Epi Quiz 1

Front 1

define epidemiology

Back 1

the field of study of the distribution of a disease or a physiological condition in human pops and of the factors that influence this distribution.
epi = upon
demos = people

Front 2

list 3 objectives of epidemiology

Back 2

1. identify etiology & relevant risk factors (goal: Decrease M&M)
2. Develop rational basis for prevention programs
3. determine extent of disease in a community
4. study natural history and prognosis of disease
5. evaluate existing & newly developed preventative & therapeutic measures & modes of healthcare delivery
6. Provide foundation for developing public policy

Front 3

3 types of prevention and their def

Back 3

primary prevention - preventing a disease in persons who are well and do not have the disease

secondary prevention - identifying people in whom disease has begun but have not yet developed clinical symptoms (preclinical phase of illness)

tertiary prevention - preventing complications in the clinical phase of illness.

Front 4

describe John Snow and the cholera epidemic

Back 4

John Snow - father of epidemiology (physician/statistician/sociologist). Mapping of cholera cases in East London during cholera epidemic of 1854. Traced source to a single well on broad st. that had been contaminated by sewage. 10-20,000 people died per month.

Front 5

what is a confidence interval?

Back 5

CI is the range in which the TRUE treatment effect is likely to lie.
for a 95% confidence interval, if an experiment is run 100 times, the results will likely fall in the interval about 95 times.

- not always symmetrical

Front 6

if CI is narrow, what does this tell us?

If CI is wide, what does this tell us?

Back 6

Narrow CI - likely a large and powerful study.

Wide CI - likely a small and less powerful study.

Front 7

P value

Back 7

calculated to assess whether trial results are likely to have occurred simply through chance.

Front 8

why are CIs preferable to p values?

Back 8

P values simply show a cut-off beyond which we assert values are "statistically significant".

CIs give more information - range of possible effect sizes.

Front 9

type I error

Back 9

assuming that there is an effect when there is not.

5% chance of type 1 error for p =0.05 and 95% CI

Front 10

type II error

Back 10

assuming there is no effect when there is in fact an effect.

Front 11

when is an OR or RR not statistically significant?

Back 11

an OR or RR is not significant if the CI includes 1.

or

if the CI for mean difference includes 0.

Front 12

basic triad of descriptive epidemiology

Back 12

1. time
2. person
3. place

Front 13

basic triad of analytic epidemiology

Back 13

agent host environment

vector

Front 14

direct vs. indirect transmission

Back 14

direct: person to person

indirect: via contaminated air/water/vector

Front 15

3 characteristics of host that affect disease transmission

Back 15

genetic endowment
immunologic state
age
personal bx

Front 16

3 characteristics of agents that affect disease transmission

Back 16

nutrients
poisons, allergens
radiation
physical trauma
microbes
physiological experiences

Front 17

3 characteristics of environment that affect disease transmission

Back 17

crowding
atmosphere
modes of communication

Front 18

subclinical disease

Back 18

disease that is not destined to become clinically apparent

Front 19

preclinical disease

Back 19

disease that is destined to progress to clinical disease but has not yet manifested clinical signs and symptoms.

Front 20

latent disease

Back 20

existing infection with no active multiplication of the agent. only the genetic message is present in the host, not the viable organism.

Front 21

carrier status

Back 21

a person who harbors the organism but is not infected (as measured by serological studies - no antibody response); can still infect others but infectivity is often less serious than with other infections. Can be temporary or chronic (e.g., typhoid mary)

Front 22

endemic

Back 22

habitual presence of a disease within a given geographical area. may also refer to the usual occurrence of disease in that area.

Front 23

epidemic

Back 23

similar illnesses in a community or region clearly in excess of normal expectancy and derived from a common source.

Front 24

2 determinants of disease outbreak

Back 24

1. balance between # immune and # susceptible and at risk.

2. incubation period

Front 25

attack rate (actually a proportion)

Back 25

# of people at risk in whom a certain illness develops
___________________________________________________________
total # people at risk

(time period is usually implicit given incubation period)

Front 26

common diseases with short incubation periods

Back 26

common cold - 1-3 days
norovirus 1-2 days
cholera 0.5 - 4.5 days
influenza 1-3 days

Front 27

common diseases with long incubation periods

Back 27

chicken pox 14-16 days
5th disease 13-18 days (erythema infectiosum)
HIV 2-3 months or longer
mono 28-42 days (infectious mononucleosis)

Front 28

if we suspect a disease is occurring at a greater than endemic rate we ask:

Back 28

Who is being affected (demographics)
Where did the cases arise?
When did the disease occur?

