10/02/2014 This is the intellectural property of Dr Raywat Deonandan ©2014 No part may be reproduced without his written permission ([email protected])

HSS4303B – Intro to Epidemiology

Natural History of Disease

Artefact • (Artifact is the American spelling; both are acceptable) • a spurious finding, such as one based on either a faulty choice of variables or an overextension of the computed relationship

Artifactual trends in mortality 1. Numerator

Interpreting observed changes in mortality • Changes in mortality – Artifactual • Problems with the numerator • Problems with the denominator

– Real • Identify possible explanations • Develop a hypothesis

Cohort

Cohort

Errors in diagnosis Errors in age Changes in coding rules Changes in classification

2. Denominator

Errors in counting population Errors in classifying by demographic characteristics (e.g., age, race, sex) Differences in percentages of populations at risk

From Latin “cohors”, it was the basic unit of the Roman Legion.

Cohort

Refers to a bunch of people who move together.

Cohort • A group of people who share a particular experience or characteristic(s) over a period of time – Irish women born in 1950 – Engineers who smoked between the ages of 25-30 – HSS students in 3rd year

Now…. An example • Pertussis – Whooping cough – Highly contagious bacterial infection – Effective, well tolerate vaccine that lasts several years – One of the leading causes of vaccine-preventable deaths in the world

Refers to a bunch of people who move through time together.

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Source: Wikipedia

Pertussis

DALYs

Facts

So What’s Happening?

• Beginning in 1990 Canada experienced a resurgence of pertussis. • The mean annual incidence before 1990 was 3.8 cases per 100 000 population which increased to 37.2 thereafter. • The mean annual hospitalization rates increased from 2.7 per 100 000 before 1990 to 5.2 afterward. • The proportion of cases in 0- to 4-year-old children decreased, whereas it increased steadily in all other age groups • Between 1990 and 1998 the median age of cases shifted from 4.4 to 7.8 years.

• “The sudden increase in pertussis incidence in Canada can be largely attributed to a cohort effect resulting from a poorly protective pertussis vaccine used between 1985 and 1998.” –NTEZAYABO et al, 2003

The Pediatric Infectious Disease Journal: January 2003 - Volume 22 - Issue 1 - pp 22-27

Factors Around Cohort Effect • Smoking behaviours differ between generations • Income differs between generations • Geopolitical circumstances (e.g. war) differ • Health system issues may differ (e.g. infant health care) • etc

• In other words, something that happened in the 80s to infants did not manifest till the 90s in older children, as the cohort moved through time

Example • In the UK, politicians often speak of the “cohort effect” in terms of a certain generation: – Brits born between 1925 and 1945 (centred around 1931) experienced more rapid improvements in mortality than generations born on either side (i.e., younger and older) WHY?

• Cross sectional view – Identifies peculiarities and key messages from the data – Which age group has the highest rates of tuberculosis

• Cohort view – Identifies groups with the trait or disease incidence – Group is followed over time to see if the trait develops or disease manifests

Cohort vs Cross-Sectional View (1900) Table 4-14. Age-specific Death Rates per 100,000 from Tuberculosis (All Forms), Males, Massachusetts, 1880-1930

Cohort effect Table 4-15. Age-specific Death Rates per 100,000 From Tuberculosis (All Forms), Males, Massachusetts, 1880-1930

Year Age (yr)

Year

1880

1890

1900

1910

1920

1930

0-4

760

578

309

309

108

41

5-9

43

49

31

21

24

11

10-19

126

115

90

63

49

21

20-29

444

361

288

207

149

81

30-39

378

368

296

253

164

115

40-49

364

336

253

253

175

118

50-59

366

325

267

252

171

127

60-69

475

346

304

246

172

95

70+

672

396

343

163

127

95

Age (yr)

1880

1890

1900

1910

1920

0-4

760

578

309

309

108

5-9

43

49

31

21

24

10-19

126

115

90

63

49

1930

21

20-29

444

361

288

207

149

81

30-39

378

368

296

253

164

115

40-49

364

336

253

253

175

118

50-59

366

325

267

252

171

127

60-69

475

346

304

246

172

95

70+

672

396

343

163

127

95

41 11

Data from Frost WH: The age selection of mortality from tuberculosis in successive decades. J Hyg 30:91-96, 1939.

