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Epidemiology > final content > Flashcards

final content Flashcards

1
Q

what is an infectious disease

A
  • cases are dependent on exposure to other cases
  • starts with exposure to a pathogen, then infection occurs, then disease MAY occur
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2
Q

infection vs disease

A

infection: established pathogen within the host
disease: the effects of an infection (clinical signs and symptoms)

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3
Q

latent vs incubation period

A

latent period: when host becomes infected to when they become infectious to others
incubation period: from when host becomes infected to when symptoms/clinical signs of disease show

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4
Q

what period is long for asymptomatic hosts

A

incubation period

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5
Q

what is a differential equation

A
  • a function measuring the change in one variable with respect to another
  • a system of differential equations is a set where each equation may or may not be dependent on other variables
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6
Q

a 3-state system for stages of a disease model

A

state 1: suceptible
state 2: infected
state 3: recovered

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7
Q

what does disease transmission depend on

A

the number/proportion of susceptible individuals AND the number/proportion of infectious individuals

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8
Q

generation time vs serial interval

A

generation time = time between infections in 1st and 2nd case
serial interval = time between symptoms of the 1st and second case

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9
Q

how to calculate serial interval

A

serial interval = latent period + (infectious period/2)

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10
Q

reproductive number (R) vs basic reproductive number (R0)

A

R = the average number of secondary infections caused by an initial infectious individual
R0 = the average number of secondary infections caused by an initial infectious individual in a completely susceptible population

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11
Q

basic reproductive number value interpretations

A

R0 > 1: epidemic
R0 = 1: endemic
R0 < 1: fadeout

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12
Q

how to calculate R0 for a SIR model

A

R0 = c x p x d
c = rate of contact
p = probability of transmutation given contact
d = duration of infectiousness

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13
Q

how do you calculate the critical proportion to vaccinate (Pc)

A

Pc = 1- (1/R0)
- as R0 increases more people must become vaccinated

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14
Q

how do you calculate the effective reproductive number

A

Re = R) x proportion susceptible

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15
Q

steps in building and analyzing a disease model

A
  1. define population and pathogen of interest
  2. construct a system of equations
  3. code the model and conduct numerical analysis
  4. assess the effect that interventions have on model outcomes
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16
Q

what interventions can be used to control disease

A
  • vaccination (full immunity)
  • reduce contact
  • reduce probability of infection given contact
  • reduce period of infectiousness
  • increase rate of recovery
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17
Q

why might we use mathematical models for disease control in epidemiology

A
  • ethical concerns for experimental studies
  • no disease present for observational studies
  • expensive and timely
  • to test “what if” scenarios
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18
Q

when would we use an experimental study instead of an observational study

A
  • prophylactic/preventative studies
  • therapeutic studies
  • management strategies
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19
Q

types of experimental studies

A
  1. lab based experiment: researchers create a controllable environment
  2. Randomized control trial: researcher creates groups in a “real-world” setting, no control over environment
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20
Q

pros and cons of lab-based experiments

A

pros: provides best control of manipulative conditions, reduces confounding, can be repeated
cons: lacks external validity, is unrealistic

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21
Q

pros and cons of randomized control trials

A

pros: best form of blinding, answers specific questions
cons: issues with ethics and costs

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22
Q

strongest to weakest strength evidence based research

A

systematic reviews > meta-analyses > blinded RTCs > cohort studies > case-control studies > case series > single case report

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23
Q

how do we conduct RTCs

A

take study population, divide into 2 treatment groups, determine who is O+ and O- from both groups

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24
Q

10 key aspects of conducting RTCs

A
  • clearly defined question
  • is it ethical to intervene?
  • what os the target population?
  • what groups are needed?
  • how are the groups created?
  • is there evidence of a challenge?
  • what are the outcomes?
  • how big of a study would you need?
  • how do we avoid bias in follow-up?
  • statistical analysis
25
Q

negative vs positive control group

A

negative: given nothing or a placebo
is it better than nothing?
positive: given the best possible current treatment
is it better than the old treatment?

