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Quizzes > Health & Medicine > Diseases & Conditions

Epidemiology Questions Quiz: Test Your Expertise

Brush up with our epidemiology practice quiz - sharpen your skills now!

Difficulty: Moderate
2-5mins
Learning OutcomesCheat Sheet
Paper art illustration showing layered virus icons charts and lab equipment on coral background for epidemiology quiz

Use this epidemiology quiz to practice incidence rates, risk factors, attack rates, and outbreak investigations. You'll solve brief cases, get instant feedback, and spot gaps before an exam or field exercise. Then try a warm‑up quiz or explore bonus public health trivia for a quick refresh.

Which measure refers to the proportion of a population that has a disease at a specific point in time?
Case fatality rate
Prevalence
Incidence rate
Attack rate
Prevalence represents the proportion of individuals in a population who have the disease at a specific time or period, capturing both new and existing cases. This is distinct from incidence, which only accounts for new cases. Prevalence helps to understand the overall burden of disease and is often used in planning healthcare resources.
How is cumulative incidence best defined?
Total person-time of observation
New cases during a period divided by population at risk at start
Existing cases at one point in time
New cases per person-time
Cumulative incidence is calculated by dividing the number of new cases of disease during a specific time period by the population at risk at the start of that period. It provides a measure of risk in a cohort over a defined period. This is different from incidence density, which accounts for person-time.
Which measure uses person-time in the denominator to account for varying follow-up times?
Prevalence
Attack rate
Cumulative incidence
Incidence density
Incidence density (or incidence rate) uses person-time in the denominator, allowing for varying follow-up durations among participants. It is calculated as new cases divided by total person-time at risk. This approach is useful when subjects enter and leave a study at different times or are lost to follow-up.
In which study design are participants classified based on exposure status and followed over time to assess disease occurrence?
Cohort study
Case-control study
Cross-sectional study
Ecological study
A cohort study identifies participants based on exposure status (exposed vs unexposed) and follows them prospectively to compare incidence of outcomes. This design allows for direct calculation of incidence and relative risk. It is powerful for establishing temporal relationships.
Which study design selects participants based on disease status and looks back to assess exposures?
Case-control study
Randomized controlled trial
Cross-sectional study
Cohort study
In a case-control study, cases with the disease and controls without are selected, then past exposures are assessed. This design is efficient for rare diseases and can estimate odds ratios. It cannot directly calculate incidence but is useful for hypothesis generation.
Which design assesses exposure and disease status at a single point in time?
Case-control study
Randomized trial
Cross-sectional study
Cohort study
A cross-sectional study measures exposure and outcome simultaneously in a population at one point in time. It is used to assess prevalence and associations but cannot establish temporality. It is often quick and less expensive than longitudinal designs.
What term describes any attribute, characteristic, or exposure that increases the likelihood of developing a disease?
Confounder
Exposure
Risk factor
Incidence
A risk factor is any characteristic or exposure that is associated with an increased probability of a disease outcome. Identifying risk factors helps in prevention and control strategies. Observational studies often aim to detect and quantify these associations.
Which term describes a disease prevalence that is constant in a population over time?
Epidemic
Outbreak
Pandemic
Endemic
An endemic disease is one that is consistently present at a baseline level in a population within a geographical area. It indicates a steady state without large fluctuations. Examples include malaria in certain regions.
When a disease occurs at a higher-than-expected rate in a population, it is called a/an:
Epidemic
Endemic
Outbreak
Pandemic
An epidemic occurs when the incidence of a disease rises significantly above the expected baseline within a population or area. It may be localized or widespread. Control measures focus on identifying sources and interrupting transmission.
Which term is used when an epidemic spreads across multiple countries or continents?
Outbreak
Epidemic
Pandemic
Endemic
A pandemic is an epidemic that has spread over several countries or continents, usually affecting a large number of people. It implies global disease spread. Examples include the 2009 H1N1 influenza pandemic.
What is an outbreak?
A sudden increase in cases of a disease in a limited area
Worldwide spread of a new disease
Disease always present at steady levels
Unrelated, sporadic cases
An outbreak is characterized by a sudden rise in the number of disease cases in a specific place and time. It can be limited to a small community or region. Rapid investigation aims to identify sources and implement control measures.
Which surveillance system relies on regular, systematic collection of case reports from healthcare providers?
Passive surveillance
Active surveillance
Syndromic surveillance
Sentinel surveillance
Passive surveillance depends on health facilities and providers to report cases of disease to public health authorities routinely. It is less resource-intensive but may underreport cases. Despite limitations, it is widely used for national disease monitoring.
