Chapter 3 Measures of Morbidity and Mortality Used in Epidemiology Learning Objectives • Define and distinguish among ratios, proportions, and rates • Explain the term population at risk • Identify and calculate commonly used rates for morbidity, mortality, and natality • State the meanings and applications of incidence rates and prevalence Learning Objectives (cont’d) • Discuss limitations of crude rates and alternative measures for crude rates • Apply direct and indirect methods to adjust rates • List situations where direct and indirect adjustment should be used Overview of Epidemiologic Measures Count • The simplest and most frequently performed quantitative measure in epidemiology. • Refers to the number of cases of a disease or other health phenomenon being studied. Examples of Counts • Cases of influenza reported in Westchester County, New York, during January of a particular year. • Traffic fatalities in Manhattan in a 24- hour time period • College dorm students who had mono • Foreign-born stomach cancer patients Ratio • The value obtained by dividing one quantity by another. • Consists of a numerator and a denominator. • The most general form has no specified relationship between numerator and denominator. • Rates, proportions, and percentages are also ratios. Example of a Simple Sex Ratio Calculation • A ratio may be expressed at = X/Y • Simple sex ratio (data from textbook) • Of 1,000 motorcycle fatalities, 950 victims are men and 50 are women. Number of male cases 950 Number of female cases 50 19:1 male to female= = Example of a Demographic Sex Ratio Calculation • This ratio refers to the number of males per 100 females. In the U.S., the sex ratio in 2010 for the entire population was 96.7, indicating more females than males. Number of male cases 151,781,326 Number of female cases 156,964,212 96.7X 100 = =X 100 Example of a Sex Ratio at Birth Calculation • The sex ratio at birth is defined as: (the number of male births divided by the number of female births) multiplied by 1,000. Number of male births Number of female births X 1,000 Definition of Proportion • A measure that states a count relative to the size of the group. • A ratio in which the numerator is part of the denominator. • May be expressed as a percentage. Uses of Proportions • Can demonstrate the magnitude of a problem. • Example: 10 dormitory students develop hepatitis. How important is this problem? – If only 20 students live in the dorm, 50% are ill. – If 500 students live in the dorm, 2% are ill. Example of a Proportion • Calculate the proportion of African- American male deaths among African- American and white boys aged 5 to 14 years. Rate • Definition: a ratio that consists of a numerator and a denominator and in which time forms part of the denominat ...

1. Chapter 3
Measures of Morbidity and
Mortality Used in
Epidemiology
Learning Objectives
• Define and distinguish among ratios,
proportions, and rates
• Explain the term population at risk
• Identify and calculate commonly used
rates for morbidity, mortality, and natality
• State the meanings and applications of
incidence rates and prevalence
Learning Objectives (cont’d)
• Discuss limitations of crude rates and

2. alternative measures for crude rates
• Apply direct and indirect methods to
adjust rates
• List situations where direct and indirect
adjustment should be used
Overview of Epidemiologic
Measures
Count
• The simplest and most frequently
performed quantitative measure in
epidemiology.
• Refers to the number of cases of a
disease or other health phenomenon
being studied.
Examples of Counts

3. • Cases of influenza reported in
Westchester County, New York,
during January of a particular year.
• Traffic fatalities in Manhattan in a 24-
hour time period
• College dorm students who had mono
• Foreign-born stomach cancer patients
Ratio
• The value obtained by dividing one
quantity by another.
• Consists of a numerator and a
denominator.
• The most general form has no specified
relationship between numerator and
denominator.
• Rates, proportions, and percentages are
also ratios.

4. Example of a
Simple Sex Ratio Calculation
• A ratio may be expressed at = X/Y
• Simple sex ratio (data from textbook)
• Of 1,000 motorcycle fatalities, 950 victims
are men and 50 are women.
Number of male cases 950
Number of female cases 50
19:1 male to female= =
Example of a
Demographic Sex Ratio Calculation
• This ratio refers to the number of
males per 100 females. In the U.S.,
the sex ratio in 2010 for the entire
population was 96.7, indicating more
females than males.
Number of male cases 151,781,326

5. Number of female cases 156,964,212
96.7X 100 = =X 100
Example of a
Sex Ratio at Birth Calculation
• The sex ratio at birth is defined as:
(the number of male births divided by
the number of female births)
multiplied by 1,000.
Number of male births
Number of female births
X 1,000
Definition of Proportion
• A measure that states a count relative
to the size of the group.
• A ratio in which the numerator is part
of the denominator.

