Epidemiology Kept Simple Chapter 1 Epidemiology Past & Present

Epidemiology Kept Simple

• Chapter 1

• Epidemiology Past & Present

Comments re: Text

• EKS = Epidemiology Kept Simple

• 20 chapters

• We cover about 8

• Multiple sections (§) per chapter

• We do not cover all sections in chapters

• Chapter outline on first page

• To help organize thinking

§1.1 Epidemiology, Health, and Public Health

• What is Epidemiology?

• What is Public Health?

• What is Health?

Epidemiology Defined

• Greek roots

• epi = upon
• demos = the people
• ology = study of

• Literally - “study of epidemics”

• Modern definitions include references to

• distributions of health determinant (statistical concept)
• determinants of disease (pathophysiologic concept)
• application in control of health problems (biological and social concepts)

Comparison of epi annd medicine

• Main unit of concern

• Epi –- population
• Medicine -- individual

• But …

• Epi becoming more medical over time
• Medicine becoming more epidemiologic over time

Public Health

• Definitions include reference to

• organized effort (“activity”)
• reduction of morbidity / mortality and improved health

• Composed of dozens of disciplines

• e.g., microbiology, psychology, administration, epidemiology, health ed., etc.
• Has been called “undisciplined”

• Comparison of epi and public health

• epi = “a study of”
• pub health = “an activity”

• Follow-up on WebCT discussion board?

Health

• Multiple definitions (cultural specific?)

• WHO (1948) defined health as “well-being”

• Not merely the absence of disease
• Physical, mental, and social well-being

• Should definitions of health reference quality of life?

• Pros
• Cons

Additional Terms

• Morbidity = disease or disability

• Mortality = death

• Occurrence of disease = prevalence or incidence (will distinguish later in course)

• Endemic = normal occurrence

• Epidemic = greater than normal occurrence

• Pandemic = epidemic on multiple continents

§1.2 Uses of Epi (Morris, 1957) see pp. 3 - 4

• Historical study

• Community diagnosis

• Working of health services

• Individual chances

• Complete clinical picture

• Identify new syndromes

• Determine cause (ultimate importance)

§1.3 Epidemiologic Transition (pp. 4 – 10)

• This section of the text has section headings:

• 20th century changes in disease patterns
• Mortality trends since 1950
• Life expectancy

• Intends to provide additional context

Leading Causes of Death

Changes in mortality

• Epi transition

• Acute to chronic cause
• Infectious to “life style” cause
• Decrease mortality overall
• Death burden shifted to older ages

• Many causes

• Medical technology (antibiotics, anesthesia)
• Birth control
• Nutrition
• Sanitation and vector control
• Education
• Improved standard of living
• etc. (don’t over-simplify!)

Demographic Transition

U. S. Mortality 1950 – 1990 Discuss (Fig 1.2, p. 8)

Mortality, Selected Cancer, U. S. (Fig. 1.3, p. 9)

Life Expectancy at Birth (Fig. 1.4, p. 10)

§1.4 Selected Historical Figures and Events

• “An essential part of the outfit of the investigator in the field” (Major Greenwood)

• Headings in this section

• Before epi was a separate discipline
• Emergence of epi in Victorian England
• Twentieth century epi
• Smallpox (optional)

Before Epi was a Discipline pp. 11 – 12

• We must understand the role of culture and western civilization

• Selected points:

• Pre-scientific medicine was based on philosophy, religion, and morality
• Hippocrates symbolizes the shift to observation and the environment
• The Dark Ages represent a decline in enlightenment and public health
• The Protestant reformation brought with it important cultural changes

Western Civilization and Scientific Revolution (cont.)

• The renaissance brought with it an Age of Enlightenment

• Science liberates itself from philosophy, morality, and religion

• Post-modernism risks decadence

Demographic Approach

• John Graunt (1620 – 1674)

• pp. 12 – 14

Graunt’s Life Table % surviving to age

Lessons Learned from Graunt (Rothman, 1996)

• he was brief

• made reasoning clear

• subjected theories to multiple and varied tests

• invited criticism

• was willing to change ideas when confronted with contradictory evidence

• avoided mechanical interpretations

Germ Theory (p. 14)

• Highlights

• Self-replicating (i.e., biological) agent
• Theory not accepted until late 1800s
• Competing theory (“miasma” = atmospheric pollution) was accepted as late 1880s
• Early contagionists
• Fracastoro (first cogent germ theory, 16th century)
• Jakob Henle & Robert Koch
• Pasteur
• Snow (see next section)
• Salmon (vector borne transmission)

John Snow

• Quintessential epidemiologic hero

• Physiologist, anesthesiologist, & epidemiologist

• Remembered for

• Insightful theory of disease
• Impressive methods of studies

Snow’s Waterborne Theory

• Refuted miasma in favor of contagion

• Theory on

• Clinical facts: symptoms and treatment
• Physiologic understanding: death due to fluid loss, smudging of blood, and asphyxiation
• Epidemiologic observations: epidemics followed routes of commerce, environmental contamination during epidemics

Components of Snow’s Contagion Theory

• Free-living agent
• Fecal-oral transmission (person-to-person)
• Agent multiplies within the host
• Water-borne transmission

Snow’s Methods

• Snow’s methods are a model for non-experimental epi

• Three types of studies

• Ecological design: compared cholera rates by region
• Cohort design: compared cholera rates in exposed and non-exposed individuals
• Case-control design: compared exposure status in those with and without disease

Snow’s Ecological Study Figure 1.13 (p. 24)

Ecological Study Key data in Figure 1.13 (p. 24)

• Example of rate calculation

• Rate St. Saviour = 45 / 19,709 × 100,000 = 227
• Rate Christchurch = 7 / 16,022 × 100,000 = 43

• Water source

• St. Saviour – Southwark and Vauxhall Water Only
• Christchurch – multiple water companies including Vauxhall

Snow’s Cohort Study Key data in Table 1.7 (p. 25)

• Data by household

• Household water sources known

• Rates per 10,000 households = cases / households × 10,000

• Main comparison:

• Rate Southwark & Vauxhall = 1263 / 40,046 × 10,000 = 315
• Rate Lambeth = 98 / 26107 × 10,000 = 37.5

• Conclude: Southwark & Vauxhall households had 8.5 time risk of Lambeth

Snow’s Case-Control Study

• Collect data on all cases

• Determine source of water for cases and non-cases

• See pp. 23 – 26 for examples of interviews

Snow’s Map of Golden Square Cholera Outbreak (Fig 1.14)

• Cases more likely to live near Broad St. pump

• Exceptions: no cases in Brewery and few cases in Workhouse

• {Paste section of map here}

Exposure to Broad St. Pump Water

• Case-control studies measure frequency of exposure (not frequency of disease)

• Consumption (exposure) frequent in cases

• 61 cases – exposure confirmed
• 6 cases – non-exposed
• 6 cases – equivocal

• Exposure rare in non-cases

• Exposure more frequent in cases than controls

Removal of Broad Street Pump Handle

• Snow supported his [good] theory with high quality data

• But how did he convince the Guardians of the Golden Square area to remove the pump handle?

20th Century Epidemiology (p. 26)

• Addressing the chronic disease associated with epidemiologic Transition

• Illustrative examples

• British Doctors Study (Doll & Hills studies of the effects of smoking)
• Framingham Heart Study (risk factors for heart disease, many investigators)