assignment week 1 Managerial Epidemiology

 Managerial Epidemiology:   Week 1

Critical Reflection Paper: Chapters 1 to 3

Objective: To critically reflect your understanding of the readings and your ability to apply them to your Health care Setting. 

ASSIGNMENT GUIDELINES (10%):

Students will disapprovingly evaluate the readings from Chapter 1 to 3 in your textbook. This assignment is designed to help you assessment, inquiry, and apply the readings to your Health Care setting as well as become the foundation for all of your remaining assignments.

You need to read the article (in the additional weekly reading resources localize in the Syllabus and also in the Lectures link) assigned for week 1 and develop a 2 page paper reflecting your understanding and ability to apply the readings to your Health Care Setting. Each paper must be typewritten with 12-point font and double-spaced with standard margins. Follow APA format when referring to the selected articles and include a reference page.

  

EACH PAPER SHOULD INCLUDE THE   FOLLOWING:

1. Introduction (25%) Provide a short-lived outline of the denotation (not a description) of each Chapter and articles you read, in your own words.

2. Your Critique (50%)

What is your reaction to the content of the articles?

What did you absorb about the History and Scope of Epidemiology?

What did you acquire about the Practical applications of Epidemiology?

Did these Chapter and articles change your thoughts about the Measurement of mortality and Morbidity? If so, how? If not, what remained the same?

3. Conclusion (15%)

Fleetingly summarize your thoughts & deduction to your critique of the articles and Chapter you read. How did these articles and Chapters impact your thoughts on Patient Protection and Affordable Care Act?

Evaluation will be based on how clearly you respond to the above, in particular:

a) The clarity with which you critique the articles;

b) The depth, scope, and organization of your paper; and,

c) Your conclusions, including a description of the impact of these articles and Chapters on any Health Care Setting.

ASSIGNMENT DUE DATE:

The assignment is to be electronically posted no later than noon on Friday, January 17, 2020. 

Chapter 1

The History and Scope of Epidemiology

Learning Objectives

• 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.

• 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

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

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

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

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

– 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

• 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.

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

– 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

– 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

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
•

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

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

• 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

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

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.

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

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

• “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

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,

Avian influenza

• Environmental health

• Chronic diseases

• Lifestyle and health promotion

• Psychological and social epidemiology

• Molecular and genetic epidemiology

Chapter 2

Practical Applications of

Epidemiology

Learning Objectives

• 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

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

• 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.

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.

• 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

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

• 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

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

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

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

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.

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

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

• 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. . .”

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

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

• 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

• 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

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

– 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

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
• 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.

• 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

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

– 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

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 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 percent

age

s 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 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

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

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.

• 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

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:

– 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

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

•

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:

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

(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

• 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.

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

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

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.

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.

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.

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

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

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

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,

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%.