Epidemiology Practice Questions

Q: Which of the following statements is true about cohort studies?

A study that measures the incidence of a disease.. ***A study that measures the incidence of a disease.*** - Cohort studies are **prospective studies** that follow a defined group of individuals over time to observe the development of diseases or health outcomes [1]. - By following an at-risk population and documenting new cases, they can directly calculate the **incidence rate** of a disease [1]. - This is the **primary strength** of cohort studies - they provide the best epidemiological evidence for disease incidence. *A study that describes characteristics of a population.* - This describes **descriptive studies** or **cross-sectional surveys**, which characterize a population at a single point in time. - While cohort studies may initially describe baseline characteristics, their primary purpose is to observe disease occurrence over time, not just description. *A study that follows participants over time to observe outcomes but does not measure incidence.* - This is **contradictory** - the act of following participants over time and observing new disease cases IS the measurement of incidence [1]. - Incidence (new cases per unit of person-time) is precisely what cohort studies are designed to measure. *A study that can determine cause and effect.* - While cohort studies establish **temporal relationships** (exposure precedes outcome) and provide strong evidence for causality, the word "determine" is too absolute. - Establishing definitive causation requires **multiple lines of evidence**, including criteria like biological plausibility, dose-response relationships, and consistency across studies. - **Randomized controlled trials** provide stronger causal evidence due to randomization eliminating confounding.

Q: Which of the following correctly describes the components of the epidemiological triad?

Agent, host, environment. **Agent, host, environment** * The **epidemiological triad** is a classic model that describes the interrelationships contributing to disease development. * It consists of the **agent** (the causative factor), the **host** (the organism contracting the disease), and the **environment** (extrinsic factors influencing exposure and susceptibility). * *Time, place, person (descriptive epidemiology)* * **Time, place, and person** are key components of **descriptive epidemiology**, used to characterize disease patterns. * While important for understanding disease distribution, they do not represent the causative interconnectedness of the epidemiological triad. * *Disease, prevention, treatment (healthcare process)* * **Disease, prevention, and treatment** describe aspects of the healthcare process and public health interventions. * They are not the fundamental components used to explain the *occurrence* of disease as modeled by the epidemiological triad. * *Agent, disease, vector (lacks host and environmental components)* * This option includes the **agent** and a **vector** (which is a type of environmental factor or can be considered part of the agent's transmission). * However, it misses the crucial component of the **host** and fully encompassing the broader **environment**.

Q: Secondary attack rate of mumps?

75%. ***75%*** - The **secondary attack rate** for mumps is approximately **75%**, indicating its high transmissibility among susceptible household contacts. - This high rate underscores the importance of vaccination to prevent spread in close-contact settings. *85%* - While mumps is highly contagious, an 85% secondary attack rate is generally considered too high and not reflective of typical epidemiological data. - This percentage is more commonly associated with diseases like measles, which has an even higher transmissibility. *95%* - A 95% secondary attack rate is characteristic of highly contagious diseases like **measles**, which transmit very efficiently even in short, casual contacts. - Mumps, while highly infectious, does not typically reach this level of secondary attack rate. *< 50%* - A secondary attack rate of less than 50% would suggest lower transmissibility than what is observed for mumps. - Diseases with lower secondary attack rates are generally less prone to rapid outbreaks among close contacts.

Q: Sensitivity of a screening test tells about

Percentage of individuals with the disease who test positive.. ***Percentage of individuals with the disease who test positive*** - **Sensitivity** measures the ability of a test to correctly identify individuals who *have* the **disease**. - It's calculated as (True Positives / (True Positives + False Negatives)) * 100, representing the **true positive rate**. *Percentage of healthy individuals among those with a negative test result* - This describes the **negative predictive value (NPV)**, which is the probability that a person who tests negative truly does not have the disease. - NPV is crucial for ruling out disease in a population. *Percentage of individuals with the disease among those with a positive test result* - This is the definition of **positive predictive value (PPV)**, indicating the probability that a person who tests positive truly has the disease. - PPV is important for confirming a diagnosis in clinical practice. *Percentage of healthy individuals among those with a positive test result* - This describes 1 minus the positive predictive value, or the rate of **false positives** among those who test positive. - A high rate here means many healthy individuals are incorrectly identified as having the disease.

Q: What is the prevalence of Rheumatic Heart Disease (RHD) in India in the 5-15 years age group based on school-based screening studies?

5-7 per 1000. ***Correct: 5-7 per 1000*** - School-based screening studies focusing on the 5-15 years age group in India reveal a prevalence of **rheumatic heart disease (RHD)** ranging from **5 to 7 per 1000** children. - This prevalence highlights the significant public health burden of RHD within this vulnerable age demographic in India. - Multiple echocardiographic screening studies across different regions of India consistently report this range as the average prevalence. *Incorrect: 1-2 per 1000* - This range is generally considered too low for the true prevalence of RHD in school-aged children in India, as documented by multiple studies. - It might represent prevalence rates in regions with very strong primary prevention programs or different demographic groups. - Underestimates the actual disease burden in the Indian context. *Incorrect: 10-12 per 1000* - While higher than the actual average, this range is typically considered an overestimate for the general prevalence of RHD in this age group from school-based screenings in India. - Such high numbers might be seen in extremely high-risk or specific endemic areas but do not represent the national average. *Incorrect: 13-15 per 1000* - This range is significantly higher than the reported average prevalence of RHD in school-based screening studies in India. - This would indicate an alarmingly widespread and uncontrolled incidence of RHD, which is not supported by current epidemiological data. - May represent historical data from decades ago or specific high-risk pockets rather than current national estimates.

