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Introduction to epidemiology
PhD course Spring 2011University of Copenhagen
Anders Koch, senior researcher, Ph.D. MPHStatens Serum Institut&KursusreservelægeEpidemiklinikken, Rigshospitalet
The first and today’s lecture of epidemiology
• Background, definition and change over time
• Descriptive studies
• Frequency measures
• Time and population at risk
• Analytical studies (a little)
Fathers of epidemiology
John Snow1813 – 1858
Cholera in London 1849-
Peter Ludwig Panum1820 – 1885
Measles in the Faroe Islands 1846
Cholera epidemics England 1831-1854
Lancet, "History of...the...cholera in England and Scotland". 1831-32
King Cholera dispenses contagion: The London cholera epidemic of 1854
The medical profession…
"Long life to our Central Board . . . May we preserve our health by bleeding the country . . .”
George Cruikshank (1792-1878): The Central Board of Health: Cholera Consultation (London: S. Knight, 1832)
John Snow 1813 - 1858
• Obstetrician in Frith Street, London
• Considered cholera to becaused by polluted water
• Prevailing theory breathingin of vapour or contagioussubstance in the athmosphere (miasma)
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Water supply in London 1854
Southwark & Vauxhall (green)
Lambeth(red)
Cholera in London 1854
• This argumentation without effect on authorities or water works
• Loss of definitive proof
591,422256,423Rest of London
379826,107Lambeth Company
3151,26340,046Southwark and Vauxhall
Company
Deaths/10,000 houses
Deaths from cholera
No. of houses
Broad Street, Soho 1854 The pump in Broad Street
• Cholera outbreak 19. aug. – 30. sept. 1854
• 616 dead
• Sick persons short distance to particular pump
• Most sick persons direct access to pump
• Snows microscopy: White, fluffy particles in water
• Widow in Hampstead who had died from cholerahad daily her waiter get water from Soho pump
Intervention
• Anecdote: Snow sneaked out at night and removed pump handle making the epidemic stop
• Reality: Handle removed by public health authorities onSnows Snows suggestion September 8th; the removalhad no effect on epidemic
Snows epidemiology
• ’… it is obvious that no experiment could have been devisedwhich would more thoroughly test the effect of water supply onthe progress of cholera than this…. To turn this experiment to account, all that was required was to learn the supply of water to each individual house where a fatal attack of cholera mightoccur.’
• Theory about spread of infectious diseases in general and specifically about the spread of cholera before knowledge of the cause of cholera
• Concepts– Randomisation (rich/poor, males/females, children/elderly)– Mortality rates– Intervention
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Snow’s tracks in history
Society for Epidemiological Research, slogan competition 1981:
Epidemiologists Love Snow Jobs
Objectives of epidemiology course
Become acquainted with epidemiological terminology
Promote
• Understanding & interpretation of epidemiologic data
• Good epidemiologic research
• Understanding of decisions made on epidemiologic data
Netdoktor, februar 2001 Definition
• Epi (on) demos (people, population) logos (knowledgeof) = The knowledge of what happens to people
• ’The study of the distribution and determinants of healthrelated states or events in specified populations, and the application of this study to control of healthproblems’ (Last 1988)
• ’The study of the distribution and determinantsof disease frequency ’
Epidemiology: Definition & objectives
”The outbreak in epidemic form of a disease of pseudo-scientific meticulosis. The symptoms of the condition are characterised by:
a) evidence of a certain degree of cerebral exaltation; b) an inherent contempt for thosewho cannot understand logarithms, and c) the replacement of humanistic and clinical valuesby mathematical formulae.
The systemic effects of this disease areapparent; patients are degraded from human being to pricks in a column, dots in a field, ortadpoles in a pool; with the eventualelimination of the responsibility of the doctor to get the individual back to health.”
Epidemiology is (also)…
Logic and common sense!
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On epidemiologic studies
It is more important to increase the quality of data in the collection phase than to applysophisticated statistics
A. Bradford Hill
In general
Garbage in, garbage out!
