Epidemiology

Question 1

Incidence risk

Answer 1

Definition: Probability of new cases occurring in a defined population over a specific period.
Formula: IncidenceRisk = NewCases/
PopulationatRisk

Example: If 50 out of 1,000 people develop flu in a year, the incidence risk is 50/ 1000 = 0.05 or 5%

Question 2

Case control study

Answer 2

Definition: Observational study that compares individuals with a disease (cases) to those without (controls) to identify risk factors.
Example: Investigating smoking history in lung cancer patients (cases) and comparing it to non-patients (controls).

Question 3

Cohort study

Answer 3

Definition: Observational study that follows a group exposed to a risk factor and a group not exposed to compare incidence of disease.
Example: Following smokers and non-smokers over time to study the incidence of lung cancer in each group.

Question 4

Incidence rate

Answer 4

Definition: Rate at which new cases occur in a population per unit of time.
Formula: Incidence Rate = New Cases / Person-Time at Risk
Example: In a study with 100 person-years of observation, 20 new cases of a disease yield an incidence rate of 20 / 100 = 0.2 cases per person-year.

Question 5

Prevalence

Answer 5

Definition: Proportion of a population with a disease at a given point in time.
Formula: Prevalence = Existing Cases / Total Population
Example: If 100 out of 1,000 people in a community have diabetes, the prevalence is 100 / 1000 = 0.1 or 10%.

Question 6

Incidence

Answer 6

Definition: Refers to the number of new cases of a disease in a population during a specific period.
Formula: Incidence = Count of New Cases Over Time
Example: If a city has 200 new flu cases in January, the incidence is 200 for that month.

Question 7

Sensitivity

Answer 7

Definition: Proportion of true positives correctly identified by a test.
Formula: Sensitivity = True Positives / (True Positives + False Negatives)
Example: If a COVID test correctly identifies 90 out of 100 infected individuals, sensitivity is 90 / 100 = 0.9 or 90%.

Question 8

Specificity

Answer 8

Definition: Proportion of true negatives correctly identified by a test.
Formula: Specificity = True Negatives / (True Negatives + False Positives)
Example: If a COVID test correctly identifies 95 out of 100 healthy individuals, specificity is 95 / 100 = 0.95 or 95%.

Question 9

Negative predictive value

Answer 9

Definition: Probability that individuals with a negative test truly do not have the disease.
Formula: NPV = True Negatives / (True Negatives + False Negatives)
Example: If 150 out of 160 people with a negative COVID test are truly disease-free, NPV is 150 / 160 = 0.9375 or 93.75%.

Question 10

10. Positive Predictive Value (PPV)

Answer 10

Definition: Probability that individuals with a positive test truly have the disease.
Formula: PPV = True Positives / (True Positives + False Positives)
Example: If 80 out of 100 people with a positive COVID test actually have COVID, PPV is 80 / 100 = 0.8 or 80%.

Question 11

Odds ratio

Answer 11

Definition: The odds that an event occurs in one group compared to the odds of it occurring in another group, often used in case-control studies.
Formula: Odds Ratio = (A / B) / (C / D) = (A × D) / (B × C)

Question 12

Risk ratio

Answer 12

Definition: The risk of an event occurring in the exposed group compared to the risk in the unexposed group, commonly used in cohort studies.
Formula: Risk Ratio = (A / (A + B)) / (C / (C + D))

Question 13

Categorical data - which test

Answer 13

Chi squared

Question 14

Continuous - normally distributed - which test

Answer 14

Mean and standard deviation
T test

Question 15

Continuous - skewed - which test

Answer 15

Median and interquartile range
Mann Whitney U test

Question 16

Outbreak management response (10)

Answer 16

1. Quantify new cases and clarify whether this is actually an outbreak
2. Case definition
3. Assemble a team: lab staff for diagnostics, epidemiologists, clinicians, nurses, infection prevention team, pharmacists
4. Active case finding
5. Case surveillance and plot an outbreak curve
6. Develop hypotheses
7. Review hypotheses
8. Implement control and prevention measures
9. Communicate findings
10. Institute surveillance

Question 17

Point source outbreak

Answer 17

Curve goes up to a peak and then back down
Same exposure and same source with a brief exposure period
(e.g. Legionnaire’s)

Question 18

Extended common source

Answer 18

Goes up and down in peaks like a wave (reflecting the incubation period with each peak)
Caused by an ongoing source of infection
Not caused by spread between people
For example cholera from a water source

Question 19

Propagated source

Answer 19

Multiple waves, which cumulatively builds over time
Characterised by person to person transmission
e.g. Covid

Question 20

Intermittent source

Answer 20

Comes and goes in bursts, with some time free of cases in between
e.g. contaminated food which is interemittently opened/distributed like listeria in canned salmon

Question 21

What is the definition of an outbreak?

Answer 21

Occurence of more cases of an adverse health event than expected

in a given geographic area over a particular period of time

Question 22

What are the aims of an outbreak response?

Answer 22

1. Protect public health
2. Identify the source
3. Prevent further spread by implementing control measures

Question 23

Common causes of AKI in LMIC

Answer 23

1. Sepsis - consider TB/HIV
2. Dehydration/hypoperfusion
3. Obstruction
4. Intraparenchymal renal disease

Question 24

Why is AKD important in LMIC and how is it different?

Answer 24

1. Common
2. Patients are young
3. Often severe
4. Most commonly caused by infections and hypoperfusion
5. Preventable and treatable in many cases