Peak mortality occurred for the 30-39 years age group (Cross sectional view)

Follow the cohort and the peak mortality occurs for the 20-29 years old group

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The History of Disease

Age of Pestilence and Famine

The History of Disease Abdel Omran, 1971…. In very very very broad terms, historians consider the history of human disease to have occurred in 3 phases:

• Age of Pestilence and Famine • Age of Receding Pandemics • Age of Degenerative and Manmade Diseases

• • • •

High mortality rates Wide swings in mortality rates Little population growth Very low life expectancy

http://www.who.int/bulletin/archives/79%282%29159.pdf

Age of Receding Pandemics • Less frequent epidemics • Less incident infectious disease • A slow rise in degenerative disease

Age of Degenerative and Manmade Diseases

• • • •

Cancers Obesity Cardiovascular disease Diseases associated with high SES and relatively bountiful food

• Most countries are here now

Cf. Demographic Transition 1. 2.

3.

4.

5.

Omran defined: The Epidemiologic Transition • a human phase of development witnessed by a sudden and stark increase in population growth rates brought about by medical innovation in disease or sickness therapy and treatment, followed by a re-leveling of population growth from subsequent declines in procreation rates – Wikipedia

Cf. Demographic Transition

stage one, pre-industrial society, death rates and birth rates are high and roughly in balance stage two, that of a developing country, the death rates drop rapidly due to improvements in food supply and sanitation, which increase life spans and reduce disease stage three, birth rates fall due to access to contraception, increases in wages, urbanization, etc. stage four: there are both low birth rates and low death rates. Birth rates may drop to well below replacement level as has happened in countries like Germany, Italy, and Japan Stage five: sub-replacement fertility

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Perfectly correlated to per capita alcohol consumption in these countries.

Epidemiologic transition from 1990 to 2020

Natural History of Disease

Natural history of a disease in a patient

refers to a description of the uninterrupted progression of a disease in an individual from the moment of exposure to causal agents until recovery or death

An idealized depiction of the natural history of disease.

Natural history of a disease in a patient

Death

Natural history of coronary heart disease.

Survival

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Natural History of Disease • …is not the same as the changing patterns of disease in a population • E.g., the distribution of CHD over SES groups may change over time as a society changes…. • But the natural history of CHD will not change

“Pyramid” or “Iceberg” of Disease

Prognosis

--  SCREENING

• “the likely outcome of a disease” • The important endpoint in the Natural History of Disease

“Petosiris to Nechepso”

Prognosis • Identify the end points – Death – Survival with disability – Survival without disability – Relapse

• Delay the endpoints • Improve the quality of life • Measures of prognosis

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Measures of prognosis 1. Case-fatality ratio 2. Mortality rates – Person years

3. Five-year survival rate 4. Observed survival (rationale for life table) 5. Life table – Kaplan-Meier method for survival

6. Median survival time 7. Relative survival rate

Measures of prognosis CFR

1. _______________ – Is defined as the number of people who die of the disease divided by the number of people who have the disease – Is used mostly for diseases with shorter duration or acute conditions – Is less used for diseases with low mortality and long disease span – Alternate measure of prognosis need to be used for diseases with longer span

Measures of prognosis Mortality Rate 2. ______________ (person-years)

– Is defined as number of deaths divided by the person-years over which the group is observed – The unit of measure is person-years (individuals multiplied by the number of years the individuals are observed) – The risk for different individuals is assumed to be the same; for one person-year is equivalent to another

Measures of prognosis 3. ______________ rate Five Year Survival

• Is the percentage of patients who are alive 5 years after treatment begins or 5 years after diagnosis • For cancer is used as a measure of treatment efficacy • Is not effective in late diagnosis and when treatment is not effective • Is not effective when the survival is less than five years

6

hss4303b - natural history of disease.pdf

Changes in classification. 2. Denominator Errors in counting population. Errors in classifying by demographic characteristics (e.g., age, race,. sex). Differences in percentages of populations at risk. Cohort. From Latin “cohors”, it was the basic unit of the Roman Legion. Cohort. Refers to a bunch of people who move together.

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