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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

Ready to dive into the world of disease detection and control? Our Ultimate Epidemiology Questions Quiz challenges public health pros to master incidence rates, risk factors, and outbreak investigations. In this interactive epidemiology practice quiz, you'll apply key concepts and get real-time feedback on your strengths and knowledge gaps. Engage with realistic scenarios and epidemiology trivia questions that refine your outbreak response and exposure assessment skills. From calculating attack rates to analyzing surveillance data, you'll sharpen your ability to spot risk factors and implement control measures. Take the challenge by trying our epidemiology quiz now, and explore bonus public health trivia questions to sharpen your public health quiz skills. Jump in and boost your expertise today!

Which measure refers to the proportion of a population that has a disease at a specific point in time?
Incidence rate
Prevalence
Attack rate
Case fatality 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. CDC: Measures of Disease Frequency
How is cumulative incidence best defined?
New cases during a period divided by population at risk at start
Existing cases at one point in time
Total person-time of observation
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. WHO: Cumulative Incidence
Which measure uses person-time in the denominator to account for varying follow-up times?
Cumulative incidence
Prevalence
Incidence density
Attack rate
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. CDC: Incidence Rate
In which study design are participants classified based on exposure status and followed over time to assess disease occurrence?
Cross-sectional study
Cohort study
Case-control 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. Health Knowledge: Cohort Studies
Which study design selects participants based on disease status and looks back to assess exposures?
Cohort study
Cross-sectional study
Case-control study
Randomized controlled trial
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. CDC: Case-Control Studies
Which design assesses exposure and disease status at a single point in time?
Cross-sectional study
Cohort study
Case-control study
Randomized trial
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. BMJ: Cross-sectional studies
What term describes any attribute, characteristic, or exposure that increases the likelihood of developing a disease?
Incidence
Exposure
Risk factor
Confounder
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. WHO: Risk Factors
Which term describes a disease prevalence that is constant in a population over time?
Epidemic
Endemic
Pandemic
Outbreak
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. WHO: Disease Endemicity
When a disease occurs at a higher-than-expected rate in a population, it is called a/an:
Outbreak
Endemic
Pandemic
Epidemic
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. CDC: Epidemics
Which term is used when an epidemic spreads across multiple countries or continents?
Endemic
Epidemic
Pandemic
Outbreak
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. WHO: Pandemic Basics
What is an outbreak?
A sudden increase in cases of a disease in a limited area
Disease always present at steady levels
Worldwide spread of a new disease
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. CDC: Outbreak Investigation
Which surveillance system relies on regular, systematic collection of case reports from healthcare providers?
Passive surveillance
Active surveillance
Sentinel surveillance
Syndromic 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. CDC: Surveillance Systems
Which surveillance method involves actively seeking out cases through contacting providers and laboratories?
Passive surveillance
Active surveillance
Cross-sectional surveillance
Retrospective 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. WHO: Surveillance Systems
What is the attributable risk?
Proportion of disease in exposed due to exposure
Odds of exposure among cases
Rate ratio in unexposed
Population prevalence minus incidence
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. CDC: Measures of Association
How is the population attributable risk percent interpreted?
Proportion of all disease in population due to exposure
Risk in exposed divided by risk in unexposed
Odds of disease in unexposed
Person-time at risk ratio
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. WHO: Population Attributable Fraction
Under what condition does the odds ratio approximate the relative risk?
When the disease is rare
When exposure is common
In cohort studies
When sample size is small
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. NIH: Rare Disease Assumption
What best describes a confounding variable?
Associated with both exposure and outcome, not in the causal pathway
A mediator between exposure and disease
Independent predictor of the outcome only
Random error in measurement
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. CDC: Confounding
Which bias occurs when participants self-select into a study based on exposure or outcome?
Information bias
Selection bias
Confounding
Observer bias
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. CDC: Selection Bias
Which bias is introduced by systematic differences in data collection methods between groups?
Selection bias
Information bias
Confounding
Lead-time 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. WHO: Bias in Epidemiology
What is sensitivity of a diagnostic test?
Probability test is positive when disease is present
Probability test is negative when disease not present
Proportion of true positives in all positives
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. CDC: Sensitivity & Specificity
What is specificity of a diagnostic test?
Probability test is negative when disease is absent
Probability test is positive when disease is present
Proportion of false positives
Prevalence of disease
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. CDC: Sensitivity & Specificity
Which is the positive predictive value (PPV)?
Probability disease is present when test positive
Probability disease is absent when test negative
Test sensitivity multiplied by prevalence
1 minus false positive rate
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. CDC: PPV & NPV
What does a 95% confidence interval represent?
Range where true value lies with 95% certainty over repeated samples
Probability that null hypothesis is true
Range containing 95% of data points
Standard error of the estimate
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. Statistics Lectures: Confidence Intervals
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. CDC: Effect Modification
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. Cochrane: Evidence Hierarchy
What is the ecological fallacy?
Assuming individual-level associations from group-level data
Bias from loss to follow-up
Error in randomization
Misclassification of exposure
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. NCBI: Ecological Fallacy
Which method estimates survival functions and accounts for censored data?
Kaplan-Meier estimator
Logistic regression
Linear regression
Chi-square test
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. NCBI: Kaplan-Meier Method
What does a hazard ratio of 2.0 indicate in a survival analysis?
Event rate is twice as high in the treatment group compared to control
Survival at 2 years is double
Risk difference is 2 per 100
Median survival time doubled
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. NCBI: Understanding Hazard Ratios
In meta-analysis, what does high I-squared (I²) indicate?
Substantial heterogeneity among study results
Low risk of bias
High publication bias
Large sample sizes
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. BMJ: Measuring Heterogeneity
Which model assumes a single true effect size shared by all studies?
Random-effects model
Fixed-effects model
Bayesian hierarchical model
Mixed-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. Cochrane: Fixed vs Random Effects
Which regression technique assesses time to event data while adjusting for covariates?
Cox proportional hazards model
Poisson regression
Linear regression
Logistic 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. NCBI: Cox Model
What does the basic reproduction number (R0) represent?
Average number of secondary cases from a primary case in a susceptible population
Time between successive cases in an outbreak
Proportion of population immune
Incubation period duration
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. CDC: Reproduction Number
Which curve plots sensitivity versus 1-specificity for different test thresholds?
ROC curve
Survival curve
Dose-response curve
Kaplan-Meier plot
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. NCBI: ROC Curves
What is the secondary attack rate?
Proportion of susceptible contacts who become infected after exposure to a primary case
Rate of new cases in population over time
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. Epi-Win: Outbreak Measures
What statistical method can adjust for multiple confounders when estimating incidence rate ratios?
Poisson regression
Log-rank test
Wilcoxon signed-rank test
Chi-square 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. NCBI: Poisson Regression
What is the purpose of directed acyclic graphs (DAGs) in epidemiology?
To visually represent causal assumptions and identify confounding paths
To calculate sample size for studies
To perform survival analysis
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. NCBI: DAGs in Epidemiology
Which approach uses genetic variants as instrumental variables to infer causal effects?
Mendelian randomization
Case-crossover study
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. NCBI: Mendelian Randomization
What is multilevel modeling used for in epidemiologic research?
To account for data clustered at different hierarchical levels
To impute missing data
To perform time-series analysis
To calculate incidence rates
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. NCBI: Multilevel Modeling
In outbreak investigations, what is the case definition?
Standard criteria for person, place, time, and clinical features to classify cases
List of all exposures investigated
Protocol for laboratory testing only
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. CDC: Case Definitions
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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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