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Public Health > Epidemiology > Flashcards

Epidemiology Flashcards

1
Q

What does a measure of effect do?

A

It summarises the strength of the relationship between exposure and outcome

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2
Q

Are prevalence ration, risk ratio and odds ratio absolute or relative measures of effect?

A

Relative

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3
Q

How to sample in a cross-sectional study?

A

Sample from study population

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4
Q

How to sample in a case-control study?

A

Sample from cases as well as controls

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5
Q

How to sample in a cohort study?

A

Sample a cohort of exposed and unexposed

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6
Q

Measures of effect in a cross-sectional study?

A

Prevalence ratio

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7
Q

Measures of effect in a case-control study?

A

Odds ratio

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8
Q

Measures of effect in a cohort study?

A

Risk ratio

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9
Q

Formula for prevalence ratio

What type of study does this apply to?

A

Prevalence in exposed group/Prevalence in unexposed group
= [a/(a+b)]/[c/(c+d)]
Cross-sectional

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10
Q

Formula for odds ratio

What type of study does this apply to?

A

Odds in exposed group/Odds in unexposed group
= { [a/(a+b)/[b/(a+b)] } / { [c/(c+d)]/[d/(c+d)] } = ad/bc
Case-control

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11
Q

Formula for risk ratio

What type of study does this apply to?

A

Risk in exposed group/Risk in unexposed group
= [a/(a+b)]/[c/(c+d)]
Cohort, randomised control trials

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12
Q

What does a relative measure of association do?

Examples?

A

Determines the strength of a variable’s relationship to an outcome. They give the relative effect of an exposure on disease occurrence.
Odds ratio, risk ratio, rate ratio

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13
Q

What does an absolute measure of association do?

Examples?

A

Determines how much of the disease can be attributed to the exposure.
Risk difference, rate difference, attributable fraction, number needed to treat

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14
Q

What does a risk ratio measure?

A

The risk of developing the disease (or event occurring) amongst exposed participants compared to the risk of developing the disease (or event not occurring) amongst the unexposed participants

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15
Q

What does the risk ratio mean?

A

RR = x, then those who are exposed are x times as likely to develop disease compared to those who are unexposed
RR = 1, there is no difference in risk for exposed and unexposed
RR>1, risk of disease is greater amongst the exposed than non-exposed (harmful exposure)
RR

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16
Q

What does an odds ratio measure?

A

The risk of having an outcome compared to the risk of not having an outcome. When performing a case-control study you start with the known outcomes and establish exposure. Case control studies can’t calculate incidence or prevalence.

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17
Q

Important points to remember about case-control studies

A
  • Percentage of population with disease can’t be calculated with this study design
  • -> Individuals with the disease have been oversampled
  • -> Try to get 1:1 ratio of cases:controls for comparison
  • -> Therefore, percentage of diseases participants is higher than in population, hence risk overestimating by generalising
  • The OR approximates the RR when the outcomes is rare
  • ->a Therefore, the lower the prevalence of a disease, the more similar the OR and RR will be in magnitude
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18
Q

What does OR/RR show us?

A

1 - exposure is harmful

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19
Q

Additional tidbits on OR and RR

A
  • OR and RR will always estimate in the same direction of association e.g. if RR >1, then OR will also be >1
  • The OR will always overstate the effect compared to the RR e.g. OR will be smaller when effect is 1
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20
Q

Formula for sensitivity

A

a/a+c

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21
Q

Formula for specificity

A

d/b+d

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22
Q

Formula for positive predictive value

A

a/a+b

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23
Q

Formula for negative predictive value

A

d/c+d

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24
Q

What is sensitivity?

A

The true positive rate. This measures the proportion of positive patients who were correctly identified (e.g. disease+test+ )
= true positive/condition positive
Useful for ruling out disease reliably
Low Type II error rate
“of those who were positive, how many were picked up as positive?”

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25
Q

What is specificity?

A

The true negative rate. This measures the proportion of negative patients who were correctly identified (e.g. disease-test-)
= true negative/condition negative
Useful for ruling in disease reliably
Low Type I error rate
“of those who were negative, how many were picked up as negative?”

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26
Q

What is false positive rate?

A

1-specificity

Represents Type I error e.g. false positive

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27
Q

What is false negative rate?

A

1-sensitivity

Represents Type II error e.g. false negatives

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28
Q

Statistical power

A

1-B

= sensitivity

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29
Q

What is Positive predictive value?