Causes of death 1900-1982, DK
100.0%Total100.0%Total
18.0%Other7.2%Other
1.7%Diabetes1.9%Diphtheria
1.9%Chronic liver disease4.2%Accidents
2.0%Pneumonia./influenza4.5%Cancer
2.1%Suicide5.9%Nephritis
2.9%Chronic lung disease6.3%Diarrhea/enteritis
6.5%Stroke7.6%Stroke
6.6%Accidents9.4%Heart disease
23.9%Cancer11.2%Tuberculosis
34.4%Heart disease11.8%Pneumonia/influenza
19821900
Evolvement of epidemiology
• Study of the distribution and determinants of health-related states orevents in specified populations (Last: A Dictionary of Epidemiology)
• In the 1950’erne shift from infectious diseases to chronic diseases(coronary disease, cancer, etc.) – advent of antibiotics
• Framingham study 1949- (coronary diseases)
• Denmark in the lead (Cancer Registry, CPR)
US Surgeon General William Stewart
Talk to the Congress 1969:
The war against pestilence is over and now it is time to close the book on infectiousdisease
Result:
Low priority to infectiousdisease and microbiologicalresearch in Western Europeand the USA
Epidemiology in a historical perspective
• Patterns of mortality and morbidity are changing– From ”infections” to ”chronic” disorders
• Diseases have different natural histories– From diseases with short latency periods (weeks to years)– To diseases with long latency periods (years to decades)
• Changing effects of determinants– From great to moderate effects
• Requires development of new methodology
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1982
Lancet. 1982 May 15;1(8281):1083-7. Related Articles,Links
Risk factors for Kaposi's sarcoma in homosexual men.
Marmor M, Friedman-Kien AE, Laubenstein L, Byrum RD, William DC, D'onofrio S, Dubin N.
An investigation of 20 homosexual men with histologically confirmed Kaposi's sarcomaand 40 controls revealed significant associations between Kaposi's sarcoma and use of a number of drugs (amyl nitrite, ethyl chloride, cocaine, phencyclidine, methaqualone, and amphetamine), history of mononucleosis, and sexual activity in the year before onset of the disease. Patients with Kaposi's sarcoma also reported substantially higher rates of sexually transmitted infections than did controls. Multivariate analysis indicatedindependent significant associations for amyl nitriteand sexual activity and showed useof phencyclidine, methaqualone, and ethyl chloride to be non-significant. Evaluated at the median exposure for patients, the analysis yielded risk-ratio estimates of 12.3 for amyl nitrite (95% confidence limits 4.2, 35.8) and 2.0 for sexual activity (95% confidence limits 1.3, 3.1).
2009
Swine flu symptom checker:
If you wake up looking likethis, don’t go to work
Miranda Carnewro, 18, and Jorge Juarez, 18, wears a masks as they wait to clear U.S. Customs crossing from Ciudad Juarez, Mexico, into El Paso, Texas, Monday, April 27, 2009. (AP Photo/LM Otero)
Epidemiological way of thought(Infectious diseases)
• Is there a problem ?• What characterises the problem?
– When– Where– Who
• Hypothesis
• Is the hypothesis correct?
• Devise public health measures
}}
Descriptiveepidemiology
Analyticepidemiology
Descriptive & analytic epidemiology
Randomised intervention
Epidemiologic focus
Case control study
Cohort study
Case report
Case series
Ecological study(correlational study)
Cross sectional study
generating testing
Hypothesis-
Incidence report
U-land undersøger…..
Når intervieweren mærker at personen i den anden ende af røret er ved at miste interessen, må man sikre sig, at røret ikke bliver smækket på:
"Så ved man at det måske regner eller sner, hvor kunden bor, og så snakker man lidt om det, mens man skynder sig selv at udfylde hvad man regner med kunden ville have svaret."
Skulle folk alligevel smække røret på, fortsætter de mest rutinerede interviewere alligevel:
"Man lader som om kunden stadig er i røret - man taler videre, så de andre ved siden af ikke opdager det, og udfylder hvad man regner med kunden ville have sagt."
http://www.econ.ku.dk/milhoj/stik/uland%20unders%C3 %B8ger.htm
Excess leukemia cases in soldiers 2001?
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Epidemiological way of thought(Infectious diseases)
• Is there a problem ?• What characterises the problem?
– When does it occur?– Where does it occur?– Who’s problem is it?
• Hypothesis (what is the cause of the problem)
• Is the hypothesis correct?
• Devise public health measures
}}
Descriptiveepidemiology
Analyticepidemiology
Diseases can be characterised
• How many?• Absolute/relative
• Where?• When?• Who?
• Gender, age, race, etc..
