Transcript document

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
1.
2.
3.
4.
5.
6.
7.
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
1900
1990
1
Pneumonia / influenza
Heart disease
2
TB
Neoplasms
3
Diarrhea
Cerbrovascular
4
Heart disease*
COPD
5
Cerebrovascular*
Pneumonia/ influenza
* Large % had infectious component
Changes in mortality
• Epi transition
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•
•
•
Acute to chronic cause
Infectious to “life style” cause
Decrease mortality overall
Death burden shifted to older ages
• Many causes
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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
6
16
26
36
46
56
60
76
80
64
40
25
16
10
6
3
1
0
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
to age 16
• Water-borne transmission
Snow’s Methods
• Snow’s methods are a model for nonexperimental 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?
th
20
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)