6. • May be expressed as a percentage.
Uses of Proportions
• Can demonstrate the magnitude of a
problem.
• Example: 10 dormitory students
develop hepatitis. How important is
this problem?
– If only 20 students live in the dorm, 50%
are ill.
– If 500 students live in the dorm, 2% are
ill.
Example of a Proportion
• Calculate the proportion of African-
American male deaths among African-
American and white boys aged 5 to 14
years.

7. Rate
• Definition: a ratio that consists of a
numerator and a denominator and in
which time forms part of the denominator.
• Contains the following elements:
– disease frequency
– unit size of population
– time period during which an event occurs
Crude death rate =
Number of deaths in a given year
Reference population
(during the midpoint of the year
X 100,000
Example:
Number of deaths in the United States during 2007 = 2,423,712
Population of the U.S. as of July 1, 2007 = 301,621,157
2,423,712

8. 301,621,157
Crude death rate = = 803.6 per 100,000
Example of Rate Calculation
Definition of Prevalence
• The number of existing cases of a
disease or health condition in a
population at some designated
time.
Figure 3-1:
Analogy of
prevalence and
incidence. The
water flowing
down the waterfall
symbolizes
incidence and
water collecting in

9. the pool at the
base symbolizes
prevalence.
Source: Robert
Friis.
Interpretation of Prevalence
• Provides an indication of the extent
of a health problem.
– Example 1: Prevalence of diarrhea in a
children’s camp on July 13 was 15.
– Example 2: prevalence of obesity
among women aged 55-69 years was
367 per 1,000.
Uses of Prevalence
• Describing the burden of a health
problem in a population.

10. • Estimating the frequency of an
exposure.
• Determining allocation of health
resources such as facilities and
personnel.
Point Prevalence
Point Prevalence =
Number of persons ill
Total number in the group
at point in time
Example:
Total number of smokers in the group = 6,234
Total number in the group 41,837
or 14.9%
= 149.0 per 1,000
Period Prevalence = during a time period
Period Prevalence

11. Number of persons ill
Average population
Example:
Persons ever diagnosed with cancer = 2,293
Average population 41,837
= 5.5%
Definition of Incidence
• The number of new cases of a
disease that occur in a group during a
certain time period.
Incidence Rate (Cumulative
Incidence)
• Describes the rate of development of a
disease in a group over a certain time
period.
• Contains three elements:

12. – Numerator = the number of new cases.
– Denominator = the population at risk.
– Time = the period during which the cases
occur.
Example of Incidence Data
• Number of new cases of HIV
infection diagnosed in a population
in a given year: a total of 164 HIV
diagnoses were reported among
American Indians or Alaska natives
in the U.S. during 2009.
Incidence Rate Calculation
(IWHS Data)
Incidence rate =
Number of new cases
over a time period

13. Total population at risk
during the same time period
X multiplier (e.g., 100,000)
Number of new cases = 1,085
Population at risk = 37,105
Incidence rate =
1,085
37,105
= 0.02924/8 = 0.003655 x 100,000
= 365.5 cases per 100,000 women per year
Attack Rate (AR)
• Alternative form of incidence rate.
• Used for diseases observed in a
population for a short time period.
• Not a true rate because time dimension
often uncertain.
• Example: Salmonella gastroenteritis
outbreak

14. • Formula:
Ill
Ill + Well
AR = x 100 (during a time period)
Incidence Density
• An incidence measure used when
members of a population or study
group are under observation for
different lengths of time.
Number of new cases during the time period
Total person-time of observation
Incidence
density =
Number of new cases during the time period
Total person-years of observation
Incidence density =
If period of observation is measured in years, formula
becomes:

15. Formulas for Incidence Density
Incidence Density, Example
Interrelationship Between
Prevalence and Incidence
Interrelationship Between
Prevalence and Incidence (cont’d)
• If duration of disease is short and
incidence is high, prevalence becomes
similar to incidence.
• Short duration--cases recover rapidly or
are fatal.
• Example: common cold
Interrelationship Between
Prevalence and Incidence

16. (cont’d)
• If duration of disease is long and
incidence is low, prevalence
increases greatly relative to
incidence.
• Example: HIV/AIDS prevalence
Crude Rates, Measures of
Natality
• Crude birth rate
• Fertility rate
– General
– Total
• Infant mortality
rate
• Fetal death rate

17. • Neonatal mortality rate
• Postneonatal mortality
rate
• Perinatal mortality rate
• Maternal mortality rate
Crude Birth Rate
Crude Birth Rate =
Number of live births
within a given period
Population size at the
middle of that period
X 1,000
population
Sample calculation: 4,130,665 babies were born in the U.S.
during 2009, when the U.S. population was 307,006,550.
The birth rate was
4,130,665/307,006,550 = 13.5 per 1,000.

