09-11-21 - Introduction to Epidemiology Flashcards

1
Q

Learning outcomes

A
  • Define selected basic epidemiological terms (i.e. mortality rate, incidence, prevalence, patterns of outcome occurrence, outcomes, exposures
  • Describe the need to consider time, place, and person in epidemiological enquiry.
  • Define and calculate prevalence and incidence, and factors that can alter the such measures
  • Describe and differentiate exposures and outcomes in epidemiological enquiry.
  • Describe the hierarchy of evidence, and differentiate the various epidemiological study designs
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2
Q

What is epidemiology the study of?

A

• Epidemiology is the study of distribution and determinants of health-related states or events in a specified population, and the application of this study to control of health problems

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3
Q

What is mortality rate?

What is mortality rate typically measured in?

What are infection fatality rates?

What is infection rate?

What is Ro?

How does Ro affect the spread of disease?

What are 4 factors that affect Ro?

A
  • Mortality rate is an estimate of the portion of a population that dies during a specific time period
  • Infection fatality rate (IFR) is the proportion of cases of a specified condition that die divided by total infected people
  • Infection rate is the rate at which an infection spreads within a population
  • Ro is the basic reproduction number, which specifies the number of cases that potentially be infected by one case, where everybody is susceptible
  • Spread of disease is less likely when Ro<1, and is more likely when Ro>1, the larger the Ro, the harder it is to control the spread of disease

• Ro is not a biological constant, and is influences by:

1) People’s behaviour
2) Infectiousness cases
3) Pathogen virulence
4) Environment

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4
Q

What is typical units for mortality?

How can mortality be expressed as a %?

How can this be expressed to give mortality per 100,000?

A
  • Mortality is typically given in deaths per 1000 individuals per years
  • Mortality per 100,000 can be used by scaling the denominator and numerator up to 100,000
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5
Q

What does 10,000 person years mean?

What is needed to follow up?

A

• 10,000 person years can mean:

1) 10,000 people for 1 years
2) 5,000 people for 2 years
3) 2,000 people for 5 years

• An n-year follow up is needed to differentiate between these e.g 5-year mortality of 10 deaths per 10,000 people would mean 2 deaths per 2,000 for 5 years

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6
Q

What is incidence rate?

How can this be calculated and expressed per 100,000?

A

• Incidence is the number of new cases over a certain period of time

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7
Q

What is prevalence?

How can prevalence rate in both cases be calculated?

A

• Prevalence is the proportion of a population that has a disease:

1) At a specified time – e.g 1% of population has COPD in 2010
2) Over a certain period – e.g lifetime prevalence of dementia is 40%

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8
Q

How can incidence and prevalence be defined?

What are they each useful for?

A

1) Incidence
• A rate or a proportion
• Useful for identifying causes of disease
• By definition, only occurs in those without the disease

2)	Prevalence 
•	A proportion 
•	Useful for identifying disease burden 
•	Useful for planning services 
•	Depends partly upon incidence
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9
Q

What are the 5 different patterns of outcomes occurrence?

A

1) Sporadic
• Occasional cases occurring irregularly

2) Endemic
• Persistent background levels of occurrence (low to moderate levels)

3) Outbreak
• Greater than excepted cases of endemic levels
• One case in a new area can be regarded as an outbreak
• Turns into epidemic if not controlled

4) Epidemic
• Occurrence in excess of expected level for a given period of time
• Disease spreads rapidly over large geographical areas

5) Pandemic
• Epidemic occurring in or spreading over more than 1 continent

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10
Q

What are the 6 different outcomes?

A

1) Death
2) Hospitalization
3) First diagnosis with a disease
4) Recurrence (e.g cancer)
5) Quality of life
6) Surrogates (e.g blood pressure, lung function, etc)

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11
Q

What are the 3 different kinds of exposure?

A

• 3 different kinds of exposure:

1) Non-modifiable exposure – e.g age, sex, phenotype
2) Modifiable exposure – Smoking, weight, diet, alcohol consumption
3) Interventions – drug therapy, surgery, lifestyle advice

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12
Q

How is risk calculated?

How is relative risk calculated?

How is relative risk reduction (RRR) calculated?

How is absolute disk reduction calculated?

How is number needed to treat calculated?

A
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13
Q

What is a confidence interval?

What does a wider confidence interval mean?

A
  • A confidence interval is a range of plausible values, with values near the limits being less plausible
  • A wider confidence interval means there is a greater uncertainty
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14
Q

What can be used with the greatest chance to influence clinical practise?

A

• Systemic reviews and meta-analysis are at the top of the hierarchy of evidence, and are the most likely to influence clinical practise

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15
Q

What are the 3 steps of a cross-sectional study?

A

1) Sample a population

2) Estimate the proportion of:
• Different exposures
• Different signs/symptoms
• Different outcomes

3) Use data:
• To describe the prevalence/burden
• To explore associations

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16
Q

What are the 5 steps of a case-control study?

A

1) Select cases with an outcome
2) Select controls without the outcomes
3) Explore exposures in cases and control
4) Compare exposures in cases and controls
5) Identify associations

17
Q

What are the 4 steps of a cohort study?

A

1) Select people without an outcome
2) Classify according to an exposure

3) Follow up:
• Prospective (before outcome of interest has been obtained)
• Retrospective (after outcome of interest has been obtained)

4) Compare risk of disease in exposed and unexposed

18
Q

What are the 2 steps of a random controlled trial (RCT)

A

1) Random allocation
• Intervention
• Control/comparator

2) Compare risk of outcome in intervention and control groups

19
Q

What are the objectives and time-frame of these 4 study designs?

A
20
Q

What is a confounding variable?

What does confounding lead to?

What is an example?

A
  • A confound variable is a third variable that influences both the independent (variable that is changed – influences the dependent variable) and dependent (thing that is measured) variables
  • Confounding leads to the true relationship between the independent and dependent variables being confused
  • Measuring how season/weather affects murder rate
  • Number of ice creams sold positively correlates with murder rate
  • Correlation does not equal causation
21
Q

What is bias?

What does bias lead to?

A

• Bias is a systematic error in:

1) What data is collected
2) How data is collected
3) How data is analysed
4) How data is interpreted
5) How data is reported

• Bias leads to the wrong conclusions concerning:

1) Effectiveness
2) Causation

22
Q

How are levels of the hierarchy of evidence affected by confounding and bias?

A