Front 29

steps in investigating an acute outbreak (table 2-4)

Back 29

1. define the outbreak and validate the existence of an outbreak
a. define numerator cases - clincial features - disease known? serologic or cultural aspects? causes understood?
b. define denominator c. determine whether the observed # cases clearly exceeds expected
d. calculate attack rate

2. examine distribution of cases by time and place, looking for interactions
3. Look for combination/interaction of relevant variables
4. Develop a hypothesis based on existing knowledge of disease, analogy to diseases of known etiology, findings from investigation
5. test hypotheses
6. recommend control measures (current outbreak/prevention of future outbreaks)
7. prepare written report of investigation and findings
8. communicate findings to those involved in policy development and implementation and to the public.

Front 30

what are some sources of data about cases of disease?

Back 30

1. disease reporting (communicable disease registries, cancer registries)
2. insurance companies
3. public assistance and medical care plans
4. hospitals and clinics
5. pre-employment and periodic physical exams in industry and schools
6. absenteeism records
7. case-finding programs
8. military records
9. morbidity surveys on population samples

Front 31

5 approaches to describing prognosis

Back 31

1. case-fatality rate (CFR): denominator = deaths/ all sick cases
2. 5 year survival rate
3. observed survival rate
4. median survival time: length of time that 1/2 the population survives
5. relative survival time: ratio of survival time in sick / expected survival if disease absent.

Front 32

what is prognosis?

Back 32

describing the progress or outcome of the disease

(from time of diagnosis)

Front 33

prognosis: possible endpoints of disease

Back 33

death
cure
control
remission
recurrence

Front 34

what is the observed survival rate?

Back 34

observed survival rate is an estimate of the probability of surviving

Front 35

what is the five year survival rate?

Back 35

the proportion of those with disease still alive 5 years after diagnosis / all those diagnosed with disease 5 years ago (alive and dead)

Front 36

cumulative incidence rate

Back 36

# new cases of disease/ pop at risk at beginning of interval.

Front 37

what sorts of diseases are appropriate for description with CFR?

Back 37

cases that are short-term and acute, severe.

Front 38

incidence density

Back 38

most accurate

# new cases of disease / accurate population at risk throughout interval.

denominator is person-days or person-months, etc.
takes into account those who will not get disease twice, those who withdraw from pop, etc.
more accurate denominator

Front 39

relationship between incidence and prevalence

Back 39

P = I X D

prevalence = incidence X duration

Front 40

point prevalence

Back 40

(most common)

proportion of ind.s who have disease at given point in time

Front 41

period prevalence

Back 41

proportion of ind.s in spec. pop at risk who have the disease over a specified period of time.

(e.g., annual prevalence, lifetime prevalence)

Front 42

when does it make sense to consider incidence vs. prevalence?

Back 42

incidence rates are used to study a disease in question as it manifests in a pop. (etiology)

prevalence rates are used to measure societal burden (allocation of resources).

Front 43

3 sources of error in interview data

Back 43

-has disease and is unaware (so sxs)
-has disease and sxs, no med treatment and doesn't know name
-diagnosis not conveyed to person or person misunderstood
-memory problems
-involved in litigation about illness and alters response or chooses not to respond.
-coding or surveyor error
-biased interviewer
-selection bias (design)

Front 44

all-cause (crude) mortality rate

Back 44

all causes of death in a year/ population in that year

Front 45

cause-specific mortality rate (proportion)

Back 45

# deaths from specific cause in year / population (midpoint, because it fluctuates)

Front 46

case fatality rate (CFR)

Back 46

deaths from a specific disease / cases of specific disease

Front 47

proportionate mortality rate

Back 47

# deaths from specific cause / # deaths (all-cause)

Front 48

explain YPLL

Back 48

YPLL - years of potential life lost due to a disease.

calculated by determining the average life expectancy in pop and subtracting the age at death for an individual. adding all such individuals for a given year gives the total YPLL for a disease.

3 functions:
1. resource and research priorities
2. temporal trends in premature death
3. evaluating effectiveness of interventions

Front 49

when would you use direct age-adjustment? how?

Back 49

you would use direct age-adjustment when comparing populations that are different in their age distribution, making the overall mortality rates misleading in comparison.

you take the (existing) mortality rates for each specific age group and apply them to a standard population (age-distributed), then recalculate the mortality rate and compare.

Front 50

when would you use indirect age-adjustment (standardized mortality ratios)? how?

Back 50

used when total # deaths for age-specific stratum are not available.

estimate the age-specific population (using a known sample) for each age stratum.

use the cause-specific mortality rate for this age distribution in the general population.

calculate the expected # dead in each stratum given the gen. risk and est. pop.

we can then calc. the standardized mortality ratio:

observed # deaths (actual in sample)
___________________________________________ X 100

expected # deaths

an SMR of 100 would mean no increased risk.

Front 51

describe the kaplan-meir method

Back 51

uses the exact point in time when death occurred rather than prefixed intervals.
at participant death, new row is started

graphically, this can be seen as percent surviving on the y axis and time on the x axis with blocks as the body of the graph rather than a smooth line.