surveillance is the systematic
collection, analysis, interpretation and
dissemination of health data in an ongoing
basis.

Surveillance cont…
• Surveillance provides "information for action"
which can be used to investigate, prevent, and
control disease in communities. Its purpose is
to provide a factual basis for setting priorities,
planning programs, and taking action to
promote and protect community health.

We monitor health events for the following
purposes:
• • To detect sudden changes in disease occurrence and
distribution (determines the need for epidemic investigation
and control) and to ensure that effective action to control the
disease is being done.
• • To follow secular (long-term) trends and patterns of disease
(alerts decision makers of the need to reallocate resources or
shift policy)
• • To identify changes in agents and host factors (helps to
assess the potential for future disease occurrence)
• • To detect changes in health care practices (points up the
need for changes in preventive measures)

Types of Surveillance
1. Passive surveillance is that in which health
care providers send reports based on a known
set of rules and regulations.

Cont…
• Active surveillance is that in which public
health officials contact providers to solicit
reports of events or diseases. Such active
surveillance is usually limited to specific
diseases over a limited period of time, such as
after a community exposure or during an
epidemic.

Sources of data for surveillance
• 1.mortality registration
• 2.morbidity registration
• 3.Epidemic reporting
• 4.Report of lab. Utilization
• 5.Report of epidemic field investigation
• 6.Special survey, etc

Activities in surveillance:
. Data collection and recording
• Reporting and notification
• Compilation, data analysis, and
interpretation
• Dissemination of findings for action

Factors related with the selection of disease
for surveillance
• Magnitude of the disease
• Feasibility of control measures
• Need for monitoring and evaluating the
performance of a control program
• Resource availability

Conditions in which active surveillance is
appropriate:
• For periodic evaluation of ongoing programs .
E.g. HIV/AIDS, EPI,...
• For programs which have time limit of
operation . E.g. Small pox
• With the occurrence of unusual situations.

Features of good surveillance system
• Uses a combination of passive and active
mechanisms to collect data.
. Emphasize the collection of minimum data in a
simplest possible way.
. To assure quality and enhance compliance
make sure that the data collected is useful for
the workers who collect the data.

Good surveillance cont…
• Timely reporting.
• Timely and comprehensive action.
*Action must be targeted towards
both case detection and treatment
and as well as to the control of the disease.
• Strong laboratory services for accurate
diagnosis.

Limitations of surveillance
• Surveillance systems are never perfect.
Understanding the limitations of surveillance
data is important to ensure correct
interpretation. The most common limitations
of surveillance systems include:

Limitation cont…
• 1) Under reporting (such as due to lack of knowledge
of reporting requirements, negative attitudes toward
reporting)
• 2) Lack of representative ness of reported cases
(such as due to a bias toward reporting severe cases,
or increased likelihood of reporting after publicity)
• 3) Lack of timeliness
• 4) Inconsistency of case-definitions

The integrated disease surveillance system
Integrated Disease Surveillance and Response (IDSR):
Concept and Experience in Ethiopia
• Integrated disease surveillance and response (IDSR)
is an approach adapted to strengthen national
disease surveillance systems by coordinating and
streamlining all surveillance activities and ensuring
timely provision of surveillance data to all disease
prevention and control programmes in order to
initiate timely response (intervention).

IDSR…
• The integrated disease surveillance strategy
recommends coordination and integration of
surveillance activities for disease of public
health importance .The diseases are listed
below.
.cholera, yellow fever, dracunculiasis,
measles, meningitis, tetanus, plague, ..

Cont…
..Viral hemorrhagic fever, malaria, diarrhea,
AIDS, STI, onchocerciasis, TF, RF, TYPHUS,
pneumonia in children, leprosy, TB.

Chapter 12: Screening: Program and
Evaluation
Objectives
At the end of this chapter the student is expected to:
Define screening
Identify diseases appropriate for screening
Know the mechanisms of determining the validity of screening tests
Discuss the criteria for establishing screening program
Describe how to evaluation screening programs

Screening …
Definition
• Screening is the search for unrecognized disease or
defect by means of rapidly applied tests,
examinations or other procedures in apparently
healthy individuals.
• A screening test is not intended to be diagnostic.
• Screening is an initial examination only, and positive
responders require a second, diagnostic examination

Screening …
Diseases Appropriate for Screening
To be appropriate for screening:
• A disease should be serious
• Treatment given before symptoms develop should be more
beneficial in terms of reducing morbidity or mortality than
that given after they develop
• The prevalence of preclinical disease should be high among
the population screened

Screening …
Criteria for establishing screening program
1.The condition sought should be an important health problem.
2. Screening should be undertaken only when it has the potential to lead to a
significant decrease in rates of disability or death or both
3.There should be an accepted treatment for patients with recognized disease
4.Facilities for diagnosis and treatment should be available
5. There should be a recognized latent or early symptomatic stage
6. There should be a suitable test or examination which has high validity as
measured by its sensitivity and specificity
7. The test should be acceptable to the population

Screening …
7. The natural history of the condition, including development from latent to
declared disease, should be adequately understood
8. The cost of case-finding (including diagnosis and treatment of patients
diagnosed) should be economically balanced in relation to possible
expenditure on medical care as a whole.
A cost effectiveness analysis should weigh the benefits of early detection
(in terms of decreased mortality) against the toll on available resources,
the risks, and the inconvenience of screening.
9. Case finding should be a continuous process and not a “once and for all”
project

Screening …
Screening Tests
• For a screening test to be successful a suitable screening test must be
available.
• A screening test should ideally be inexpensive, easy to administer, and
impose minimal discomfort on the patients.
• In addition the results of the screening test must be valid and reliable.
• In the belief that ‘prevention is better than cure’ there has been
widespread enthusiasm for screening of populations for illness in its early
stage, so that a better outcome can be achieved by more effective
intervention.

