1. Descriptive Epidemiology HSC4500 Module 4 1

2. Types of Epidemiology Descriptive Examines the development and distribution of disease or health-related events Analytic Determines the validity of hypotheses that attempt to explain what descriptive epidemiology has revealed Experimental Purposeful manipulation of the independent variable to study the subsequent effect on the dependent variable

3. Corresponding epidemiological study designs Descriptive ▫ If comparing populations:  Ecological (correlational) ▫ If comparing Individuals:  Case report  Case series  Cross sectional studies Analytic studies ▫ Observational  Case-control  Cohort (retrospective; prospective) Experimental  Randomized controlled trial (ex. testing new pharmaceuticals)  Field trial (high risk members of the population)  Community trial (evaluate lifestyle interventions)

4. Descriptive vs. Analytic Epidemiology Descriptive Usually the “first step” Utilized when relatively little is known regarding the disease or health-related event Utilizes previously collected data Identifies potential associations for further testing (hypothesis generation) Involves the determination of person, place, time (PPT) Analytic Examines potential associations revealed by “new” data Utilized when there exists a greater understanding of various aspects of the disease or health-related event Examines the causality of associations Involves the determination of the “why”

5. Descriptive Studies Often less expensive than analytic studies Often less time-consuming than analytic studies Most often used to explain: ▫ Patterns of disease occurrence  Who becomes ill (or experiences the “health-event”)  Who does not become ill (or avoids the “health-event”)  In what populations are disease (or event ) rates highest  In what populations are disease (or event) rates lowest  Are temporal patterns of disease (or health-related event) evident ▫ Beneficial in:  Allocation of resources (administrators)  Determination of risk factors (epidemiologists, providers)  Development of effective programs

6. Four main types of descriptive studies 1.Ecologic studies 2.Case reports 3.Case series 4.Cross-sectional surveys © 2010 Jone s and Bartl ett Publi shers, LLC

7. 7 1. Ecological studies: These are large-scale studies that provide population-wide estimates of disease rates vs. exposure status In other words: Data are often presented comparing various countries around the world For example:

8. Interpret these findings regarding breast cancer mortality: 4-8

9. 2. Case reports and 3. Case series A case report involves a profile of a single individual A case series involves a small group of patients with a similar diagnosis These studies provide evidence for larger scale studies They are hypothesis-generating © 2010 Jone s and Bartl ett Publi shers, LLC

10. Ex. Case reports (case series) “I saw three patients in the past 48 hours who reported experiencing psychotic episodes after watching ‘Here Comes Honey Boo Boo’ last Tuesday night”. What are your assumptions regarding this phenomenon? Note: There is NO comparison group NO detailed definition of either the exposure or the outcome There is a suggestion that the exposure preceded the outcome but NO proof. There is an implied relationship between the two events. 10

11. 4. Cross-sectional survey (sometimes called prevalence survey) Conducted over a short period of time (usually a few days or weeks) and the unit of analysis is the individual Like a “snapshot in time” of the characteristics of a group of individuals There is no follow-up period * A cross-sectional survey that is conducted on a regular or scheduled basis is a serial survey © 2010 Jone s and Bartl ett Publi shers, LLC

12. 12 Example: A study of the severity of angina and exercise showed that there was an inverse relationship between the level of exercise and reported chest pain severity. Note: It is NOT clear which is the exposure and which is the outcome. Does lack of exercise cause chest pain? Or does chest pain lead to lack of exercise?

13. Cross-sectional study Strengths Can be used to study several associations at once Can be conducted over a short period of time Produce prevalence data Weaknesses Unable to establish sequence of events Not feasible to use these studies to investigate rare conditions (Wilson’s disease, 1-4 cases per 100,000) Potentially influenced by response bias (another lecture) © 2010 Jone s and Bartl ett Publi shers, LLC

14. Ex. Serial surveys Cross-sectional surveys that are routinely conducted ▫U.S. Census ▫Behavior Risk Factor Surveillance System ▫National Health Interview Survey ▫National Hospital Discharge Survey © 2010 Jone s and Bartl ett Publi shers, LLC

15. The “Person” Factor: All those characteristics about an individual that may explain the reason for the development of a particular disease or the occurrence of a particular health event: AgeHobbies SexPets OccupationTravel Immunization statusPersonal Habits Co-morbidity Stress Medication(s)Family dynamics Nutritional statusSchool environment Socioeconomic factorsGenetics, etc., etc., etc., Religion

16. The “Time” Factor: Secular = the trend of a disease (or health event) over an extended period of time; the pattern established during long- term occurrence Periodic = temporal interruption of the general trend of a secular pattern Seasonal = cyclic variation in disease frequency by time of year & season (environmental, occupational, recreational) Epidemic = increase in incidence above the expected in a defined geographic area within a defined time period

17. Secular trend: Genital Warts; Initial Visits to Physicians’ Offices, United States, 1966–2011 NOTE: The relative standard errors for genital warts estimates of more than 100,000 range from 18% to 30%. SOURCE: IMS Health, Integrated Promotional Services ™. IMS Health Report, 1966–2011. 2011-Fig 53. SR

18. Periodic trend: Whooping Cough Four-monthly admissions, 1954-1973 Chaturved, C., Descriptive Epidemiology

19. Seasonal Trend Outpatient Influenza Visits 2006-2010 Percentage of visits for influenza-like Illness (ILI)* reported by the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet),† by surveillance week --- United States, October 1, 2006--May 1, 2010, CDC influenza data

20. A Review: Endemic, Epidemic and Pandemic Endemic - The habitual presence (or usual occurrence) of a disease within a given geographic area Epidemic - The occurrence of an infectious disease clearly in excess of normal expectancy, and generated from a common or propagated source Pandemic - A worldwide epidemic affecting an exceptionally high proportion of the global population Number of Cases of Disease Time

21. Clustering Time/place clusters, or Disease clusters A group of cases that occur within a relatively close proximity and with a distinct pattern of distribution Cluster analysis is particularly beneficial when examining rare diseases or “unique” disease events.

22. Time/Place clustering analysis An inferential tool Nearly always ineffective in identifying causes of disease Often used to address public concern about environmental hazards. Typically performed post hoc, and not as a result of a prior hypothesis Describes disease events as they are distributed geographically. Geographical area divided into a series of equal square areas. If clustering occurs, probability of cause-effect relationship increases  further epidemiological testing is pursued Cluster analysis and disease mapping—why, when, and how? A step by step guide, BMJ 1996; 313 doi: http://dx.doi.org/10.1136/bmj.

24. Now: Geographic Information Systems Per CDC: Collection of science and technology tools used to manage geographic relationships and integrate information Help to analyze spatially-referenced data and make well- informed decisions based on the association between the data and the geography Refers to both the software and hardware that make up the system of digital databases and layered maps. Plays an important part in health promotion and protection 24

25. 25 FLORIDA DEPARTMENT OF HEALTH Division of Public Health Statistics & Performance Management, Florida Charts

26. Obesity United States, 1987-1998

27. Credits: Sexually Transmitted Disease: Surveillance 2011Centers for Disease Control and Prevention National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention Division of STD PreventionCenters for Disease Control and PreventionNational Center for HIV/AIDS, Viral Hepatitis, STD, and TB PreventionDivision of STD Prevention 27