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Epidemiology > Epi Final > Flashcards

Epi Final Flashcards

1
Q

Routine reporting for healthcare facilities and labs, cases present themselves over time.

A

Passive Surveillance

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2
Q

Example case scenario: passive surveillance

A

admitted patient testing positive for Covid-19

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3
Q

Public health researchers and clinicians seek out new cases

A

Active surveillance

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4
Q

Example case scenario: active surveillance

A

John Snow going from house to house to ask questions regarding cholera outbreak

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5
Q

Innate immunity, immunity through antibodies from another person or animal. Short duration

A

passive immunity

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6
Q

case scenario

A

baby born with antibodies from mother

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7
Q

immunity via vaccines, teaches body how to identify and ward off pathogens. longer duration, best for herd immunity

A

active immunity

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8
Q

person to person transmission, close proximity to one another

A

direct contact

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9
Q

direct contact examples

A

kissing, mother to baby via placenta or breastmilk

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10
Q

transmission via food, air, water, vector or vehicle

A

indirect transmission

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11
Q

non-living, inanimate object that carries infectious agents, vehicle born

A

fomite

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12
Q

how much potential agent can cause damage to the host

A

virulence

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13
Q

ability to spread to adjacent tissues

A

invasiveness

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14
Q

ability to cause damage to host cells

A

pathogenic potential

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15
Q

ability to infect, multiply and spread to new hosts

A

infectivity

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16
Q

Incidence rate equation

A

(# of new cases over period of time)/(average population at risk during same time) x 100,000

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17
Q

two epidemiological rates for open populations

A

incidence rate, incidence density

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18
Q

Incidence density equation

A

(# of new cases over specific period of time)/(person time)

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19
Q

sum total of all time contributed by all subjects

A

person time

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20
Q

measures the rate in which new cases of a health outcome develop in a population within a specific time

A

incidence

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21
Q

two epidemiological rates for closed populations

A

crude attack rate, cumulative incidence

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22
Q

Crude attack rate equation

A

(# ill with health outcome)/(total # of people at event) x100

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23
Q

cumulative incidence equation

A

(# of new cases over study’s time period)/(study’s sample at risk)

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24
Q

proportion of people who have the disease (existing and new cases) over a given period of time

A

prevalence

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25
Q

health outcomes that occur at a particular point in time relative to a specific population

A

point prevalence

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26
Q

heath outcomes that occur within a specific population over a period of time

A

period prevalence

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27
Q

does incidence depend on prevalence or vice versa?

A

prevalence depends on incidence

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28
Q

crude/annual death rate equation

A

(# of deaths from all causes in given year)/(total population) x100,000

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29
Q

disease specific death rate equation

A

(# of deaths due to certain disease)/(total population) x100,000

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30
Q

case fatality rate equation

A

(# of deaths due to disease)/(# of cases of disease) x100,000

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31
Q

age adjusted death rate equation

A

(# of deaths in age group)/(total population of age group) x100,000

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32
Q

maternal mortality rate equation

A

(# of deaths due to childbirth)/(total # live births) x100,000

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33
Q

infant mortality rate equation

A

(# of infant deaths)/(# of live births) x100,000

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34
Q

screening that focuses on high risk groups

A

selective screening

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35
Q

selective screening case scenario

A

screening for prostate cancer among individuals with a family history

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36
Q

screening of the population regardless of risk status

A

mass screening

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37
Q

mass screening case scenario

A

screening for Covid-19

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38
Q

Pros and cons of mass screening

A

pro: prevents mass onset/diagnosis of specific diseases
cons: expensive

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39
Q

pros and cons of selective screening

A

pros: less expensive
cons: can be challenging to get participation

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40
Q

concluding that something is true when it is false

A

false positive

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41
Q

concluding that something is false when it is actually true

A

false negative

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42
Q

reject the null hypothesis when we should fail to reject the null hypothesis

A

type 1 error, false positive

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43
Q

failing to reject the null hypothesis when we should reject the null hypothesis

A

type 2 error, false negative

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44
Q

a patient testing positive and having the disease

A

true positive

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45
Q

the proportion of diseased individuals who were correctly identified as positive, ability to identify who has the disease

