lesson 3

Question 1

Front: What are the three main objectives of analyzing surveillance data?

Answer 1

Back: 1. Describe data to collect based on the surveillance system’s objective.
2. Identify how to present surveillance data.
3. Interpret surveillance data, including trends and patterns.

Question 2

Front: Name the six categories of surveillance data.

Answer 2

Back: Identifying, Demographic, Clinical, Laboratory, Risk Factor, Source.

Question 3

Front: Why is confidentiality important in surveillance data?

Answer 3

Back: It protects individuals’ privacy and ensures ethical data handling.

Question 4

Front: What are two ways to maintain confidentiality in surveillance systems?

Answer 4

Back: 1. Assign unique ID numbers instead of personal identifiers.
2. Avoid unintentional disclosure of sensitive information.

Question 5

Front: What does “completeness” mean in data quality?

Answer 5

Back: It refers to how much of the required data is available and whether all events are captured.

Question 6

Front: Give an example of missing data in surveillance.

Answer 6

Back: If 10% of respondents did not report their age, the dataset has missing age data.

Question 7

Front: What is data validity?

Answer 7

Back: It refers to the accuracy and correctness of the collected data.

Question 8

Front: Name two sources of error that affect data validity.

Answer 8

Back: 1. Incorrect information provided by respondents.
2. Errors in data entry or recording.

Question 9

Front: What are the three core epidemiologic attributes used to describe data?

Answer 9

Back: Person (who?), Place (where?), and Time (when?).

Question 10

Flashcard 10

Front: What are some ways to present surveillance data?

Answer 10

Back: Tables, graphs, charts, and maps.

Question 11

Front: Give an example of how “place” is used in surveillance data.

Answer 11

Back: Mapping disease prevalence by residence, workplace, or exposure site.

Question 12

Front: Why is analyzing trends over time important in surveillance?

Answer 12

Back: It helps identify seasonal patterns, outbreaks, and long-term health trends.

Question 13

Front: What are modifiable risk factors?

Answer 13

Back: Risk factors that individuals can change, such as smoking or physical inactivity.

Question 14

Front: What are non-modifiable risk factors?

Answer 14

Back: Factors that cannot be changed, such as age, genetics, and sex.

Question 15

Front: What is underreporting in surveillance data?

Answer 15

Back: Failure to report health conditions or vital events due to unawareness or system limitations.

Question 16

Front: Give an example of underreporting.

Answer 16

Back: A doctor does not report a notifiable disease due to lack of awareness of reporting requirements.

Question 17

Front: What is representativeness in data quality?

Answer 17

Back: How accurately the data reflects the occurrence and distribution of a disease in a population.

Question 18

Front: What factors can affect data representativeness?

Answer 18

Back: Exclusion of subpopulations, changes in reporting practices, and inconsistent case definitions.

Question 19

Front: Why are case definitions important in public health surveillance?

Answer 19

Back: They standardize data collection, ensuring consistency across reporting systems.

Question 20

Front: What happens if case definitions change over time?

Answer 20

Back: It may lead to misleading trends or apparent changes in disease prevalence.

Question 21

Front: How does the International Classification of Diseases (ICD) help in surveillance?

Answer 21

Back: It provides standardized criteria to classify health conditions and compare data across countries.

Question 22

Front: What is an alert threshold in surveillance?

Answer 22

Back: A predefined level at which a disease’s case count signals a potential outbreak.

Question 23

Front: Give an example of an alert threshold.

Answer 23

Back: More than five cases of bloody diarrhea in one location within a day may indicate an outbreak.

Question 24

Front: What is a 5-year moving average in data analysis?

Answer 24

Back: The average number of cases over five years to identify trends and detect anomalies.

Question 25

Front: What is the formula for calculating an incidence rate?

Answer 25

Back: \text{Incidence Rate} = \frac{\text{Number of cases} \times 100,000}{\text{Total population}}

Question 26

Front: How can surveillance data be used for advocacy?

Answer 26

Back: By informing policies, targeting resources, and evaluating public health interventions.

Question 27

Front: What is a surveillance bulletin?

Answer 27

Back: A regular report that shares surveillance findings with stakeholders.

Question 28

Front: What should be included in a surveillance bulletin?

Answer 28

Back: Summary, methods, epidemiological data (time, place, person), outbreaks, and conclusions.

Question 29

Front: How does surveillance help in public health decision-making?

Answer 29

Back: It provides data to detect trends, assess interventions, and guide resource allocation.

Question 30

Front: What are three common challenges in surveillance data analysis?

Answer 30

Back: Underreporting, lack of representativeness, and changing case definitions.