18. Used to project population changes; it is affected by the
number and age composition of women of childbearing
age
General Fertility Rate
General
fertility rate
=
# of live births
within a year
# of women
aged 15-44 yrs.
during the midpoint
of the year
X
1,000 women
aged 15-44
Sample calculation: During 2009, there were 61,948,144

19. women aged 15 to 44 in the U.S. There were 4,130,665 live
births. The general fertility rate was 4,130,665/61,948,144 =
66.7 per 1,000 women aged 15 to 44.
Used for comparisons of fertility among age, racial, and
socioeconomic groups.
Total Fertility Rate
• This rate is “[t]he average number of
children that would be born if all women
lived to the end of their childbearing years
and bore children according to a given set
of age-specific fertility rates.”
• In the United States, the total fertility rate
was 2.06 in 2012. This rate is close to
• The replacement fertility rate is 2.1.
Fetal Death Rate
Used to estimate the risk of death of the fetus associated

20. with the stages of gestation.
Fetal Death Ratio
Refers to the number of fetal deaths after gestation
of 20 weeks or more divided by the number of live
births during a year.
Fetal Death
Ratio =
Number of fetal deaths after
20 weeks or more gestation
Number of live births
X 1,000
(during a
year)
Infant Mortality Rate
Used for international comparisons; a high rate indicates
unmet health needs and poor environmental conditions.

21. Neonatal Mortality Rate
• Reflects events happening after birth,
primarily:
– Congenital malformations
– Prematurity (birth before gestation week
28)
Neonatal Mortality Rate
Formula
Postneonatal Mortality Rate
Measures risk of dying among older infants
during a given year.
Perinatal Mortality Rate
Reflects environmental events that occur during
pregnancy and after birth; it combines mortality during
the prenatal and postnatal periods.

22. Perinatal Mortality Ratio
Maternal Mortality Rate
Reflects health care access and socioeconomic
factors; it includes maternal deaths resulting from
causes associated with puerperium (period after
childbirth), eclampsia, and hemorrhage.
Crude Rates
• Use crude rates with caution when
comparing disease frequencies between
populations.
• Observed differences in crude rates may
be the result of systematic factors (e.g.,
sex or age distributions) within the
population rather than true variation in
rates.

23. Specific Rates
• Specific rates refer to a particular
subgroup of the population defined
in terms of race, age, sex, or single
cause of death or illness.
Cause-Specific Rate
Cause-specific mortality rate (age group 25-34) due to HIV in
2003 = 1,588/39,872,598 = 4.0 per 100,000
Example:
Proportional Mortality Ratio
(PMR) %
PMR (%) for HIV among the 25- to 34-year-old group
= 1,588/41,300 = 3.8%
Indicates relative importance of a specific cause of
death; not a measure of the risk of dying of a

24. particular cause.
Example:
Age-Specific Rate (Ri)
Method for Calculation of Age-
Specific Death Rates
Adjusted Rates
• Summary measures of the rate of
morbidity and mortality in a
population in which statistical
procedures have been applied to
remove the effect of differences in
composition of various populations.
Direct Method
• The direct method may be used if

25. age-specific death rates in a
population to be standardized are
known and a suitable standard
population is available.
New Standard Population
• Year 2000 population
– Replaces the standard based on 1940 population
– Results in age-adjusted death rates that are much
larger
– Affects trends in age-adjusted rates for certain
causes of death
– Narrows race differentials in age-adjusted death
rates
• Reduces the three different standards into
one acceptable standard
Direct Method for Adjustment of

26. Rates
Weighted Method for Direct Rate
Adjustment
Indirect Method
• Indirect method may be used if age-
specific death rates of the population for
standardization are unknown or unstable,
for example, because the rates to be
standardized are based on a small
population.
• The standardized mortality ratio (SMR)
can be used to evaluate the results of the
indirect method.
Standardized Mortality Ratio
(SMR)
Interpretation of SMR
• If the observed and expected numbers are
the same, the SMR would be 1.0,