Which surveillance method involves actively seeking out cases through contacting providers and laboratories?
Active surveillance
Passive surveillance
Retrospective surveillance
Cross-sectional surveillance
Active surveillance involves proactive case finding by health authorities, including regular contact with healthcare providers and laboratories. It yields more complete and timely data but is resource-intensive. It is often used during outbreaks or for monitoring vaccine-preventable diseases.
What is the attributable risk?
Population prevalence minus incidence
Odds of exposure among cases
Proportion of disease in exposed due to exposure
Rate ratio in unexposed
Attributable risk (risk difference) is the difference in incidence between exposed and unexposed groups. It represents the proportion of disease among the exposed that is due to the exposure. This measure helps in quantifying public health impact if exposure is eliminated.
How is the population attributable risk percent interpreted?
Risk in exposed divided by risk in unexposed
Person-time at risk ratio
Proportion of all disease in population due to exposure
Odds of disease in unexposed
The population attributable risk percent indicates the proportion of cases in the entire population that can be attributed to a specific exposure. It helps set priorities by estimating the impact of removing the exposure. Calculation uses both incidence in exposed and unexposed, and the prevalence of exposure.
Under what condition does the odds ratio approximate the relative risk?
When exposure is common
When sample size is small
When the disease is rare
In cohort studies
When the disease outcome is rare (usually <10% incidence), the odds ratio from a case-control study approximates the relative risk. This is called the rare disease assumption. In common diseases, OR can overestimate the RR.
What best describes a confounding variable?
Independent predictor of the outcome only
Random error in measurement
Associated with both exposure and outcome, not in the causal pathway
A mediator between exposure and disease
A confounder is related to both the exposure and the outcome without being an intermediate step in the causal pathway. It can distort the true association. Controlling confounding is essential in study design or analysis.
Which bias occurs when participants self-select into a study based on exposure or outcome?
Selection bias
Observer bias
Information bias
Confounding
Selection bias arises when the study sample is not representative because of how participants are chosen or self-select. This can occur if exposure influences participation. It threatens internal validity by distorting associations.
Which bias is introduced by systematic differences in data collection methods between groups?
Confounding
Information bias
Lead-time bias
Selection bias
Information bias (measurement bias) occurs when there are systematic inaccuracies in the measurement of exposures or outcomes. It can be differential or non-differential. Proper instrument calibration and standardized protocols reduce this bias.
What is sensitivity of a diagnostic test?
Proportion of true positives in all positives
Probability test is negative when disease not present
Probability test is positive when disease is present
Overall accuracy of the test
Sensitivity is the ability of a test to correctly identify individuals who have the disease (true positives). A highly sensitive test minimizes false negatives. It is crucial in screening when missing a disease has serious consequences.
What is specificity of a diagnostic test?
Prevalence of disease
Proportion of false positives
Probability test is negative when disease is absent
Probability test is positive when disease is present
Specificity measures a test's ability to correctly identify those without disease (true negatives). A highly specific test minimizes false positives. It is important where unnecessary treatment carries risks.
Which is the positive predictive value (PPV)?
Probability disease is absent when test negative
Probability disease is present when test positive
1 minus false positive rate
Test sensitivity multiplied by prevalence
PPV is the probability that a person has the disease given a positive test result. It depends on both test specificity/sensitivity and disease prevalence. PPV increases as prevalence rises.
What does a 95% confidence interval represent?
Probability that null hypothesis is true
Range where true value lies with 95% certainty over repeated samples
Standard error of the estimate
Range containing 95% of data points
A 95% confidence interval means that if the study were repeated multiple times, 95% of the calculated intervals would contain the true parameter. It provides both an estimate and its precision. It is not the probability the true value lies within the single observed interval.
What is effect modification?
When the association between exposure and outcome differs across levels of a third variable
When a confounder distorts the exposure-outcome association
Systematic error in measurement
Bias from non-random sampling
Effect modification occurs when the strength or direction of an exposure - outcome association changes across strata of a third variable. Identifying it can reveal subgroups with different risks. It is a biological interaction, not bias, and should be reported.
Which level of evidence is highest for determining causality?
Ecological studies
Cross-sectional studies
Randomized controlled trials
Case series
Randomized controlled trials (RCTs) are considered the gold standard for causal inference because randomization minimizes confounding. They provide high internal validity. Observational studies rank lower due to potential biases.
What is the ecological fallacy?
Assuming individual-level associations from group-level data
Misclassification of exposure
Bias from loss to follow-up
Error in randomization
