# 15 Epidemiology Interview Questions and Answers

Prepare for the types of questions you are likely to be asked when interviewing for a position where Epidemiology skills will be used.

Prepare for the types of questions you are likely to be asked when interviewing for a position where Epidemiology skills will be used.

Epidemiology is the study of how diseases spread and how they can be controlled. It is a vital tool in public health, as it helps us to understand the patterns of disease transmission and identify risk factors for certain diseases.

If you’re interested in a career in epidemiology, you will need to be able to demonstrate your knowledge and skills in an interview. In this guide, we will provide some sample epidemiology interview questions and answers to help you prepare for your next job interview.

Common Epidemiology Interview Questions

- What is epidemiology?
- Can you explain what a cohort study is in the context of epidemiology?
- What’s the difference between incidence and prevalence? How do you measure them?
- Can you explain what an Epi curve is?
- What are some considerations to keep in mind when performing statistical analysis on population data?
- What types of bias can occur during statistical analysis?
- What are confounding variables?
- What’s the difference between descriptive, analytical, and experimental studies?
- What is multivariate analysis?
- What is sensitivity analysis?
- What is specificity?
- Why should one use ROC curves instead of using other methods like accuracy or precision/recall?
- How do you interpret regression coefficients in linear models?
- Can you explain the difference between Mean Absolute Error and Root Mean Square Error? Which one do you think is a better measure of accuracy?
- What is logistic regression?

This question is a basic one that an interviewer may ask to see if you have the necessary knowledge of what epidemiology is. Your answer should include a definition and examples of how it’s used in your field.

**Example:*** “Epidemiology is the study of disease patterns, causes and effects. It involves collecting data on diseases and health issues within a population. I use this skill when analyzing information about outbreaks or other public health concerns. For example, I recently worked with my team to determine why there was a higher-than-normal occurrence of flu cases among senior citizens.”*

This question is a great way to test your knowledge of cohort studies and how they apply to the field of epidemiology. When answering this question, it can be helpful to define what a cohort study is and give an example of one in relation to epidemiology.

**Example:*** “A cohort study is a type of observational study that follows a group of people over time. It’s often used to examine risk factors for disease or other health conditions. For instance, I once worked with a team of researchers who were conducting a cohort study on the effects of smoking on lung cancer. They followed a group of smokers and non-smokers over several years to see if there was any correlation between smoking and lung cancer.”*

This question tests your knowledge of two important epidemiological concepts. It also allows you to show the interviewer that you can apply what you know about these terms in a real-world situation.

**Example:*** “The difference between incidence and prevalence is that incidence measures how many new cases of a disease occur within a specific time period, while prevalence measures the total number of people who have a certain disease at a given point in time. You measure incidence by dividing the number of newly diagnosed patients by the population size. To measure prevalence, you divide the number of existing patients by the population size.”*

An Epi curve is a graphical representation of the number of cases of an illness over time. This question allows you to demonstrate your knowledge of epidemiology by describing what an Epi curve is and how it can be used in research.

**Example:*** “An Epi curve is a graph that shows the number of people who have contracted a disease at different points in time. It’s useful for determining when a disease outbreak occurred, where it started and how quickly it spread. I use this tool frequently during my research because it helps me identify patterns and trends among data sets.”*

This question can help the interviewer assess your critical thinking skills and ability to apply them in a professional setting. Use examples from your experience that demonstrate how you analyze data, consider different factors and make decisions based on those factors.

**Example:*** “When performing statistical analysis on population data, it’s important to keep several things in mind. First, I always ensure that my calculations are accurate by double-checking all of my work. Second, I try to avoid making assumptions about the data because this could lead to inaccurate results. Third, I use appropriate methods for analyzing the data so that I can get an accurate picture of what is happening within the population.”*

Interviewers may ask this question to assess your ability to recognize and avoid bias in your work. They want to know that you can perform accurate research and interpret data correctly. In your answer, explain the different types of bias that can occur during statistical analysis and how you would identify and correct them.

**Example:*** “There are several types of bias that can occur during statistical analysis. One is selection bias, which occurs when a study sample isn’t representative of the larger population. Another type of bias is measurement bias, which happens when researchers use inaccurate methods to measure certain factors. Lastly, there’s confirmation bias, which is when researchers only look for information that supports their hypothesis.”*

This question tests your knowledge of a specific epidemiology concept. Confounding variables are factors that make it difficult to determine the cause-and-effect relationship between two or more things. Your answer should show that you understand what confounding variables are and how they affect research results.