27. indicating that observed mortality is not
unusual.
• An SMR of 2.0 means that the death rate
in the study population is two times greater
than expected.
Indirect Age Adjustment
(cont’d)
• From previous table, SMR is
(502/987.9) X 100 = 50.8%.
Chapter 2
Practical Applications of
Epidemiology
Learning Objectives

28. • Discuss uses and applications of
epidemiology
• Define the influence of population
dynamics on community health
• State how epidemiology may be used for
operations research
• Discuss the clinical applications of
epidemiology
• Cite causal mechanisms from the
epidemiologic perspective
Seven Uses for Epidemiology
• Health Status and Health Services
1. Study history of the health of populations
2. Diagnose the health of the community
3. Examine the working of health services
• Disease Etiology
1. Estimate the individual risks and chances
2. Identify syndromes
3. Complete the clinical picture
4. Search for causes

29. Health Status and Health
Services
• Describing the occurrence of disease in
the community
• Planning for allocation of resources
– Public health practitioners
– Administrators
• Evaluating programs, e.g., public health
service programs
Disease Etiology
• Epidemiologists continue to search
for clues as to the nature of disease.
• Knowledge that is acquired may be
helpful in efforts to prevent the
occurrence.
Historical Use of Epidemiology

30. • Refers to the study of past and future
trends in health and illness
• For example: Secular trends--
changes in disease frequency over
time
Examples of Trends
• Chronic diseases have replaced acute
infectious diseases as the major causes of
morbidity and mortality.
• In 2009, the leading causes of U.S. deaths
were heart disease, cancer, and chronic
lower respiratory disease.
• Increases were reported for Alzheimer’s
disease, kidney disease, and
hypertension.

31. Factors Affecting Reliability of
Observed Changes
• Lack of comparability over time due
to altered diagnostic criteria
• Aging of the general population
• Changes in the fatal course of the
condition
Four Trends in Disorders
• Disappearing
• Residual
• Persisting
• New epidemic
Disappearing Disorders
• This category refers to conditions that were
once common but are no longer present in
epidemic form.

32. • Examples include smallpox, poliomyelitis,
and measles.
• Brought under control by immunizations,
improvement in sanitary conditions, and the
use of antibiotics and other medications led
to eradication of these diseases
Residual Disorders
• Conditions for which the key contributing
factors are largely known
• Methods of control not implemented
effectively
• Examples:
– STDs
– Perinatal and infant mortality among low SES
persons
– Problems associated with alcohol and
tobacco use

33. Persisting Disorders
• Diseases for which there is no effective
method of prevention or no known cure
• Examples: certain types of cancer and
mental disorders
New Epidemic Disorders
• Diseases that are increasing in frequency
• Examples: Lung cancer, AIDS, Obesity,
Type 2 diabetes
• The emergence of new epidemics of
diseases may be a result of increased life
expectancy of the population, new
environmental exposures, or changes in
lifestyle, diet, and other practices.
Predictions About the Future

34. • A population pyramid represents the age
and sex composition of the population of
an area or country at a point in time.
• By examining the distribution of a
population by age and sex, one may view
the impact of mortality from acute and
chronic conditions.
Trends in the Age and Sex
Distributions
• Developing countries
– In 1950 and 1990, countries had a triangular
population distribution, which is associated
with high death rates from infections, high
birth rates, and other conditions.
– By 2030, improvements in health are likely to
result in greater survival of younger persons,
causing a projected change in the shape of

35. the population distribution.
Trends in the Age and Sex
Distributions
• Developed countries
– Manifest a rectangular population distribution
– Infections take a smaller toll and cause a
greater proportion of children to survive into
old age
– Residents enjoy greater life expectancy
– The population of developed countries will
grow increasingly older due to continuing
advances in medical care
Population Dynamics
• Denotes changes in the demographic
structure of populations associated
with such factors as births and deaths

36. and immigration and emigration
• Two types of populations
– Fixed populations
– Dynamic populations
Population Terms
• Fixed population
– Adds no new members and, as a result,
decreases in size due to deaths only
– Examples: survivors of the 9-11 terrorist
attack in New York, residents of New
Orleans during Hurricane Katrina, and
persons who had a medical procedure
such as hip replacement
Population Terms
• Dynamic population
– Adds new members through immigration