The ecological fallacy occurs when inferences about individuals are drawn from aggregate data for groups. Associations seen at the group level may not hold for individuals. Caution is required when interpreting ecological studies.
Which method estimates survival functions and accounts for censored data?
Chi-square test
Kaplan-Meier estimator
Linear regression
Logistic regression
The Kaplan-Meier estimator is used to estimate survival probabilities over time, accommodating censored observations. It provides a stepwise survival curve. It is foundational in time-to-event analysis.
What does a hazard ratio of 2.0 indicate in a survival analysis?
Risk difference is 2 per 100
Median survival time doubled
Event rate is twice as high in the treatment group compared to control
Survival at 2 years is double
A hazard ratio (HR) of 2.0 means that at any point in time, the event rate in the exposed or treatment group is twice that of the control group. It is an instantaneous risk comparison. HRs derive from Cox proportional hazards models.
In meta-analysis, what does high I-squared (I²) indicate?
Low risk of bias
Substantial heterogeneity among study results
Large sample sizes
High publication bias
I² quantifies the proportion of variability in effect estimates due to heterogeneity rather than chance. High I² (e.g., >75%) suggests substantial heterogeneity. Investigators may explore sources or use random-effects models.
Which model assumes a single true effect size shared by all studies?
Bayesian hierarchical model
Mixed-effects model
Random-effects model
Fixed-effects model
A fixed-effects meta-analysis model assumes that all studies estimate the same underlying effect size, and observed differences are due to chance. It is appropriate when heterogeneity is low. Random-effects allow for between-study variation.
Which regression technique assesses time to event data while adjusting for covariates?
Cox proportional hazards model
Linear regression
Logistic regression
Poisson regression
The Cox proportional hazards model estimates the effect of covariates on the hazard of an event occurring, without specifying the baseline hazard function. It is widely used for survival data. The proportional hazards assumption must be tested.
What does the basic reproduction number (R0) represent?
Time between successive cases in an outbreak
Incubation period duration
Average number of secondary cases from a primary case in a susceptible population
Proportion of population immune
R0 is the expected number of new infections generated by one case in a fully susceptible population. If R0>1, an outbreak can grow; if <1, it will decline. Understanding R0 helps guide control measures.
Which curve plots sensitivity versus 1-specificity for different test thresholds?
Survival curve
Kaplan-Meier plot
Dose-response curve
ROC curve
A receiver operating characteristic (ROC) curve displays the trade-off between sensitivity and specificity across threshold values. The area under the curve (AUC) measures overall test accuracy. It helps choose optimal cut-offs.
What is the secondary attack rate?
Rate of new cases in population over time
Proportion of susceptible contacts who become infected after exposure to a primary case
Proportion of cases that are fatal
Prevalence among exposed group
Secondary attack rate measures the spread of disease in a defined group of susceptibles after contact with a primary case. It estimates person-to-person transmissibility in close settings. It is essential for outbreak investigations.
What statistical method can adjust for multiple confounders when estimating incidence rate ratios?
Chi-square test
Poisson regression
Wilcoxon signed-rank test
Log-rank test
Poisson regression models count data and rates, allowing adjustment for multiple covariates when estimating incidence rate ratios. It accounts for person-time offset. It is widely used in cohort studies.
What is the purpose of directed acyclic graphs (DAGs) in epidemiology?
To perform survival analysis
To visually represent causal assumptions and identify confounding paths
To calculate sample size for studies
To measure disease prevalence
DAGs are graphical tools that represent assumed causal relationships among variables and help identify confounders, mediators, and colliders. They guide adjustment strategies to avoid bias. Their use improves study design and analysis.
Which approach uses genetic variants as instrumental variables to infer causal effects?
Case-crossover study
Mendelian randomization
Interrupted time series
Ecological study
Mendelian randomization leverages random allocation of alleles at conception to assess causal relationships between exposures and outcomes. Genetic variants serve as proxies for modifiable risk factors. This reduces confounding and reverse causation.
What is multilevel modeling used for in epidemiologic research?
To calculate incidence rates
To account for data clustered at different hierarchical levels
To perform time-series analysis
To impute missing data
Multilevel (hierarchical) models handle data structured in clusters (e.g., patients within hospitals), allowing for random effects at each level. They account for intra-cluster correlation and provide accurate standard errors. They are essential when outcomes may vary by context.
In outbreak investigations, what is the case definition?
Protocol for laboratory testing only
List of all exposures investigated
Standard criteria for person, place, time, and clinical features to classify cases
Study design outline
A case definition specifies clinical criteria (signs, symptoms, lab tests) and limits by time, place, and person to identify whether an individual is a case. It ensures consistency during an outbreak investigation. A clear definition improves data accuracy.
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Study Outcomes

