Epidemiology — MCQs
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Secondary attack rate of mumps?
Which of the following statements about natural experiments is false?
A screening test has sensitivity of 90% and specificity of 99%. The prevalence of disease under investigation is 5 per 1000 population. What is the PPV of the given screening test?
What does the secondary attack rate measure?
What is the prevalence of Rheumatic Heart Disease (RHD) in India in the 5-15 years age group based on school-based screening studies?
Sensitivity of a screening test tells about
During investigation of an epidemic, the area is declared free of epidemic when?
Major reservoir of KFD?
Best indicator for spread of TB in a community?
What is the expected effect on incidence [I] and prevalence [P] when an effective treatment for a disease is introduced in a community?
Epidemiology Indian Medical PG Practice Questions and MCQs
Question 1711: Secondary attack rate of mumps?
- A. 95%
- B. < 50%
- C. 85%
- D. 75% (Correct Answer)
Explanation: ***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.
Question 1712: Which of the following statements about natural experiments is false?
- A. Researcher has no control over the allocation of subjects
- B. All are correct
- C. They utilize naturally occurring events or policy changes to approximate experimental conditions
- D. Includes Randomized controlled trials [RCTs] as an example of natural experiments. (Correct Answer)
Explanation: ***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.
Question 1713: A screening test has sensitivity of 90% and specificity of 99%. The prevalence of disease under investigation is 5 per 1000 population. What is the PPV of the given screening test?
- A. 10
- B. 70
- C. 33 (Correct Answer)
- D. 99
Explanation: ***33*** * **Positive Predictive Value (PPV)** = \[Sensitivity \times Prevalence] / \[(Sensitivity \times Prevalence) + (1 – Specificity) \times (1 – Prevalence)] * Here, 0.9 x 0.005 / \[(0.9 x 0.005) + (1-0.99) x (1-0.005)] = 0.0045 / \[0.0045 + (0.01 x 0.995)] = 0.0045 / \[0.0045 + 0.00995] = 0.0045 / 0.01445 ≈ 0.3114 or 31.14%. Converting to a percentage closest to the answer choices, it would be 33%. *10* * This value would be obtained if there was an error in calculating either the **prevalence** of the disease or the contribution of false positives to the total positive tests. * Inaccuracies in the formula or arithmetic would lead to results far from the correct PPV. *70* * This value suggests a much higher **prevalence** or a significantly lower number of **false positives** than indicated by the given sensitivity, specificity, and prevalence. * Such a high PPV is inconsistent with a low disease prevalence (0.5%) and a relatively high false positive rate (1-specificity = 1%). *99* * This value is close to the given **specificity**, which is the probability of a true negative test among individuals without the disease, not the PPV. * A PPV of 99% would be extremely high for a disease with a prevalence of 0.5% and would typically require a much higher specificity and/or sensitivity.
Question 1714: What does the secondary attack rate measure?
- A. The ability of a disease to spread from one person to another
- B. The proportion of susceptible people who become infected after exposure to a primary case (Correct Answer)
- C. The ability of a disease to cause death
- D. The rate at which a disease progresses in severity
Explanation: ***The proportion of susceptible people who become infected after exposure to a primary case*** - This is the **correct definition** of the **secondary attack rate (SAR)** - SAR = (Number of new cases among contacts of primary cases) / (Total number of susceptible contacts at risk) - It is typically measured within one incubation period after exposure - Commonly used to assess transmission in **households or closed populations** (schools, institutions, etc.) - Important measure of **communicability** of infectious diseases in real-world settings *The ability of a disease to spread from one person to another* - This broadly describes **transmissibility** or **infectivity** but is too general - The **basic reproductive number (R₀)** is the specific measure of disease spread in a fully susceptible population - SAR is more specific, measuring spread among actual contacts *The ability of a disease to cause death* - This describes **case fatality rate (CFR)** or **virulence** - CFR = (Number of deaths from disease) / (Total number of cases) × 100 - Completely different concept from secondary attack rate *The rate at which a disease progresses in severity* - This describes **disease progression** or **natural history** of disease - Not related to the secondary attack rate concept - SAR measures **spread between people**, not progression within an individual
Question 1715: What is the prevalence of Rheumatic Heart Disease (RHD) in India in the 5-15 years age group based on school-based screening studies?
- A. 1-2 per 1000
- B. 5-7 per 1000 (Correct Answer)
- C. 10-12 per 1000
- D. 13-15 per 1000
Explanation: ***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.
Question 1716: Sensitivity of a screening test tells about
- A. Percentage of individuals with the disease who test positive. (Correct Answer)
- B. Percentage of healthy individuals among those with a negative test result.
- C. Percentage of individuals with the disease among those with a positive test result.
- D. Percentage of healthy individuals among those with a positive test result.
Explanation: ***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.
Question 1717: During investigation of an epidemic, the area is declared free of epidemic when?