37. and births or loses members through
emigration and deaths
– Example: the population of a country,
city, or state in the United States
Influences on Population Size
• Three major factors affect the sizes of
population births, deaths, and
migration.
• Population in equilibrium or a steady
state
– The three factors do not contribute to
net increases or decreases in the
number of persons.
Influences on Population Size
• Population increasing in size
– The number of persons immigrating plus the
number of births exceeds the number of

38. persons emigrating plus the number of
deaths.
• Population decreasing in size
– The number of persons emigrating plus the
number of deaths exceeds the number of
persons immigrating plus the number of
births.
Demographic Transition
• Shift from high birth and death rates found in
agrarian societies to lower birth and death rates
found in developed countries.
Epidemiologic Transition
• Shift in the pattern of morbidity and mortality
from infectious and communicable diseases to
chronic, degenerative diseases.

39. Epidemiology and the Health of
the Community
• Provides a key to the types of
problems requiring attention
• Determines the need for specific
health services
Demographic and Social
Variables
• Age and sex distribution
• Socioeconomic status
• Family structure
• Racial, ethnic, and religious
composition
Variables Related to
Community Infrastructure
• Availability of social and health

40. services
• Quality of housing stock
• Social stability (residential mobility)
– Community policing
– Employment opportunities
Health-Related Outcome
Variables
• Homicide and suicide rates
• Infant mortality rate
• Chronic and infectious diseases
• Drug and alcohol abuse rates
• Teen pregnancy rates
• Sexually transmitted diseases
• Birth rate
Environmental variables
• Air pollution from stationary and mobile sources

41. • Access to parks/recreational facilities
• Availability of clean water
• Availability of markers that supply healthful
groceries
• Number of liquor stores and fast-food outlets
• Nutritional quality of foods and beverages
vended to school-children
Health Disparities
• Healthy People 2010, Goal 2
– “ . . . To eliminate health disparities among
segments of the population, including
differences that occur by gender, race, or
ethnicity, . . .”
• Healthy People 2020
– “. . .To achieve health equity, eliminate
disparities, and improve the health of all
groups. . .”

42. Health Disparities
• Infant mortality in the U.S.
• Income inequality (Gini index)
– Ranges for 0 to 1
– The closer the index is to one, the greater is
the level of inequality.
• States with the highest Gini Scores:
Tennessee, Kentucky, and West Virginia
Epidemiology and Policy Evaluation
• Using epidemiologic methodologies to evaluate
public health policies
• Examples: tobacco control, needle distribution
programs, ban on plastic bags, printing of
nutritional content on restaurant menus,
removal of high fat and high sugar content
foods from vending machines in schools, and

43. prohibition of drivers’ use of cell phones
Working of Health Services
• Operations research (OR)
• Program evaluation
Operations Research (OR)
• The study of the placement and
optimum utilization of health services
in a community
• Contribution of epidemiology to OR is
the development of research designs,
analytic techniques, and
measurement procedures
Examples of OR
• Coordination of programs for the
developmentally disabled

44. • Studies of health care utilization
• Residential care facilities
Program Evaluation
• Uses epidemiologic tools to
determine how well a health program
meets certain stated goals
Epidemiology and Program
Evaluation
• Methods for selecting target populations
• Design of instruments for data collection
• Delimitation of types of health-related data
• Methods for assessment of healthcare
needs
Epidemiology and Disease
Etiology

45. • Applications include:
–Search for causes
–Individual risks
–Specific clinical concerns
Causality in Epidemiologic
Research
• Epidemiologic research is the subject
of criticism.
• Many conflicting studies
• Henle-Koch postulates are not
relevant to many contemporary
diseases.
• Multivariate causality
Risk Factors Defined
• Due to the uncertainty of “causal”
factors the term risk factor is used.
• Definition: exposure that is associated

46. with a disease
• Example of a risk factor: smoking.
Risk Factors Defined (cont’d)
• Three Criteria for Risk Factors
– The frequency of the disease varies by
category or value of the factor, e.g., light
smokers vs. heavy smokers.
– The risk factor precedes onset of the
disease.
– The observation must not be due to
error.
Modern Concepts of Causality:
1964 Surgeon General’s Report
• Five criteria for causality
– Strength of association
– Time sequence