A

sensitivity

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46
Q

sensitivity equation

A

of true positives/ total with disease

47
Q

95% of the individuals with the disease are screened as true positives while the remaining 5% are true negatives

A

95% sensitivity

48
Q

a patient testing negative and not having the disease

A

true negative

49
Q

proportion of non-diseased individuals who were correctly identified as negative, the ability to correctly identify who does not have the disease

A

specificity

50
Q

specificity equation

A

of true negatives/ total # without the disease

51
Q

the probability that a patient with a positive test will have the disease

A

positive predictive value

52
Q

as prevalence increases, positive predictive value ______

A

increases

53
Q

the probability that a patient with a negative test will not have the disease

A

negative predictive value

54
Q

as prevalence decreases, negative predictive value ______

A

increases

55
Q

no evidence of disease, preclinical phase (no genetic changes or agent interaction with host), primary prevention (vaccines, health education)

A

pre-pathogenesis

56
Q

potential signs and evidence of disease, subclinical phase (changes in genetic makeup, host has been exposed), secondary prevention (screening)

A

pathogenesis

57
Q

disease is present, clinical phase (diagnosis of disease by physician), tertiary prevention (rehab, surgery)

A

late pathogenesis

58
Q

answers who, where, and when

A

observational studies

59
Q

exposures and risk factors assessed at group level, clusters (neighborhoods, hospitals, cities, states, countries)

A

ecological studies

60
Q

pros and cons of ecological studies

A

pro: understanding disease occurrence across groups
cons: ecological fallacy (assuming association is the same for population and individual levels)

61
Q

accounts of a single of small number of patients with various signs, symptoms, and health outcomes

A

case report

62
Q

pros and cons of case report

A

pro: beneficial for observing symptoms among patients
cons: small number of individuals and effectiveness of treatment difficult to determine

63
Q

case report scenario

A

exploring the side effects of a patient given a new drug for their asthma

64
Q

ecological study scenario

A

assessing the occurrence of fatty liver disease between Nevada and Arizona

65
Q

larger collection of cases among patients with a common characteristic

A

case series

66
Q

pros and cons of case series

A

pro: can be linked to other health data, can help generate hypotheses based on collection of cases
con: obtaining information for specific cases among multiple patients can be time consuming

67
Q

case series scenario

A

what is the average length of time that stroke patients admitted into the hospital stay before they are discharged?

68
Q

an observational study that involves looking at data from a population at one specific point in time (measuring exposure and outcome at the same time)

A

cross-sectional study

69
Q

pros and cons cross sectional study

A

pro: no wait time for disease to occur in population, assessing existing number of cases within population
con: not suitable for rare or highly fatal diseases, cannot determine if exposure preceded disease

70
Q

age, sex, race/ethnicity, religion, health conditions, etc.
beneficial for utilizing characteristics that better define the population

A

person variables

71
Q

regional differences within a nation that may affect prevalence and incidence of disease
climate, latitude, rural vs urban, county, neighborhood, state, country

A

place variables

72
Q

gradual changes in the occurrence of disease over long periods of time
chronic illnesses

A

secular trends

73
Q

what effects secular trends?

A

diagnostic techniques of diseases, changes in disease incidence rates (accuracy of denominator)

74
Q

increases and decreases in the frequency of a disease or other phenomenon over a period of several years or within a year
allergies in spring, URI in winter, car accidents in rainy months

A

cyclic trends

75
Q

focuses on the why and the how

A

analytical epidemiology

76
Q

compare the number of people who have disease with number of those who do not. starts with disease and looks in the past for exposure variables.