• Descriptive epidemiology
Disease patterns can be analysed
Frequency & distribution
Determinants
Application
Characteristic A
Characteristic B
Descriptive and analytic studytypes
Randomised/Intervention trialsCross sectional surveys
Cohort studies Correlational studies
Case-control studies Case reports/series
Analytic studiesDescriptive studies
Case-reports and -series Case-reports and -series
"These types of studies in which typically an astute clinician identifies an unusual feature of a disease or a patient's history, may lead to the formulation of a new hypothesis."
"This design has historical importance in epidemiology, as it was often used as an early means to identify the beginning or presence of an epidemic…….. Investigation of the activities of the affected individuals in the case series can then lead to formulation of a hypothesis."
"While case reports and case series are very useful for hypothesis formulation, they cannot be used to test for the presence of a valid statistical association."
H&B 106-7
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When is too much too much?
• Endemy (sporadic)
• Period/seasonal changes
• Epidemy
• Pandemy
Endemic – sporadic outbreaks
• Sporadic outbreaks that constitute the background frequency (rate) in the population
• Fluctuation (daily/weekly/monthly), but overall not significantly different from backgroundrate
• Constitute the main part of infections in a population
Endemicity
URILRI
Inci
denc
e
Aug. Dec. Apr. Aug. Dec. Apr. Aug.
1996 1997 1998
Respiratory tract infection in children in Greenland
Periodic changes
Seasonal variation The epidemic
“Epidemic…include any disease, infectious or chronic, occurring at a greater frequency than usually expected”
When is that?
• Point source• Person-to-person (propagated)
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Point source - cholera Person-to-person spread
When does the observed numberexceed the expected?
• 500 cases of pneumonia in Zealand in toddlersJanuary 2001, but 50 cases in June. Epidemic?– Every winter 500 cases - RS-virus
Cases of Kaposi’s sarcoma in S.F.
Biggar et al., Am J Epidemiol 1987 Oct;126(4):578-86
0
20
40
60
80
100
120
140
160
1976 1977 1978 1979 1980 1981 1982 1983 1984
The epidemic – the special situation
http://www.cdc.gov/mmwr/PDF/wk/mm5040.pdf
Anthrax incidence
0
100
200
300
400
500
600
700
88 89 90 91 92 93 94 95 96 97 98 99 0 1
Turkey USA
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Surveillance / epidemic PandemicsSARSSpanish fluAvian fluSwine flu
Measures of frequency
• Prevalence (prevalence rate)
Number of persons in the population
Number of sick persons at given time
– Point prevalence – prevalence at given time (Christmas eve)– Periodic prevalence – prevalence in a period (Christmas holiday)
Sum of time at risk for the population
Number of new cases of disease in a specific period
• Incidence (incidence rate)
The concept of time at risk
Time not at risk
Real time
� Time at risk
”Start” ”End”
Why different measures ?
• Prevalence measures the presence of disease at a specific time in a population
• Measure of burden of disease
• Incidence measures the frequency of diseaseper unit of time
• Measure of risk
Factors affecting prevalence
Beaglehole et al., Basic Epidemiology, WHO 1993.
• Longer duration of disease
• Prolongation of life without cure
• Increase in new cases• In-migration of cases
• Out-migration of healthy
• In-migration of susceptibles• Improved diagnostic facilities
• Shorter duration of disease
• Higher case-fatality rate from disease
• Decrease in new cases• In-migration of healthy
• Out-migration of cases
• Improved cure rate
Prevalence = Incidence * duration of disease
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What measure to use?
The measure depends on the question!
Incidence and prevalence: practical example
• Respiratory tract infections (RTI) in children in Greenland• What is the prevalence and incidence of RTI?
• Prevalence– Time with disease by time of
observation
– (15+15+11)/100 = 41%– Measure of disease burden
• Incidence– Number of new episodes by
time at risk
– 3/(100-41-9) = 3 per 50 days– Measure of risk
Day 1
Time at risk
Time of observation
Day 100
15 15 113 3 3
Population at risk
• Crucial to the calculation of frequency and rates that the population at risk is defined! Who is at risk?
• Influenza– All who have not been infected with the (this year) prevailling
serotypes or are unvaccinated
• Cervical cancer– Women aged 25-69 years
• Breast cancer– All
• Salmonella outbreak in restaurant– All who have tasted the food
• Hospital infections– Salmonella in the central kitchen– Defect bedpan disinfector in ward
Background population• England 1983: ’Windscale – the Nuclear Factory’
(Sellafield)• Statistically significant excess number of cases of
childhood leukemia in the village Seascale• Should the plant be shut down?