47. – Consistency upon repetition
– Specificity
– Coherence of explanation
Modern Concepts of Causality:
Sir Austin Bradford Hill
• Hill expanded the list of criteria to
include:
– Biologic gradient
– Plausibility
– Experiment
– Analogy
Study of Risks to Individuals
• Etiologic study designs used
• Case-control
• Cohort

48. Case-Control Design
• A type of design that compares persons
who have a disease (cases) with those
who are free from the disease (controls).
• This design explores whether
differences between cases and controls
result from exposures to risk factors.
Cohort Design
• A group of people free from a disease is
assembled according to a variety of
exposures.
• The group (cohort) is followed over a
period of time for development of
disease.
How Results Impact Clinical
Decisions

49. • The following considerations
determine a study’s influence:
– Criteria of causality
– Relevance to each patient
• Size of the risk
– Public health implications
• Individual vs. population
Enlargement of the Clinical
Picture of Disease
• Cases of a new disease often the
most dramatic cases
• Need to survey a complete population
• Example of a “new” disease—
Legionnaires’ disease
Prevention of Disease
• Research is applied to identify where in a
disease’s natural history effective
intervention might be implemented.

50. • The natural history of disease refers to the
course of disease from its beginning to its
final clinical end points.
Natural History of Disease
• Prepathogenesis--before agent
reacts with host
• Pathogenesis--after agent reacts
with host
• Later stages include development of
active signs and symptoms.
– Clinical end points are: recovery,
disability, or death.
Primary Prevention as a
General Concept
• Occurs during prepathogenesis
phase
• Includes health promotion and

51. specific protection against diseases
Primordial Prevention
• Concerned with minimizing health
hazards in general
• Examples include improvement of:
– Economic conditions
– Social conditions
– Behavioral conditions
– Cultural patterns of living
Primary Prevention as a
Specific Concept
• Involves specific protection against
disease-causing hazards
• Examples:
– Utilization of specific dietary supplements
– Immunizations

52. – Educational campaigns against unintentional
injuries
Primary Prevention: Active and
Passive• Active
– Necessitates behavior change on the part of
the subject
– Examples: Vaccinations and wearing
protective devices
• Passive
– Does not require any behavior change
– Examples: Fluoridation of public water and
vitamin fortifications of milk and bread
products
Secondary Prevention
• Occurs during pathogenesis phase
• Designed to reduce the progress of

53. disease
• Examples are screening programs for
cancer and diabetes.
Tertiary Prevention
• Takes place during late pathogenesis
• Designed to limit disability from disease
• Also directed at restoring optimal
functioning (rehabilitation)
• Examples include: physical therapy for
stroke patients, halfway houses for alcohol
abuse recovery, and fitness programs for
heart attack patients.
Chapter 1
The History and Scope of Epidemiology
Learning Objectives

54. • Define the term epidemiology
• Define the components of epidemiology (determinants,
distribution, morbidity, and mortality)
• Name and describe characteristics of the epidemiologic
approach
• Discuss the importance of Hippocrates’ hypothesis and
how it differed from the common beliefs of the time
• Discuss Graunt’s contributions to biostatistics and how
they affected modern epidemiology
• Explain what is meant by the term natural experiments,
and give at least one example
2009 H1N1 Influenza
• During April 2009, 2 cases of 2009 H1N1
came to the attention of CDC.
• The initial cases occurred in the U.S. and
then expanded rapidly worldwide.
• By summer 2010, the epidemic subsided
and an estimated 60 million cases had
occurred in the U.S.

55. • Heavily affected people were from 18 to
64 years old. See Exhibit 1-1.
2006 Outbreak of Escherichia coli
• Outbreak during late summer and fall of 2006
• Affected 199 persons and caused 3 deaths
• Caused 102 (51%) of ill persons to be
hospitalized
• A total of 31 patients (16%) were afflicted with
hemolytic-uremic syndrome (HUS).
• Spread across 26 states
• Fresh spinach linked to the outbreak
Epidemiology Defined
• Epidemiology derives from "epidemic," a
term which provides an immediate clue to
its subject matter. Epidemiology originates

56. from the Greek words, epi (upon) + demos
(people) + logy (study of).
Definition of Epidemiology
• Epidemiology is concerned with the
distribution and determinants of health and
diseases, morbidity, injuries, disability, and
mortality in populations.
• Epidemiologic studies are applied to the
control of health problems in populations.
Key Aspects of This Definition
• Determinants
• Distribution
• Population
• Health phenomena
• Morbidity and mortality