A

retrospective case control study

77
Q

pros and cons of case control study

A

pro: determines temporality (does exposure come before outcome), inexpensive, fast, does not need large study sample
con: recall bias, participant bias

78
Q

individuals recruited in study are disease free at beginning, but have known exposure status

A

cohort study

79
Q

exposed and non-exposed groups are known at the beginning of the study, moves forward in time. also known as longitudinal study

A

prospective cohort study

80
Q

pros and cons retrospective cohort study

A

pros: information is immediately available
cons: recall bias, accuracy of records may be flawed, tracing subjects can be challenging

81
Q

pros and cons prospective cohort study

A

pros: measure multiple health outcomes within a single study
cons: difficult to measure multiple exposures in single study, and for assessing rare or uncommon diseases, drop offs (drop out before end of study), more expensive and time consuming

82
Q

These two professionals combined prospective and retrospective cohort studies regarding smoking

A

Doll and Hill

83
Q

researcher is aware of the status of the disease at start of study.
beneficial for uncommon diseases
can only study one disease

A

case control study

84
Q

researcher is aware of the status of the exposure at the start of the study.
beneficial for common diseases.
can study multiple diseases

A

cohort study

85
Q

this study measures odd ratio

A

case control

86
Q

this study measures relative risk

A

cohort study

87
Q

designed to assess the effectiveness/safety of medical treatments and education.
subjects randomly assigned to control or test group
participants chosen randomly
intervention controlled by the investigator

A

randomized controlled study

88
Q

pros and cons of randomized controlled study

A

pros: equal chance of being selected, greatly reduces biases (selection, information, confounding), facilitates blinding
cons: groups may have different # of participants, more time and money, groups may not reflect entire population, dropouts/loss of follow up, drop-ins

89
Q

group members can remain within start group or switch through process known as crossover design (washout period must occur to reduce side effects)

A

crossover randomized controlled study

90
Q

study conducted with means of avoiding researcher bias

A

blinding or masking randomized controlled study

91
Q

participant is unaware of what group they belong to

A

single blinded

92
Q

participant and researcher are unaware of what group they belong to

A

double blinded

93
Q

clinicians, data collectors, and analysts are all

A

triple blinded

94
Q

pros and cons of blinding/masking randomized controlled trial

A

pros: minimizes bias
cons: costly and time consuming

95
Q

9 steps and phases of randomized controlled trials

A

1: Preclinical
2: drug is approved for testing in humans
3: phase 1 (20-80 participants)
4: phase 2 (100-300 participants)
5: phase 3 (1,000-3,000 participants)
6: drug submitted for FDA approval
7: FDA review to confirm safety and effectiveness
8: drug is approved
9: phase 4 (1,000+ participants)

96
Q

steps for completing randomized controlled trial

A

1: decide objective and phase of the study
2: decide who members of study population will be and how they will be recruited
3: choose blinding method

97
Q

any quantity that can have different values across individuals or study units that are associated with one another

A

variables

98
Q

if value of one variable increases, the value of the other increases

A

positive association

99
Q

if the value of one variable increases, the value of the other decreases

A

negative association

100
Q

measuring the odds of exposure among cases and controls

A

odds ratio

101
Q

odds of the exposure among cases are greater than the odds among the controls

A

odds ratio greater than 1

102
Q

odds of the exposure among cases are the same as the odds among controls

A

odds ratio equal to one

103
Q

odds of the exposure among cases are less than the odds among controls, protective factor (individual is not at risk of being diagnosed with disease)

A

odds ratio less than one

104
Q

what does an odds ratio of 1.62 mean?

A

the odds of smoking is approx. 1.62 times higher among CHD cases compared to non-CHD cases

105
Q

what does an odds ratio of 0.62 mean?

A

the odds of smoking is 38% (1-0.62) less likely among CHD cases compared to non-CHD cases

106
Q

the ratio of incidence rate of the disease within the exposed group compared to the ratio of incidence rate of disease within the non-exposed group

A

relative risk

107
Q

relative risk equation

A

(A/A+B)/(C/C+D)

108
Q

exposure variable is a risk factor for the disease

A

relative risk greater than 1

109
Q

there is no association between the exposure variable and the disease

A

relative risk equal to 1

110
Q

the exposure variable decreases the risk of the disease, protective effect

A

relative risk less than 1

111
Q

relative risk of 1.38 means?

A

risk of developing CHD is 1.38 times higher among smokers than non-smokers

112
Q

incidence rate in the exposed group minus the incidence in non-exposed group

A

attributable risk

113
Q

how would you interpret an attributable risk of 10.6?

A

10.6 of the incidence cases of CHD can be contributed to smoking

Epidemiology (1 decks)

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