1. Introduction to epidemiology Mark Dancox Public Health Intelligence Analyst Course – Day 1

2. In this session What is epidemiology? – Definitions – Types Measures of disease frequency – Incidence – Prevalence Types of epidemiological study – Descriptive – Analytic

3. What is Epidemiology? “the study of the distribution, frequency and determinants of health problems and disease in human populations” The unit of interest is the population.

4. Types of epidemiology and their uses 1.Descriptive epidemiology Describing patterns and trends in health and disease in populations 2.Analytical epidemiology Examining associations and causation 3.Experimental epidemiology Testing population interventions

5. Measures of disease frequency The two main measures of disease frequency are: – Incidence – Prevalence

6. What is incidence? The incidence is the number of NEW CASES of disease that develop in a population during a specified time period Usually expressed as the number of new cases per 100,000 population per year.

7. Incidence Incidence quantifies the number of new cases of disease that develop in a population of individuals at risk during a specified time period The denominator “population at risk” should consist of the entire population in which new cases can occur. Need specified Population and time period

8. Incidence -Example In 24 practices in Scotland with a total male population of size 60,577 there were 165 new patients in one year with epilepsy.

9. Prevalence Prevalence is a measure of the individuals in a population who have the disease at a specific instant. Can be expressed as a proportion, percentage or per 1,000 population. Can be point, period or lifetime prevalence Often referred to as prevalence rate, but it is not strictly speaking a rate. Prevalence = Total No. cases at given time Total Population at that time

10. Prevalence Example In 24 practices in Scotland with a total male population of size 60,577 there were 577 male patients with epilepsy. Thus the prevalence of epilepsy in this population is: Prevalence = 577 60577 = 0.0095 Or 9.5 cases per 1,000

11. Why might the prevalence of a condition appear to have changed? New diagnostic technique Increased incidence following increased exposure to a causal factor Improved treatment resulting in longer survival time High profile case, raises awareness Changed surveillance system – broadens the definition of a case Improved treatment – resulting in cure for some

12. How are Incidence and Prevalence related? For diseases with a low incidence rate but where those with the disease are affected for a long time period e.g. diabetes or asthma, the prevalence will be high relative to the incidence. If the rate of development of a disease is high, but it has a short duration, the prevalence will be low relative to the incidence. Prevalence = Incidence x Average Duration of Disease

13. Incidence and prevalence Sick population (Prevalence) Healthy population Incidence (new cases) die (mortality) recover

14. When to use Incidence or Prevalence prevalence descriptive studies can calculate the effect of a particular disease in a community can predict the health care requirements incidence studying aetiology (causes of disease) can establish the sequence of events not susceptible to bias by survival

15. Example: incidence and prevalence Cases of cold infections in class 4J. Class size: 20 JanuaryFebruaryMarch What is the incidence in February? What is the point prevalence on the 28 th February? What is the period prevalence during February?

16. In Summary : incidence and prevalence incidence: the number of new cases of disease per n of population occurring in a specified time period prevalence: the number of persons with disease at one point in time as a proportion of the total number of persons in that population.

17. Types of study

18. Types of studies Epidemiology is concerned with 3 things: – frequency of disease } – distribution of disease } definition – cause of disease } Descriptive studies = (frequency/distribution) Analytical studies = (causes)

20. Descriptive studies Characterise disease in terms of time, person, place Type of people affected by disease and when Assist in planning of healthcare services Hypothesis generating

21. 1. Case reports/series Detailed report of disease in a single patient Several patients = case series Thalidomide (1950s) HIV (1980s)

22. 2. Ecological Populations rather than individuals Different countries, regions, health areas, towns Explore association between disease/possible cause Mortality and unemployment Cancer and smoking

23. Example: Fat in the Diet and Cancer Source: K. Carroll, “Experimental evidence of dietary factors and hormone-dependent cancers,” Cancer Research vol. 35 (1975) p. 3379. Copyright by Cancer Research.

24. On the country level, per capita food intake may just be an indicator of overall wealth and industrialization. The ecological fallacy was in studying countries when one should have been studying people.

25. 3. Cross sectional Look at prevalence of disease Snapshot of the population at a point in time Respiratory symptoms and smoking Circulatory disease and aspirin use

26. Analytical studies Test a specific hypothesis Is a group at high risk of developing disease Is a treatment or intervention effective Is a factor associated with development of disease Individuals rather than populations

27. An hypothesis… The number of Cholera infections fell after John Snow removed the handle from the Broad Street pump..

28. Two types of analytical studies Observational Associations between disease and outcome No experimental intervention/treatment given Intervention Associations between treatment and outcome Intervention is made

29. 1 Case-Control Study (observational) Compares people with a condition (cases) to a similar group of people without the condition (controls). Often used to investigate the source of an outbreak of disease. Cannot calculate the incidence risk as selection based on the basis of having disease in the first place. Lung cancer and cigarette smoking Doll and Hill (1952, BMJ)

31. 2 Cohort Study Follow up two groups over time and compare the occurrence of disease One group is exposed to a possible risk factor for the disease, while the other is not (the control group) The exposure is the starting point, the disease is the outcome of interest. Cigarette smoking and mortality Doll and Hill (1964, BMJ)

33. 1 Clinical trials (intervention) Investigator intervenes to provide treatment Group 1 = new treatment Group 2 = control treatment (placebo) Blind allocation/blind assessment/double blind Treatments compared at different times

36. James Lind and Vitamin C Surgeon on HMS Salisbury Selected 12 sailors having scurvy Split them into six pairs Each given additions to rations: (1) seawater, cider, garlic, mustard, horseradish (2) spoonfuls of vinegar (3) oranges and lemons RECOVERY IN THOSE FED CITRUS FRUITS!

37. Association and causation Epidemiology does not determine the cause of a disease in a given person It helps determine the relationship or association between an exposure and frequency of disease We infer causation based upon the association and several other factors

38. Association Association is an identifiable relationship between an exposure and disease – implies exposure might cause disease – ‘risk factors’ for disease Most often, we design interventions based on associations

40. Factors affecting disease Health is affected by many factors, as summarised by Dahlgren and Whitehead’s diagram…

41. Assessing the relationship between a possible cause and an outcome Could it be the result of chance? Could it be due to selection/measurement bias? Could it be due to confounding? Could it be causal? Apply guidelines and make a judgement.

42. Causation Causation implies there is a true mechanism that leads from exposure to disease Finding an association does not make it causal

43. A Note on Causation – Bradford- Hill Criteria Is there evidence from true experiments in humans? Is the association strong? Is the association consistent from study to study? Is the temporal relationship appropriate (Did the postulated cause precede the postulated effect?) Is there a dose response gradient (Does more of the postulated effect follow from more of the postulated cause?) Does the association make epidemiological sense? Does the association make biological sense? Is the association specific? Is the association analogous to a previously proven causal association?

44. References Epidemiology for the uninitiated. Coggon D, Rose G, Barker DJP. 1997. ISBN: 0-7279-1102-3 Epidemiology in medicine. Hennekens CH, Buring JE. 1987. SBN: 0-316-35636-0