Epidemiology Kept Simple

1. Epidemiology Kept Simple Chapter 1 Epidemiology Past & Present

2. 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

3. §1.1 Epidemiology, Health, and Public Health • What is Epidemiology? • What is Public Health? • What is Health?

4. 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)

5. 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

6. 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?

7. 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

8. 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

9. §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)

10. §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

11. Leading Causes of Death * Large % had infectious component

12. 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!)

13. Demographic Transition

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

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

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

17. §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)

18. Before Epi was a Disciplinepp. 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

19. 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

20. Demographic Approach • John Graunt (1620 – 1674) • pp. 12 – 14

21. Graunt’s Life Table% surviving to age

22. 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

23. 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)

24. John Snow • Quintessential epidemiologic hero • Physiologist, anesthesiologist, & epidemiologist • Remembered for • Insightful theory of disease • Impressive methods of studies

25. 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

26. Components of Snow’s Contagion Theory • Free-living agent • Fecal-oral transmission (person-to-person) • Agent multiplies within the host • Water-borne transmission to age 16

27. 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

28. Snow’s Ecological StudyFigure 1.13 (p. 24)

29. Ecological StudyKey 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

30. 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

31. 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

32. 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}

33. 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

34. 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?

35. 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)