The Texas sharpshooterDescriptive and analytic study
types
Randomised/Intervention trialsCross sectional surveys
Cohort studies Correlational studies
Case-control studies Case reports/series
Analytic studiesDescriptive studies
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Ecological studies
In correlational studies, measures that represent characteristics of entirepopulations are used to describe disease in relation to some factors of interest such as age, calendar time, utilization of health services orconsumption of a food, medication or other product. (H&B p 102)
Correlation (0 < r < 1)
Correlation (-1 < r < 0)
Occurrence
”Exposure”
No correlation (r = 0)
Kaposi’s sarcoma
Fig. 1. Kaposi’s sarcoma and non-Hodgkin’s lymphoma incidence among men, per 100 000 people per year, age-standardized to the 1970 U.S. population, shown on a linear and log scale to illustrate both the absolute and relative changes in nine Surveillance, Epidemiology and End Results (SEER) registries and in the San Francisco area registry only, from 1973 through 1998. Years with no cases were set arbitrarily at 0.12 cases in the log scale.
Correlational studies
“The presence of a correlation does not necessarily imply the
presence of a valid statistical association. Conversely, lack of a
correlation in such studies does not necessarily imply the
absence of a valid statistical association.”
(Hennekens & Buring page 104)
Cross sectional surveys
”A third type of study is the cross-sectional or prevalence survey, in
which exposure and disease status are assessed simultaneously
among individuals in a well-defined population.”
(H&B p. 108)
Cross sectional surveys
• Studies, in which outcome and exposure are determined simultaneously
• The observed outcomes are prevalent
• Data on risk factor associations will accordingly represent both survivaland etiology
• It cannot be ruled out that the exposure under observation has changedafter and maybe because of the outcome
• It cannot always be determined which came first, the exposure or the outcome
Risk of Trichinella infection in Greenlanders
(1.74-43.31)8.68Yes
Intake of Polar bear meat
1No
(1.01-1.57)1.26Yes
1No
Occupation as hunter orfisherman
(95% CI)OR
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The Lancet 1999Causal association between MMR and
neuropsychiatric disorders?
Subsequent actions
10 of 11 original authors, 2004:• We wish to make it clear that in this paper no causal link was established
between MMR vaccine and autism as the data were insufficient. However, the possibility of such a link was raised and consequent events have had major implications for public health. In view of this, we consider now is the appropriatetime that we should together formally retract the interpretation placed upon these findings in the paper, according to precedent.4 We were unable to contactJohn Linnell.
BMJ, 2010:• In a statement published online (www.thelancet.com) the editors of the Lancet
said: "Following the judgment of the UK General Medical Council’s Fitness to Practise Panel on Jan 28, 2010, it has become clear that several elements of the 1998 paper by Wakefield et al are incorrect, contrary to the findings of an earlier investigation.
• "In particular, the claims in the original paper that children were ‘consecutivelyreferred’ and that investigations were ‘approved’ by the local ethics committeehave been proven to be false. Therefore we fully retract this paper from the published record."
• Cohort studies– Information on exposure and outcome in the whole study
population– Frequent outcomes
• Case-control studies– Only information about sample from the population– More rare disease
• Randomised controlled studies
Analytic study types
Descriptive epidemiology
Advantages
• Cheap & quick
• May provide important overview
Disadvantages
• No information on the individual
• No control for confounding
• May involve bias
• Results may be ambiguous
• Can not test (causal) hypotheses
Descriptive vs. analytic epidemiology
Analytic epidemiology
Disadvantages
• Expensive
• Laboreous
• May involve bias
Advantages
• Information on the individual
• Control for confounding
• Results less ambiguous
• Can test (causal) hypotheses
Summary day 1
• Epidemiology the study of the distribution and determinants of disease frequency
• Change from infectious diseases to chronic diseases in 20th Century (but infectious diseases are not outdated)
• Epidemiological way of thought identification of problem, description in time, place and person, setting up hypothesis and subsequent testing
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Summary day 1
• Descriptive studies include case reports/series, correlationand cross sectional studies
• Diseases can occur endemic, in epidemics and in pandemics
• Epidemics point source or person-to-person
• Frequency measures include prevalence and incidence
And the next times…
Analytic studies (cohortstudies, case controlstudies) and much, much more…