A

Number of true positives/Number of positive results

“Of those who tested positive, how many truly were positive?”

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30
Q

What is Negative predictive value?

A

Number of true negatives/Number of negative results

“Of those who tested negative, how many truly were negative?”

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31
Q

What is pre-test probability?

A

Prevalence of the disease

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32
Q

What is a likelihood ratio?

A

A tool used to assess the value of performing a diagnostic test. It uses sensitivity and specificity to determine whether a test result usefully changes the probability that a disease exists.

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33
Q

Type I error

A

1 - specificity

False positive rate

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34
Q

Type II error

A

1 - sensitivity

False negative rate

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35
Q

What is post-test probability?

A

Probability of the condition being present after the test
Calculated by multiplying Pre-test probability by likelihood ratio
When test is positive, post-test = PPV
When test is negative, post-test = 1-NPV

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36
Q

Positive likelihood ratio

A

sensitivity/(1-specificity)

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37
Q

Negative likelihood ratio

A

(1-sensitivity)/specificity

38
Q

Definition of an infectious disease

A

An illness due to a specific infectious agent or its toxic products that arises through transmission of that agent or its products from an infect person, animal or reservoir to a susceptible host, either directly or indirectly through an intermediate plant, host, vector of the inanimate environment

39
Q

Prevalence =?

A

Incidence x duration

40
Q

Incubation period

A

The time between exposure to an infectious agent and the onset of symptoms/signs of infection

41
Q

Latent period

A

Time period from successful infection until the development of infectiousness

42
Q

Infectious period

A

The time when infection can be transmitted to another susceptible host

43
Q

Serial interval

A

Time period between successive generations of a disease being spread from person to person

44
Q

Infectivity

A

The ability of an agent to cause infection in a susceptible host
Measured by: minimum number of infectious particles required to establish infection; proportion of susceptible people who develop infection after exposure

45
Q

Basic reproductive ratio (R0)

A

Average number of secondary cases from one primary case. This tells us how fast the infection is spreading
Primary case: individual who brings disease into population
Secondary case: people infection by primary case

46
Q

Different R0 values

A

1 then there will be an epidemic

Assumes everyone in population is susceptible

47
Q

Determinants of R0

A

P: Probability of transmission in a contact between infected and susceptible individuals
C: Frequency of contacts in the population/number of exposures of susceptible people to infectious partners per unit time
D: How long an infected person is infectious for

R0 = PCD

48
Q

Determinants of disease outbreaks or epidemics

A
  1. Number of people in that population who are susceptible

2. Number of people who are immune

49
Q

Pathogenicity

A

The ability of a microbial agent to induce disease

Measured by attack rate

50
Q

Attack rate

A

people at risk who get sick/total # at risk

51
Q

Virulence

A

The severity of disease after infection occurs

Measured by case fatality ratio/proportion that develop severe disease

52
Q

Immunogenicity

A

The ability of an organism to induce specific immunity

53
Q

Premunition

A

Host response that protects against against high numbers of parasites (e.g. P. falciparum) without clearing the infection

54
Q

Herd immunity

A

Threshold of number of immune people in community at which the likelihood of transmission is small enough to prevent an epidemic

55
Q

Outbreak investigation

A

The study of a disease cluster or epidemic in order to control or prevent further spread of disease in a population

56
Q

What is a cause?

A

An event, condition, characteristic or combination of these factors which plays an important role in producing the disease
Causality is the relationship between an event (cause) and a second event (effect), where the second event in understood as a consequence of the first

57
Q

Sufficient cause

A

The set of minimal conditions and events that inevitably produce disease in at least some people
== complete causal mechanism

58
Q

Component cause

A

One cause amongst a constellation of causes that make up a sufficient cause together. Factors that work together with the necessary cause to produce disease

59
Q

Necessary cause

A

A component cause which is a member of every sufficient cause for a given disease. This MUST be present for a disease to occur

60
Q

Necessary AND sufficient cause

A

= Only one component cause e.g. rabies virus

Most causes of non-communicable diseases are neither necessary nor sufficient

61
Q

3-step process in determining causation

A
  1. Is there an association? (measures of association)
  2. Is it a true association? (validity - exclude other reasons: chance, bias, confounding)
  3. Is the observed association likely to be a causal one?
62
Q

Confounder

A

A third variable which confuses our assessment of the true association between exposure and outcome

63
Q

How to address confounding

A
  • Study design:
  • -> Randomization
  • -> Matching
  • -> Restriction
  • Data analysis:
  • -> Measure confounders
  • -> Adjust for them through stratification or multivariate regression
64
Q

Strength of association

A

A small association doesn’t mean that there isn’t a causal effect, although the larger the association, the more likely that it is causal

65
Q

Consistency

A

Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect

66
Q

Temporality

A

The effect has to occur after the cause!