**Example:*** “Confounding variables are any extraneous factors that can influence the outcome of an experiment. For example, if I wanted to know whether eating carrots makes people healthier, I would need to conduct a study where all other factors remain constant. If I didn’t control for confounding variables, such as age, gender, diet and exercise habits, then my results might be inaccurate.”*

This question tests your knowledge of the different types of studies and how they’re used in epidemiology. Your answer should include a definition for each type of study, along with an example of when you’ve used each one.

**Example:*** “Descriptive studies are used to describe a population or group’s characteristics. They can be conducted using surveys, interviews, observations and other methods. Analytical studies use statistical analysis to test hypotheses about relationships between variables. I have used this type of study many times to determine if there is a correlation between certain diseases and environmental factors. Experimental studies compare two groups that differ only by one variable. This allows researchers to see what effect the variable has on the subjects.”*

This question tests your knowledge of a specific skill. It also allows you to show the interviewer that you can apply this skill in an effective way. In your answer, define what multivariate analysis is and give an example of how you used it in your previous role.

**Example:*** “Multivariate analysis is a statistical method for examining several variables at once. I have used this method many times when analyzing data from surveys or experiments. For instance, I conducted a survey on public health issues in my community. The results showed that people who had access to healthy food options were more likely to eat well. This information helped me develop programs to increase access to fresh produce.”*

Sensitivity analysis is a statistical process that allows you to determine the impact of changes in your data. This question tests your knowledge of epidemiology processes and how they apply to real-world situations. In your answer, define sensitivity analysis and give an example of when you used it in your previous role.

**Example:*** “Sensitivity analysis is a method for determining the effect of changing one variable on another. For instance, I once worked with a client who was concerned about the number of people who would be affected by their new product launch. We ran several scenarios using different variables like age, gender and income level to see which factors had the greatest impact on our results. After running these simulations, we determined that the majority of people who would purchase this product were between the ages of 25 and 35.”*

This question tests your knowledge of epidemiology terminology. It also allows you to show the interviewer that you can apply this term in a real-world situation. In your answer, define specificity and give an example of when you used it in your previous role.

**Example:*** “Specificity is the percentage of positive results from a test compared to all the results. For instance, if I had 100 people who tested positive for a disease and only 20 of them actually have the disease, then my specificity would be 20%. This means that 80% of the people who tested positive do not have the disease.”*

This question is an opportunity to show your knowledge of the field by explaining how ROC curves are used in epidemiology. You can also use this as a chance to highlight any experience you have using ROC curves, which may be beneficial if you’re applying for a position that requires them.

**Example:*** “ROC curves are useful because they allow one to compare two different methods of classification and see how well each performs. This allows us to determine which method is more effective at identifying patients who need treatment or monitoring those who are already infected with a disease. They’re also helpful when comparing multiple methods of classification since they provide a visual representation of their performance.”*

This question is a more technical one that allows you to show your knowledge of epidemiological concepts. You can answer this question by explaining the concept and how it applies to your work.

**Example:*** “Regression coefficients in linear models are used to determine the relationship between two variables. For example, if I’m looking at the relationship between age and blood pressure, I would use regression coefficients to find out what each unit increase in age means for blood pressure. In my last role, I was tasked with analyzing data on the spread of disease within a population. I used regression coefficients to understand which factors were most likely to lead to an outbreak.”*

This question tests your knowledge of two common measures of accuracy in epidemiological studies. It also tests your ability to make a decision based on the information you have available.

**Example:*** “Mean Absolute Error is a measure of how far off an estimate is from the actual value, while Root Mean Square Error is a measure of how far off an estimate is from the mean. In my experience, I find that Root Mean Square Error is more useful because it takes into account both direction and distance when measuring error. This makes it easier to understand which estimates are most accurate.”*

This question tests your knowledge of a specific statistical process. It also allows you to show the interviewer that you can apply what you know about this process to real-world situations. In your answer, define logistic regression and explain how it is used in epidemiology.

**Example:*** “Logistic regression is a statistical method for analyzing data from surveys or experiments. It’s often used to predict the probability of an event occurring based on certain factors. For example, if I wanted to determine whether there was a correlation between smoking and lung cancer, I could use logistic regression to analyze the data from my survey. This would allow me to see if there is a relationship between these two factors.”*