Q: Which of the following statements about natural experiments is false?

Includes Randomized controlled trials [RCTs] as an example of natural experiments.. ***Includes Randomized controlled trials [RCTs] as an example of natural experiments*** - This statement is **false** because **Randomized Controlled Trials (RCTs)** are a form of **experimental study design** where researchers actively intervene and randomly assign participants to treatment or control groups. - In contrast, **natural experiments** capitalize on naturally occurring events or policies that create exposure groups without direct researcher intervention. - RCTs are the gold standard for experimental studies, while natural experiments are a type of **observational study** that mimics experimental conditions. *Researcher has no control over the allocation of subjects* - This statement is **true** and accurately describes a key characteristic of **natural experiments**. - The exposure or intervention is determined by nature, policy changes, or external circumstances, not by the researcher. - The lack of researcher control over allocation is what fundamentally differentiates natural experiments from true experimental designs like RCTs. *They utilize naturally occurring events or policy changes to approximate experimental conditions* - This statement is **true** and describes the fundamental principle of natural experiments. - Examples include studying health effects of smoking bans, natural disasters, or policy implementations that create "treatment" and "control" groups naturally. - These studies leverage real-world variations to draw causal inferences. *All are correct* - This statement is **false** because the option "Includes RCTs as an example of natural experiments" is definitively incorrect.

Q: In the context of epidemiology, standardization is most important for which of the following distributions?

Age distribution. ***Age distribution*** - **Standardization** (e.g., age adjustment) is crucial when comparing health outcomes or disease rates between populations with different **age structures**. - This method removes the confounding effect of age, allowing for a more accurate comparison of underlying risk factors or disease incidence. *Sex distribution* - While sex can influence disease prevalence, its distribution is generally less variable and confounding than age when comparing populations, making standardization for sex less universally critical than for age. - Differences in sex distribution can still be accounted for, but often through direct stratification rather than complex standardization methods. *Disease distribution* - **Disease distribution** itself is what we often aim to measure and compare, rather than a characteristic necessitating standardization to understand other variables. - Standardization techniques are applied to demographic features (like age or sex) to understand their impact on disease distribution, not to the disease distribution itself. *None of the options* - This option is incorrect because **age distribution** is a primary factor where standardization is essential in epidemiology to ensure valid comparisons. - Ignoring age differences when comparing populations can lead to misleading conclusions about disease risk or health statuses.

Question 1

During investigation of an epidemic, the area is declared free of epidemic when?

Accepted Answer

Twice the incubation period of the disease since occurrence of the last case

Answer

Thrice the incubation period of the disease since occurrence of the last case

Answer

The longest incubation period for the disease

Answer

Incubation period for the disease plus two standard deviations

Question 2

Which of the following statements is true about cohort studies?

Accepted Answer

A study that measures the incidence of a disease.

Answer

A study that follows participants over time to observe outcomes but does not measure incidence.

Answer

A study that describes characteristics of a population.

Answer

A study that can determine cause and effect.

Question 3

What is the primary difference between descriptive and analytic studies in epidemiology?

Accepted Answer

Descriptive studies do not test hypotheses but generate them.

Answer

Analytic studies test hypotheses about relationships between health outcomes and exposures.

Answer

Descriptive studies are always retrospective while analytic studies are prospective.

Answer

Descriptive studies describe the distribution of health outcomes in a population.

Question 4

Which of the following correctly describes the components of the epidemiological triad?

Accepted Answer

Agent, host, environment

Answer

Agent, disease, vector

Answer

Time, place, person

Answer

Disease, prevention, treatment

Question 5

Secondary attack rate of mumps?

Accepted Answer

75%

Answer

95%

Answer

< 50%

Answer

85%

Question 6

Sensitivity of a screening test tells about

Accepted Answer

Percentage of individuals with the disease who test positive.

Answer

Percentage of healthy individuals among those with a negative test result.

Answer

Percentage of individuals with the disease among those with a positive test result.

Answer

Percentage of healthy individuals among those with a positive test result.

Question 7

What is the prevalence of Rheumatic Heart Disease (RHD) in India in the 5-15 years age group based on school-based screening studies?

Accepted Answer

5-7 per 1000

Answer

1-2 per 1000

Answer

10-12 per 1000

Answer

13-15 per 1000

Question 8

Which of the following statements is true regarding the iceberg of disease?

Accepted Answer

The tip of the iceberg represents the clinical cases.

Answer

Screening is primarily done for the tip of the iceberg.

Answer

Hypertension is a classical example of the iceberg of disease.

Answer

The clinician is primarily concerned with the hidden portion of the iceberg.

Question 9

Which of the following statements about natural experiments is false?

Accepted Answer

Includes Randomized controlled trials [RCTs] as an example of natural experiments.

Answer

Researcher has no control over the allocation of subjects

Answer

All are correct

Answer

They utilize naturally occurring events or policy changes to approximate experimental conditions

Question 10

In the context of epidemiology, standardization is most important for which of the following distributions?

Accepted Answer

Age distribution

Answer

Sex distribution

Answer

Disease distribution

Answer

None of the options

Epidemiology — MCQs

Epidemiology — MCQs

On this page

Practice by Chapter

Want unlimited practice?