26
Q

why are clinical trials stronger than case series

A

clinical trials include a comparative group

27
Q

what are cross-over studies

A
  • each individual is their own control
  • good for interventions that treat symptoms
  • mostly used for studying chronic diseases
28
Q

the number of subjects needed in a trial increases with…

A
  • smaller treatment effect (difference between groups)
  • larger variation among individuals
  • more covarieties
  • more groups
  • more clusters
  • longer duration
29
Q

types of blinding

A

single blinded: either subject, observer or data analyst are blinded
double blinded: 2 of the 3 are blinded
triple blinded: all 3 are blinded

30
Q

pros and cons of historical controls

A

pros: more practical/ethical, shorter duration
cons: recall bias

31
Q

what is a systematic review

A

a systematic approach to synthesize scientific evidence for a specific topic

32
Q

what is a meta-analyses

A

a statistical method used to combine the results of various studies in the systematic review - can’t do it without a systematic review first

33
Q

benefits of systematic reviews

A
  1. transparency
  2. many studies considered simultaneously
  3. can do meta-analyses
34
Q

limitations of systematic reviews

A
  1. garbage in, garbage out
  2. selection bias
  3. heterogeneity
  4. publication bias and inclusion of “grey literature”
35
Q

how do we measure disease frequency

A

counts: number of people with disease
proportions: number with disease divided by population size
rates: an expression of event occurrence in a defined population in a specified period of time (“per unit something”)

36
Q

what tool do we use to measure disease prevalence (existing cases)

A

proportions - ranges from 0-1
- only one measurement required

37
Q

how do you calculate point prevalence

A

with disease at a single point in time / # in population that COULD have disease at that point in time

38
Q

how do you calculate period prevalence

A

with disease during a specific time period / # in population that COULD have disease during that time period

39
Q

what is censoring

A

when observation is stopped for some reason, could be
- end of study
- individual left cohort
- lost to follow-up
- death

40
Q

why is prevalence NOT a measure of risk

A

it doesn’t take into account when the disease occurred - only tells us how many individuals are affected

41
Q

2 observations/tests required to measure incidence

A
  1. establishes which individuals are disease free
  2. identifies which ones developed disease in the observation period
42
Q

what are the 2 ways to measure incidence

A
  1. rate
  2. risk
    - the numerator is the same for both
    - denominator differs
43
Q

what is risk (aka cumulative incidence)

A
  • proportion of unaffected individuals who will develop the disease of interest over a specified time period
  • PROPORTION, range 0-1
44
Q

how do we calculate risk

A

of new cases during a time period / (initial # at risk - 1/2 withdrawals during that time period)

45
Q

what is rate (aka incidence density)

A
  • measures the average speed with which newly diagnosed cases of the disease develop
  • the denominator is the sum of units of time each individuals was at risk and observed
46
Q

2 ways to calculate rates

A

numerator is number of new cases for both
1. exact denominator: know exact details for each individual
2. approximate denominator: only have summary data

47
Q

calculating rate with exact denominator

A

of new cases in population surf specified time period / net time individuals in population ate at risk during that time

48
Q

calculating rate with the approximate denominator

A

of new cases in population during specified time period / ( 1/2 x (initial NAR - final NAR) x internal time component)

49
Q

what is an internal time component

A

time period in the denominator or rate calculations (e.g. person time)

50
Q

interpreting incidence rate

A

… cases per person-year (or whatever component of time you are using)

51
Q

general relationship between prevalence and incidence

A

prevalence is proportional to incidence x duration

52
Q

what is case fatality rate

A

proportion of individuals with a specific disease that die as a result of that during a given time period

of deaths among cases of x / # diagnosed cases of X

53
Q

what is attack rate

A

used in outbreak investigations

exposed people who got ill / total # exposed people

54
Q

what is an outbreak

A

when 2 or more cases meet the case definition with a common epidemiological link and onset of symptoms within the same time period

55
Q

steps involved in an outbreak investigation

A
  • confirm the outbreak
  • develop outbreak case definition
  • case identification and management
  • epidemiological analysis
  • reporting the outbreak
  • investigating potential exposures
  • implementing control measures
56
Q

what measures of association can we use to determine the most likely cause of an outbreak

A

odds ratio - generated from case-control studies
risk ratio - generated Fromm cohort studies
if OR or RR is > 1 then exposure increased the odds or risk of illness

57
Q

types of epidemic curves

A

point source: exposure from a single event, majority of cases in one incubation period
continuous source:ongoing exposure, not confined to one point in time
propagated source: spread of pathogen from one susceptible individual to multiple
intermittent source: exposure in spurts, is ongoing but intermittent

58
Q
A

Epidemiology (3 decks)

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