57. Determinants
• Factors or events that are capable
of bringing about a change in health.
Examples of Determinants
• Biologic agents--bacteria
• Chemical agents--carcinogens
• Less specific factors--stress, drinking,
sedentary lifestyle, or high-fat diet
The Search for Determinants
• Outbreak of Fear--Ebola virus in Kikwit,
Zaire
• Fear on Seventh Ave.--Legionnaires’
disease in New York City
• Red Spots on Airline Flight Attendants--
dye from life vests
• Bioterrorism-Associated Anthrax Cases

58. Bioterrorism-Associated
Anthrax Cases
• Index case reported in Florida
• Additional cases, including fatal cases,
reported in New York, New Jersey,
Connecticut
• Contaminated mail linked to some of the
cases
Distribution
• Frequency of disease occurrence
may vary from one population group
to another.
Disease Distribution Examples
• In 2006, death rates from CHD and stroke
were higher among African-Americans
than among American Indians/Alaskan

59. natives, Asian/Pacific Islanders, or whites.
• Coronary heart disease occurrence differs
between Hispanics and non-Hispanics.
Population
• Epidemiology examines disease
occurrence among population groups,
not individuals.
• Epidemiology is often referred to as
population medicine.
• The epidemiologic description indicates
variation by age groups, time,
geographic location, and other variables.
Health Phenomena
• Epidemiology investigates many
different kinds of health outcomes:
– Infectious diseases

60. – Chronic diseases
– Disability, injury, limitation of activity
– Mortality
– Active life expectancy
– Mental illness, suicide, drug addiction
Morbidity and Mortality
• Morbidity--designates illness.
• Mortality--refers to deaths that occur in a
population or other group.
• Note that most measures of morbidity and
mortality are defined for specific types of
morbidity or causes of death.
Aims and Levels
• To describe the health status of
populations
• To explain the etiology of disease

61. • To predict the occurrence of disease
• To control the occurrence of disease
Foundations of Epidemiology
• Interdisciplinary
• Methods and procedures—quantification
• Use of special vocabulary
• Epidemic frequency of disease
Epidemiology Is Interdisciplinary
• Epidemiology is an interdisciplinary field
that draws from biostatistics and the social
and behavioral sciences, as well as from
the medically related fields of toxicology,
pathology, virology, genetics,
microbiology, and clinical medicine.

62. Quantification
• Quantification is a central activity of
epidemiology.
• Epidemiologic measures often require
counting the number of cases of disease.
• Disease distributions are examined
according to demographic variables such
as age, sex, race, and other variables,
such as exposure category and clinical
features.
Epidemic
• “The occurrence in a community or region
of cases of an illness (or an outbreak)
clearly in excess of expectancy…”
• Relative to usual frequency of the disease
Key Terms in “Epidemic”
• Communicable disease

63. – An illness caused by an infectious agent that
can be transmitted from one person to
another.
• Infectious disease
– A synonym for a communicable disease
• Outbreak
– A localized disease epidemic, e.g., in a town
or health care facility
Concept of Epidemic and Non-
Infectious Diseases
• Some examples that use the concept of an
epidemic are:
– Love Canal
– Red spots among airline flight attendants
– Toxic Shock Syndrome
– Brown lung disease
– Asbestosis among shipyard workers

64. – Diseases associated with lifestyle
Pandemic
• “ . . . an epidemic on a worldwide scale;
during a pandemic, large numbers of
persons may be affected and a disease
may cross international borders.” An
example is a flu pandemic.
Ascertainment of Epidemics
• Surveillance
• Epidemic threshold
Surveillance
• The systematic collection of data
pertaining to the occurrence of specific
diseases.
• Analysis and interpretation of these data.
• Dissemination of disease-related

65. information
• Common activities include monitoring food
born disease outbreaks and tracking
influenza.
Epidemic Threshold
• The minimum number of cases (or deaths)
that would support the conclusion than an
epidemic was underway.
• This is based on statistical projections.
• Figure1-6 demonstrates that the combined
pneumonia and influenza deaths peaked
substantially above the epidemic threshold
during early 2008, late 2009, and early
2011.
Historical Antecedents

