Epidemiology: Measure of Disease Frequency, Incidence and Prevalence

UTAH Center for Clinical & Translational Science
13 Jun 201711:15
EducationalLearning
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TLDRIn this educational segment from the University of Utah's Department of Internal Medicine, Carol Sweeney delves into the concepts of disease frequency, particularly incidence and prevalence, crucial for resident research in epidemiology. She clarifies the distinction between diseases expressed as risks versus rates, emphasizing the importance of time in measuring disease events. Through accessible explanations and illustrative graphics, Sweeney explains how incidence measures new disease occurrences in a population over time, while prevalence accounts for all current cases. The discussion extends to dynamic populations, highlighting the challenges of tracking disease outcomes and the significance of person-time data. This lecture is an essential foundation for understanding epidemiological measures and their impact on public health research.

Takeaways
  • 📊 Incidence refers to the occurrence of new disease cases in a specified population and time period, emphasizing the 'population at risk'.
  • 🔍 Distinguishing between clinical and public health perspectives, incidence can focus on disease outcomes or new disease occurrences.
  • 📈 Prevalence represents the number of affected individuals at a specific time, affected by both incidence and cure or death rates.
  • 📉 Risk, often used interchangeably with cumulative incidence, is calculated as the number of new cases divided by the population at risk.
  • 🕒 Rate involves measuring incidence with person-time data, reflecting the dynamic nature of populations where individuals enter and leave over time.
  • 👥 Dynamic populations challenge disease measurement, necessitating adjustment for varying follow-up times and population changes.
  • ⏳ Person-time is critical in calculating incidence rates, accounting for each individual’s time observed and at risk.
  • 📐 Incidence density or rate is determined by dividing new cases by total person-time, providing a time-adjusted measure of disease occurrence.
  • 🔬 Accurate measurement of incidence requires clear definition of the population at risk and comprehensive outcome observation.
  • 📚 In epidemiology, the term 'rate' specifically denotes a measure with time in the denominator, distinguishing it from other types of measurements.
Q & A
  • What are the objectives of the lecture segment on measures of disease frequency?

    -The objectives are for students to distinguish between disease expressed as a risk versus a rate, and to consider the treatment of time in measuring disease events.

  • How is incidence defined in the context of epidemiology?

    -Incidence is defined as a measure of the occurrence of new disease in a defined population at risk for the disease within a specified time period.

  • Why is the concept of a 'population at risk' important in measuring incidence?

    -The concept of 'population at risk' is important because it defines the denominator for incidence calculations, including all the people being observed for new disease occurrences within them.

  • How can the concept of incidence be applied in clinical research settings?

    -In clinical research, incidence can be used to measure disease outcomes such as mortality, cure rates, or occurrence of adverse events, by redefining the population at risk as those with a certain disease or medical characteristic.

  • What is the difference between incidence and prevalence?

    -Incidence measures the occurrence of new disease cases in a population at risk within a specific time period, whereas prevalence refers to the total number of affected persons in a population at a specific time.

  • How do incidence and death or cure rates influence prevalence?

    -Both the rate at which new cases occur (incidence) and the rate at which individuals leave the population of affected persons (through death or cure) influence the prevalence of a disease.

  • What are the two ways incidence can be measured, and how do they differ?

    -Incidence can be measured using count data (as a risk or cumulative incidence) or using person-time data (as a rate). The former is a simple proportion of new cases in a population, while the latter accounts for individual exposure times in a dynamic population.

  • Why might a cumulative incidence not be calculable in a dynamic population?

    -A cumulative incidence requires a closed population with complete follow-up on each person, which is not possible in dynamic populations where new people enter, participants are enrolled at different times, or individuals may leave or be lost to follow-up.

  • What is an incidence density, and how is it calculated?

    -Incidence density, or a rate, is calculated in a dynamic population as the number of new cases divided by the person-time at risk. It accounts for varying amounts of observation time among participants.

  • In the strict sense, when is the term 'rate' used in epidemiology?

    -In epidemiology, the term 'rate' is strictly used when the denominator is time, making it a measure with units of reciprocal time.

Outlines
00:00
📚 Introduction to Disease Measures: Incidence and Prevalence

This paragraph introduces Carol Sweeney from the Department of Internal Medicine at the University of Utah, who discusses the concepts of disease frequency, incidence, and prevalence. The lecture aims to help students differentiate between diseases expressed as risk versus rate and to understand the importance of time in measuring disease events. The definition of incidence is provided as the occurrence of new disease in a defined population at risk within a specified time period. The lecture also touches on the clinical research setting, where the focus is on disease outcomes such as mortality and adverse events. The importance of identifying the population at risk for accurate observation and measurement of incidence is emphasized, using a graphical representation to illustrate the concept of incidence in both public health and clinical settings.

05:02
📈 Understanding Risk and Rate in Disease Measurement

This section delves into the concepts of risk and rate when measuring incidence. It explains that disease risk is a simple measure based on count data, while rates require person-time data. The risk or cumulative incidence is calculated as the number of incident cases divided by the number of persons at risk. The paragraph provides examples of how to calculate incidence proportion, such as Salmonella cases after a picnic and complications following surgery. It highlights the challenges of calculating cumulative incidents in dynamic populations, where the population size changes over time. The concept of 'person-time' is introduced as a way to address this issue, leading to the calculation of incidence density or rate, which is the number of new cases divided by the total person-time at risk.