- A. Twice the incubation period of the disease since occurrence of the last case (Correct Answer)
- B. Thrice the incubation period of the disease since occurrence of the last case
- C. The longest incubation period for the disease
- D. Incubation period for the disease plus two standard deviations
Explanation: ***Twice the incubation period of the disease since occurrence of the last case*** - An epidemic is declared over when there have been no new cases for a period equal to **twice the maximum incubation period** of the disease. - This timeframe ensures that any individuals who might have been infected by the last known case would have developed symptoms (or completed their infectivity period) within this observation window. *Thrice the incubation period of the disease since occurrence of the last case* - This duration is **excessively long** and not the standard public health measure for declaring an epidemic free. - While it provides an even greater margin of safety, it is not the most **efficient or practical threshold** for public health interventions. *The longest incubation period for the disease* - Observing for only the **longest incubation period** is insufficient because a new case could still emerge at the very end of this period, potentially starting a new chain of transmission. - It does not account for the possibility of **secondary cases** occurring at the extreme end of the incubation period. *Incubation period for the disease plus two standard deviations* - This statistical measure is typically used to define the **range of normal variation** for biological data, not for epidemic declaration. - While it relates to the incubation period, it is **not the established public health standard** for determining the end of an epidemic.
Question 1718: Major reservoir of KFD?
- A. Human
- B. Squirrels (Correct Answer)
- C. Cattle
- D. Monkey
Explanation: ***Squirrels*** - **Squirrels** are considered a major reservoir for the Kyasanur Forest Disease (KFD) virus because they can carry the virus without showing severe symptoms themselves, allowing for viral persistence in nature. - The virus can be transmitted from infected squirrels to ticks, which then can spread the infection to other animals or humans. *Human* - Humans are considered **incidental hosts** for KFD, meaning they can become infected but do not typically play a significant role in maintaining the virus in nature. - While humans can experience severe disease, they do not serve as a reservoir for further transmission to other vectors or hosts. *Cattle* - **Cattle** are not typically considered a reservoir for the Kyasanur Forest Disease virus. - They can be exposed to KFD but are not known to sustain the viral cycle or transmit it effectively to ticks or other animals. *Monkey* - While KFD is often associated with **monkey deaths** (especially black-faced langurs and bonnet macaques), these animals are considered **amplifying hosts** rather than primary reservoirs. - Monkeys experience severe disease and high mortality, making them good indicators of viral activity but not long-term carriers for sustained transmission.
Question 1719: Best indicator for spread of TB in a community?
- A. Prevalence of infection
- B. Annual infection rate (Correct Answer)
- C. Incidence of new cases
- D. Case rate
Explanation: ***Annual infection rate*** - The **Annual Infection Rate (ARI)** is the gold standard indicator for measuring TB spread in a community - It measures the rate at which new TB infections occur in a tuberculin-negative population over one year - ARI directly reflects **recent transmission** and the force of infection in the community - WHO and Park's Textbook recommend ARI as the best epidemiological indicator for TB transmission - Calculated through tuberculin surveys showing conversion from negative to positive - An ARI of 1% indicates 1% of uninfected individuals become infected per year *Incidence of new cases* - Incidence measures new **disease cases** (active TB), not new infections - Only 5-10% of TB infections progress to active disease, often after years of latency - Incidence is affected by case detection rates, diagnostic capacity, and healthcare access - It underestimates actual transmission occurring in the community *Prevalence of infection* - **Prevalence** indicates total existing cases (both old and new) at a point in time - Influenced by both new infections and duration of infection/disease - Does not specifically measure the rate of ongoing transmission *Case rate* - **Case rate** refers to the number of active disease cases per population - Similar to prevalence, it doesn't isolate new transmission events - Less sensitive for detecting changes in transmission dynamics
Question 1720: What is the expected effect on incidence [I] and prevalence [P] when an effective treatment for a disease is introduced in a community?
- A. No change in P & I
- B. Both P & I will decrease
- C. P will decrease & I will increase
- D. P will decrease & I will remain the same (Correct Answer)
Explanation: ***P will decrease & I will remain the same*** - An effective treatment reduces the **duration of disease** by curing existing cases faster, which directly decreases **prevalence** (P = Incidence × Duration) - **Incidence** measures the rate of *new cases* occurring, which is unaffected by treatment of existing cases, so **incidence remains unchanged** - This is the fundamental epidemiological principle for treatment interventions *No change in P & I* - Incorrect because effective treatment shortens disease duration, which must reduce the number of existing cases at any given time - **Prevalence** will definitely decrease when cases recover faster *Both P & I will decrease* - While treatment correctly decreases **prevalence** by shortening disease duration, it does not prevent *new infections* from occurring - **Incidence** (new case rate) remains unchanged unless there's a preventive intervention like vaccination or behavioral change *P will decrease & I will increase* - Correctly identifies that **prevalence** decreases with effective treatment - However, there's no mechanism by which treatment would increase **incidence** of new cases - Treatment affects existing patients, not the rate of new infections
Practice by Chapter
Principles of Epidemiology
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Measures of Disease Frequency
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Epidemiological Study Designs
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Descriptive Epidemiology
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Analytical Epidemiology
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Experimental Epidemiology
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Screening for Disease
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Surveillance Systems
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Investigation of an Epidemic
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Association and Causation
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Modern Epidemiological Methods
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Critical Appraisal of Epidemiological Studies
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