Epidemiology Flashcards

(92 cards)

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 variableโ€™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 canโ€™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 canโ€™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
โ€œof those who were positive, how many were picked up as positive?โ€

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25
What is specificity?
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?"
26
What is false positive rate?
1-specificity | Represents Type I error e.g. false positive
27
What is false negative rate?
1-sensitivity | Represents Type II error e.g. false negatives
28
Statistical power
1-B | = sensitivity
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What is Positive predictive value?
Number of true positives/Number of positive results | "Of those who tested positive, how many truly were positive?"
30
What is Negative predictive value?
Number of true negatives/Number of negative results | "Of those who tested negative, how many truly were negative?"
31
What is pre-test probability?
Prevalence of the disease
32
What is a likelihood ratio?
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.
33
Type I error
1 - specificity | False positive rate
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Type II error
1 - sensitivity | False negative rate
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What is post-test probability?
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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Positive likelihood ratio
sensitivity/(1-specificity)
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Negative likelihood ratio
(1-sensitivity)/specificity
38
Definition of an infectious disease
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
Prevalence =?
Incidence x duration
40
Incubation period
The time between exposure to an infectious agent and the onset of symptoms/signs of infection
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Latent period
Time period from successful infection until the development of infectiousness
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Infectious period
The time when infection can be transmitted to another susceptible host
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Serial interval
Time period between successive generations of a disease being spread from person to person
44
Infectivity
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
Basic reproductive ratio (R0)
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
Different R0 values
1 then there will be an epidemic | Assumes everyone in population is susceptible
47
Determinants of R0
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 = P*C*D
48
Determinants of disease outbreaks or epidemics
1. Number of people in that population who are susceptible | 2. Number of people who are immune
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Pathogenicity
The ability of a microbial agent to induce disease | Measured by attack rate
50
Attack rate
people at risk who get sick/total # at risk
51
Virulence
The severity of disease after infection occurs | Measured by case fatality ratio/proportion that develop severe disease
52
Immunogenicity
The ability of an organism to induce specific immunity
53
Premunition
Host response that protects against against high numbers of parasites (e.g. P. falciparum) without clearing the infection
54
Herd immunity
Threshold of number of immune people in community at which the likelihood of transmission is small enough to prevent an epidemic
55
Outbreak investigation
The study of a disease cluster or epidemic in order to control or prevent further spread of disease in a population
56
What is a cause?
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
Sufficient cause
The set of minimal conditions and events that inevitably produce disease in at least some people == complete causal mechanism
58
Component cause
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
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Necessary cause
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
Necessary AND sufficient cause
= Only one component cause e.g. rabies virus | Most causes of non-communicable diseases are neither necessary nor sufficient
61
3-step process in determining causation
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?
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Confounder
A third variable which confuses our assessment of the true association between exposure and outcome
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How to address confounding
- Study design: - -> Randomization - -> Matching - -> Restriction - Data analysis: - -> Measure confounders - -> Adjust for them through stratification or multivariate regression
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Strength of association
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
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Consistency
Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect
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Temporality
The effect has to occur after the cause!
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Bradford-Hill criteria
``` 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 ```
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Strengths of case-control study
``` 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
Weaknesses of case-control study
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
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Strengths of cross sectional study
Use of routinely available data - cheap Quick Useful preliminary study to identify factors and populations for further investigation with better method
71
Weaknesses of cross sectional study
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
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Strengths of RCTs
Reliable form of evidence | Can correct for bias, confounding, chance
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Weaknesses of RCTs
Limited external validity i.e. findings may not be generalisable High time and cost Potential for conflict of interest Potential for ethical breaches
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Strengths of cohort studies
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
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Weaknesses of cohort studies
Expensive to run Requires many years Participants are prone to loss-to-follow-up
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What is recall bias?
Systematic error caused by differences in the accuracy or completeness of recollections retrieved by study participants regarding past events
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Snowball sampling
Existing study subjects recruit future subjects from their acquaintances
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Purposive sampling
Have certain criteria
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Theoretical sampling
Using emerging theory in project to drive selection of new participants
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Triangulation
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
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Methodological triangulation
Different data collection techniques
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Investigative triangulation
Different researchers
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Data triangulation
Different data sources
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Theory triangulation
Different theories
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Why run a pilot study?
Is question measuring what it is intended to measure? Is wording understood? How do respondents feel about/react to questionnaire? Time taken
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Threats to validity of questionnaire
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
Face validity
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
Criterion validity
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
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Definition of epidemiology
The branch of medicine that deals with the incidence, distribution, and possible control of diseases and other factors relating to health
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Definition of demography
The study of statistics such as births, deaths, income, or the incidence of disease, which illustrate the changing structure of human populations
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Environmental burden of disease
Number of deaths and DALYs that can be attributed to environmental factors
92
How to calculate DALY/environmental burden of disease
DALY = # of people with disease x duration of disease (or loss of life expectancy) x severity (0=perfect health, 1=death)