10:05
🔍 Measuring Disease Outcomes and the Importance of Terminology

The final paragraph focuses on the measurement of disease outcomes, such as mortality, using the same concepts as for incidence. It stresses the importance of correctly defining the population at risk and observing outcomes in all members to avoid bias in cause-effect studies. The paragraph clarifies the use of the term 'rate' in epidemiology, stating that it should be used strictly when the denominator is time, with units of reciprocal time. The lecture concludes with a reminder of the significance of accurate terminology and the mention of a subsequent segment on disease frequency measures using survival analysis.

Mindmap
Keywords
💡Incidence
Incidence is defined as the measure of the occurrence of new cases of a disease within a specific time period among a defined population at risk. This concept is crucial for understanding how often new instances of a disease appear, which can help in monitoring and controlling public health issues. The script emphasizes the importance of the population at risk and differentiates incidence from other measures of disease frequency by focusing on new disease occurrences.
💡Prevalence
Prevalence refers to the total number of cases of a disease that are present in a population at a given time. Unlike incidence, which measures the flow of new cases, prevalence is a snapshot of the disease's total impact on a population. The script uses the analogy of a beaker to illustrate how incidence (marbles pouring in) and factors like death or cure (marbles pouring out) can affect the prevalence of a disease.
💡Risk
Risk, in the context of this script, is a measure of the probability that an individual will develop a disease over a certain period of time. It's a simple proportion of the number of new cases (numerator) to the number of people at risk (denominator). The script distinguishes risk from rate by explaining that risk is based on count data and is applicable to closed populations with complete follow-up.
💡Rate
Rate is a measure of the occurrence of new cases of a disease per unit of person-time at risk. It's used when the population is dynamic, with individuals entering and leaving the risk pool over time. The script underscores that a rate is used in contexts where time is an integral part of the denominator, making it suitable for dynamic populations and emphasizing its units as reciprocal time (e.g., events per person-months).
💡Population at Risk
The population at risk is a key concept in epidemiology, referring to the group of individuals who are susceptible to the disease being studied. It is crucial for calculating both incidence and prevalence, as it defines who is included in the measure. The script highlights the importance of accurately defining this population to ensure reliable and valid measurements of disease frequency.
💡Cumulative Incidence
Cumulative Incidence is another term for risk, representing the proportion of individuals in a population who develop a disease during a specified time period. It is a straightforward measure of how widespread a disease becomes in a population over time. The script uses this term interchangeably with risk to describe the same concept of new disease occurrence in a closed population.
💡Incidence Density
Incidence Density is a form of measuring disease frequency that accounts for person-time at risk, making it useful for studies with dynamic populations. It's calculated by dividing the number of new cases by the total person-time at risk. This approach allows for a more nuanced understanding of disease occurrence over time, especially in longitudinal studies where individuals may enter and leave the study at different times.
💡Censored
Censoring occurs when there is incomplete information about an individual's outcome status at the end of a study, due to them leaving the study early or being lost to follow-up. The script discusses censoring in the context of calculating incidence rates, where some individuals may not be followed for the entire study period, necessitating adjustments in the analysis.
💡Person-Time
Person-time is a statistical measure representing the accumulated time that all participants in a study have been at risk. It's used as the denominator in calculating incidence rates for dynamic populations. The script explains how person-time allows for more accurate disease frequency measures in populations where members have varying lengths of follow-up.
💡Dynamic Population
A dynamic population is characterized by individuals entering and leaving the population at risk over time. This contrasts with a closed population, where all members are followed from the start to the end of the study period. The script notes that most populations are dynamic, highlighting the relevance of using rates (which account for person-time) to measure disease incidence in such populations.
Highlights

Carol Sweeney from the Department of Internal Medicine, University of Utah introduces a lecture on disease frequency, incidence, and prevalence.

The objectives include distinguishing between disease expressed as a risk versus a rate, and considering the treatment of time in measuring disease events.

Incidence is defined as the occurrence of new disease in a defined population at risk in a specified time period, emphasizing the importance of the 'population at risk'.

The use of incidence in both public health for measuring new disease occurrence and clinical research for disease outcomes.

Illustration of the concept of incidence using a graphic representation of a population at risk and the occurrence of new events.

Prevalence distinguished from incidence, defined as the number of affected persons at a specific time in a given population.

Illustration of prevalence using a beaker analogy, showing how incidence and cure or death rates influence prevalence.

Introduction to the concepts of risk and rate, with risk based on count data and rate on person-time data.

Cumulative incidence or risk is a simple measure of incidence based on count data, calculated from a closed population.

Dynamic populations complicate the measurement of cumulative incidence due to entry and exit of individuals.

Illustration of the challenges in dynamic populations with individuals entering and leaving the study or population.

Introduction of incidence density or rate, calculated as the number of new cases divided by the person-time at risk.

Example calculation of incidence rate using person-months, highlighting the importance of including time in the denominator.

Emphasis on the importance of defining the population at risk and observing outcomes in all members for accurate incidence measurement.

Clarification of the term 'rate' in epidemiology and statistics, stressing that it strictly refers to quantities with units of reciprocal time.

Transcripts
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