Screening …
Validity of a Screening Test
• Validity of a test is the ability to differentiate accurately
between those who have the disease and those who do not.
• Sensitivity and Specificity are two measures of the validity of a
screening test.
• Sensitivity and specificity can also be taken as measures of
validity for other tests which are applied for diagnostic
purposes.

Screening …
A. Sensitivity - is the ability of a test to identify correctly those
who have the disease
B. Specificity - is the ability of a test to identify correctly those
who do not have the disease
• Sensitivity= person with the disease who are positive by the
test divided by the total number of persons with the disease ,
multiplied by 100
• Specificity =persons without the disease who are negative by
the test divided by total number of persons without the
disease ,multiplied by 100.

Screening …
Sensitivity= TP/TP +FNX100
• Specificity= TN/TN+FPX100
Predictive Value of a Screening Test
• Predictive value is the ability of a test to predict the presence or absence
of disease from test results.
1. Predictive Value of a Positive Test (PVPT) or Positive Predictive Value
• PVPT shows the probability that the person tested positive by this
specific test truly has the disease.
PVPT = TP
TP + FP
2. Predictive Value of a Negative Test (PVNT) or Negative Predictive Value

Screening …
• PVNT Shows the degree of confidence the disease can be ruled out by using this
specific test.
TN
PVNT = X 100
TN+FN
OR
PVPT=TP/TP+FPX100
PVNT=TN/TN+FNX100
• The ability to predict the presence or absence of diseases from test results is
dependent on the prevalence of the disease in the population tested, as well as on
the sensitivity and specificity of the test.
• The higher the prevalence, the more likely it is that a positive test is predictive of
the diseases i.e PVPT will be high.

Screening …
Reliability (Precision)
• A reliable screening test is one that gives consistent results
when the test is performed more than once on the same
individual under the same conditions.
• Two major factors affect consistency of results: the variation
inherent in the method and observer variation (observer
error).
1. The variability of a method- depends on such factors as the
stability of the reagents used and fluctuation in the substance
being measured ( e.g in relation to meals, )

Screening …
2. Observer variation- can stem from differences among
observers (inter observer variation) and also from variation in
readings by the same observer on separate occasions (intra
observer variation).
These variations can usually be reduced by:
1. careful standardization of procedures
2. an intensive training period for all observers (or interviewers)
3. periodic checks on their work
4. the use of two or more observers making independent
observations.

Screening …
Evaluation of screening program
• Evaluation of a screening program involves consideration of two issues:
first, whether the program is feasible, and second, whether it is effective.
• Both must be considered carefully. No matter how effective a screening
procedure is in reducing subsequent morbidity and mortality,
• it will not be accepted if it can not be conducted efficiently, with minimal
inconvenience and discomfort, and at a reasonable cost.
• Conversely, the implementation of a screening program, no matter how
cost-effective, will not be warranted if it does not accomplish its goal of
reducing morbidity and mortality.

Screening …
Feasibility
• The feasibility of a screening program is determined by a number of
factors related to program performance, which measure the acceptability
of the program to the potential screenees, cost-effectiveness, the
subsequent diagnosis and treatment of individuals who test positive, and
the yield of cases.
• The acceptability of the program can be measured by factors such as the
number of persons examined and the proportion of the target population
that is screened.
• The costs of the screening program must be considered in terms of total
costs as well as with regard to resources expended per detected case of
the disease.

Screening …
• The successful screening program must also include
provision for follow up of persons whose screening
tests are positive.
• This can be measured by considering the proportions
of those with positive tests who are followed,
diagnosed, and treated.
• The yield of the screening program should be high.
Yield is the number of cases detected by the
screening program.

Screening …
Persons with the disease
Yield = detected by the test
X 100
Total screened
Yield=persons with the disease detected by the test divided by total screened,
multiplied by 100.
Yield=TP/TP+FN+TN+FPX100
• With respect to the yield, one measure that is commonly considered is the
predictive value of a screening test.
• The predictive value of a screening test is determined not only by factors
that determine validity of the test itself (i.e. sensitivity and specificity), but
also by the prevalence of preclinical disease.

Screening …
• The more sensitive a test, the less likely it is that an individual with a
negative test will have the disease and thus the greater the predictive
value negative.
• The more specific the test, the less likely an individual with a positive test
will be to be free from the disease and the greater the predictive value
positive.
Effectiveness
• The evaluation of the effectiveness of a screening program must be based
on measures that reflect the impact of a program on the course of a
disease.
• An effective screening program should result in reduction of morbidity,
mortality and disability.

Chapter 13. Epidemiology of selected
diseases based on their public health
importance
• Epidemiology of :
» EPI targeted diseases/ Poliomyelitis, Tuberculosis, Measles, etc..,
» ARI
» Diarrheal Diseases
» HIV/ AIDS/STI
» Malaria
» Schistosomiasis
» Leishmaniasis
» Onchocerciasis
» Human trypanosomiasis
» Yellow fever
» Relapsing fever
» Typhus
» Typhoid/enteric fever

Epidemiology ppt

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Epidemiology ppt