  1. Understand Core Epidemiology Concepts -

    Master definitions of incidence, prevalence, risk factors, and outbreak investigations as presented in our epidemiology questions quiz.

  2. Calculate Incidence, Prevalence, and Risk Metrics -

    Accurately compute and interpret measures like incidence rates, relative risk, and odds ratios based on real-world quiz data.

  3. Interpret Outbreak Investigation Findings -

    Analyze scenario-based questions to identify disease sources, transmission patterns, and effective control measures.

  4. Analyze Risk Factors Using Quiz Scenarios -

    Examine associations between exposures and outcomes to assess causality and potential confounders.

  5. Evaluate Epidemiologic Study Designs -

    Compare cohort, case - control, and cross-sectional designs to understand their strengths and limitations in public health research.

  6. Apply Evidence-Based Public Health Strategies -

    Develop targeted intervention proposals and preventive measures informed by instant feedback from the epidemiology practice quiz.

Cheat Sheet

  1. Incidence vs. Prevalence -

    According to CDC definitions, incidence measures new cases per population-time (IR = new cases/person-time), while prevalence captures all existing cases at a specific point (cases/population). Remember the mnemonic "PIN": Prevalence Is a Number snapshot, Incidence Needs time. Mastering this distinction is key for epidemiology questions on both incidence rates and disease burden in any epidemiology trivia questions set.

  2. Risk Ratio (RR) and Odds Ratio (OR) -

    Per standard epidemiology texts, the Risk Ratio (RR = incidence_exposed/incidence_unexposed) quantifies relative risk in cohort studies, while the Odds Ratio (OR = (a/c)/(b/d)) is central to case-control designs. A quick tip: if OR≈RR when disease is rare (prevalence <10%), you can approximate one from the other. Knowing these formulas inside-out will boost your confidence in any epidemiology practice quiz or public health quiz scenario.

  3. Key Epidemiological Study Designs -

    Referencing guidelines from WHO and leading universities, understand the four pillars: descriptive (who, what, when, where), analytic (cohort, case-control), experimental (randomized trials), and ecological studies. Use the "DEAR" mnemonic (Descriptive, Ecologic, Analytic, Randomized) to recall study types. Solid grasp of design strengths and limitations is often tested in an epidemiology quiz and sharpens your real-world outbreak analysis.

  4. Outbreak Investigation Steps -

    Follow the standard seven steps defined by CDC: prepare, verify, define cases, describe data, hypothesize, test hypothesis, implement control. The phrase "People Vexed Delay Defining Hard Theories" can help you remember "Prepare, Verify, Define, Describe, Hypothesize, Test, Implement." This structured approach is a staple of outbreak scenario questions in epidemiology trivia questions.

  5. Interpreting an Epidemic Curve -

    Per WHO outbreak guidelines, plot cases over time to distinguish point-source, continuous common-source, and propagated outbreaks based on curve shape. For example, a sharp peak suggests point-source, while multiple peaks indicate person-to-person spread. Mastering curve patterns is essential for quickly answering epidemiology quiz visuals and outbreak timeline questions.

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