67
Q

Bradford-Hill criteria

A 
1 Strength of association
2 Biological plausibility
3 Consistency (reproducibility)
4 Dose-response relationship
5 Coherence (between epidemiological and lab findings)
6 Specificity
7 Temporality
8 Experiment
9 Analogy
68
Q

Strengths of case-control study

A 
Cheap
Easy to manage/arrange
Quick
Useful for studying rare diseases
Useful as a preliminary study when little is known about the relationship between a risk factor and a disease
69
Q

Weaknesses of case-control study

A

Observational - don’t have the same level of evidence as RCT
Prone to confounding
May be difficult to establish timeline of exposure to disease outcome

70
Q

Strengths of cross sectional study

A

Use of routinely available data - cheap
Quick
Useful preliminary study to identify factors and populations for further investigation with better method

71
Q

Weaknesses of cross sectional study

A

Routine data may not be designed to answer the set question
Data may not describe which variable is case and which is effect
Prone to confounding

72
Q

Strengths of RCTs

A

Reliable form of evidence

Can correct for bias, confounding, chance

73
Q

Weaknesses of RCTs

A

Limited external validity i.e. findings may not be generalisable
High time and cost
Potential for conflict of interest
Potential for ethical breaches

74
Q

Strengths of cohort studies

A

Can be used to identify causal relationships between variables
Can help identify risk factors for developing a disease
Recall error is reduced
Reliable data is produced - rank high in hierarchy of evidence
Can measure large variety of exposures

75
Q

Weaknesses of cohort studies

A

Expensive to run
Requires many years
Participants are prone to loss-to-follow-up

76
Q

What is recall bias?

A

Systematic error caused by differences in the accuracy or completeness of recollections retrieved by study participants regarding past events

77
Q

Snowball sampling

A

Existing study subjects recruit future subjects from their acquaintances

78
Q

Purposive sampling

A

Have certain criteria

79
Q

Theoretical sampling

A

Using emerging theory in project to drive selection of new participants

80
Q

Triangulation

A

Facts are supported by more than a single source of evidence. If you have used multiple sources but not triangulated the data, then you have analysed each source of evidence separately

81
Q

Methodological triangulation

A

Different data collection techniques

82
Q

Investigative triangulation

A

Different researchers

83
Q

Data triangulation

A

Different data sources

84
Q

Theory triangulation

A

Different theories

85
Q

Why run a pilot study?

A

Is question measuring what it is intended to measure?
Is wording understood?
How do respondents feel about/react to questionnaire?
Time taken

86
Q

Threats to validity of questionnaire

A

Cognitive factors: comprehension, literacy, recall bias
Situation and setting in which the measurement takes place: concerns over social desirability, non-participation, social norms, interviewer, privacy etc
Factors related to study design: detection bias (prospective study), bias in measuring exposure (case control), period effects (RCT and prospective)

87
Q

Face validity

A

The relevance is obvious
Content validity: all the relevant elements are included
Consensual validity: experts agree a measurement is valid

Some degree of face validity is required, but it can be deceptive, and where possible needs to be supported by criterion validity

88
Q

Criterion validity

A

Correlation between the measure and another variable, which is suitable for use as a criterion of validity e.g. scale measuring level physical activity can be validated by test of fitness
Ideal criterion is the true value
In real life, we use a measure which has been tested before and shown to have high criterion validity

89
Q

Definition of epidemiology

A

The branch of medicine that deals with the incidence, distribution, and possible control of diseases and other factors relating to health

90
Q

Definition of demography

A

The study of statistics such as births, deaths, income, or the incidence of disease, which illustrate the changing structure of human populations

91
Q

Environmental burden of disease

A

Number of deaths and DALYs that can be attributed to environmental factors

92
Q

How to calculate DALY/environmental burden of disease

A

DALY = # of people with disease x duration of disease (or loss of life expectancy) x severity (0=perfect health, 1=death)

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