66. • The Cholera Fountain
• Environment and disease
• The Black Death
• Use of mortality counts
• Smallpox vaccination
• Use of natural experiments
• William Farr
• Identification of specific agents of disease
• The 1918 influenza pandemic
The Cholera Fountain
Dresden, Germany
• Dresden, Germany, was spared from a
deadly cholera epidemic during 19th
Century.
• Mid 1800s--Residents constructed a
Cholera Fountain to express their gratitude
for escaping the cholera epidemic that

67. threatened the city.
The Environment
• Hippocrates wrote On Airs, Waters, and
Places in 400 BC.
• He suggested that disease might be
associated with the physical environment.
• This represented a movement away from
supernatural explanations of disease
causation.
The Black Death
• Occurred between 1346-1352.
• Claimed one-quarter to one-third of
population of Europe.
Use of Mortality Counts

68. • John Graunt, in 1662, published Natural
and Political Observations Made upon the
Bills of Mortality.
John Graunt’s Contributions
• Recorded seasonal variations in births and
deaths
• Showed excess male over female
differences in mortality
• Known as the “Columbus” of biostatistics
• See Yearly Mortality Bill for 1632: The 10
Leading Causes of Mortality in Graunt’s
Time.
Edward Jenner
• Jenner conducted an experiment to create
a smallpox vaccine.
• He developed a method for smallpox

69. vaccination.
• In 1978 smallpox was finally eliminated
worldwide.
• Since 1972, routine vaccination of the
nonmilitary population of the U.S. has
been discontinued.
Use of Natural Experiments
• John Snow was an English physician and
anesthesiologist.
• He investigated a cholera outbreak that
occurred during the mid-19th century in
Broad Street, Golden Square, London.
Snow’s Contributions
• Linked the cholera epidemic to
contaminated water supplies
• Used a spot map of cases and tabulation

70. of fatal attacks and deaths
Snow’s Natural Experiment
• Two different water companies supplied
water from the Thames River to houses
in the same area.
• The Lambeth Company moved its
source of water to a less polluted
portion of the river.
• Snow noted that during the next cholera
outbreak those served by the Lambeth
Company had fewer cases of cholera.
Natural Experiment
• Refers to “naturally occurring
circumstances in which subsets of the
population have different levels of
exposure to a supposed causal factor in
a situation resembling an actual
experiment, where human subjects
would be randomly allocated to groups.

71. The presence of persons in a particular
group is typically nonrandom.”
Ignaz Semmelweis
• Mid-19th century, Viennese hospital
– Clinical assistant in obstetrics and gynecology
– Observed higher mortality rate among the
women on the teaching wards for medical
students and physicians than on the teaching
wards for midwives
– Postulated that medical students and
physicians had contaminated their hands
during autopsies
– Introduced the practice of hand washing
William Farr
• Appointed compiler of abstracts in
England, 1839
• Provided foundation for classification of

72. diseases (ICD system)
• Used data such as census reports to study
occupational mortality in England
• Examined linkage between mortality rates
and population density
Koch's Postulates
• Microorganism must be observed in
every case of the disease
• Microorganism must be isolated and
grown in pure culture
• Pure culture must, when inoculated into
a susceptible animal, reproduce the
disease
• Microorganism must be observed in, and
recovered from, diseased animal
The 1918 Influenza Pandemic

73. • “The Mother of All Pandemics” and
Spanish Flu
• Occurred between 1918 and 1919
• Killed 50- to 100 million persons worldwide
• 2.5% case-fatality rate versus 0.1% for
other influenza pandemics
• Deaths most frequent among 20- to 40-
year-olds
Other Historical Developments
• Alexander Fleming discovered the
antimicrobial properties of the mold: led to
the discovery of the antibiotic penicillin.
• Alexander Langmuir established CDC’s
Epidemic Intelligence Service.
• Wade Hampton Frost was the first
professor of epidemiology in the U.S.
• Joseph Goldberger discovered the cure for

74. pellagra.
Recent Applications of
Epidemiology
• The Framingham Heart Study (ongoing
since 1948) investigates coronary heart
disease risk factors.
• Smoking and lung cancer; e.g., Doll and
Peto’s study of British doctors’ smoking
• AIDS, chemical spills, breast cancer
screening, second-hand cigarette smoke
• Association between HPV and cervical
cancer
Additional Applications of
Epidemiology
• Infectious diseases
– SARS, pandemic influenza 2009 H1N1,

75. Avian influenza
• Environmental health
• Chronic diseases
• Lifestyle and health promotion
• Psychological and social epidemiology
• Molecular and genetic epidemiology