Epidemiology Attributable Risk Quiz

Epidemiology

• Objectives: Define terms related to infectious diseases; construct tables & figures for epidemiology data; calculate disease frequency & infection rates; interpret key components of epidemiologic data; analyze epidemiological data; preparation of tables & graphs (graphs, histograms, population pyramids, bar charts, pie charts, scatter diagrams, maps).

Define Selected Terms Related to Infectious Diseases

• Epidemic: An unusual and unexpected occurrence of a disease.
• Endemic: Constant presence and/or usual frequency of a disease or infectious agent within a specific geographic area or population. Predictable rate in that area. (Example: Malaria in Sub-Saharan Africa).
• Pandemic: An outbreak of a disease on a global scale, affecting multiple countries and continents, often causing widespread illness. (Example: Covid-19).
• Immunity: The body's ability to resist or defend against infection, disease, or other biological invaders.
  • Innate (Natural) Immunity: Body's first line of defense, present from birth, providing non-specific protection.
  • Acquired (Adaptive) Immunity: Developed after exposure to a specific pathogen, through infection or vaccination. Provides targeted, long-lasting defense. (Example: Measles vaccine providing acquired immunity) .
• Immune Response: The body's defense mechanism activated upon recognizing foreign substances (antigens) like pathogens.
• Herd Immunity: When a significant portion of a population becomes immune to a disease, reducing its spread and protecting non-immune individuals.
• Immunoglobulin: Antibodies produced by the immune system to neutralize pathogens like bacteria and viruses.
• Host Response: The way a person's body reacts to an invading pathogen, either by immune defenses or inflammatory processes.
• Hypersensitivity: An exaggerated or inappropriate immune response to a harmless substance, such as in allergies.
• Infection: The invasion and multiplication of microorganisms (bacteria, viruses, parasites) within the body causing disease.
• Infectivity: The ability of a pathogen to enter, survive, and multiply in a host.
• Pathogenicity: The ability of a microorganism to cause disease in a host.
• Carrier: An individual who harbors a pathogen but does not exhibit symptoms of the disease, potentially causing an outbreak or continued transmission. (Example: Asymptomatic carrier of Salmonella Typhi).
• Virulence: The degree of damage a pathogen can cause to the host.
• Immunogenicity: The ability of a substance (pathogen or vaccine) to provoke an immune response.
• Sporadic: Refers to diseases that occur infrequently and irregularly within a population.

Elements of the Disease Process-Chain of Infection

• Infectious Agent: The pathogen (e.g., bacteria, virus).
• Reservoir: Where the pathogen lives (e.g., humans, animals).
• Portal of Exit: How the pathogen leaves the reservoir (e.g., respiratory droplets).
• Mode of Transmission: How the pathogen spreads (e.g., airborne, direct contact).
• Portal of Entry: How the pathogen enters a new host (e.g., through broken skin).
• Susceptible Host: An individual who can contract the disease due to weak or absent immunity.

Measurements & Their Calculations

• Ratios, Proportions, Incidence rates, Prevalence rates, Demographic rates
• Relationships between predictive value and disease prevalence

Frequency

• The fundamental epidemiological measure is the frequency with which an event (disease, injury, death) occurs in the population.
• Usually expressed as a count. Examples include tables, bar charts, line graphs, etc.
• Incidence and prevalence are essential to epidemiology.
• Rates are the frequency of events in a defined time period divided by the average population at risk.

Measures of Central Tendency- Mean Mode Median

• Mean, Median, and Mode: Measures of central tendency. Summarize a dataset, identifying the central or typical value.
  • Help summarize and interpret large datasets.
  • Mean (average): arithmetic average representing the typical value. Calculated by dividing the sum of all values in a dataset by the number of values. (Examples: average age at diagnosis, average number of cases, average exposure levels in a population).
  • Median: middle value in a dataset when values are ordered. If even number of values, average of the two middle values.
  • Mode: Value that occurs most frequently in a dataset.

Interpreting Key Components of Epidemiologic Data

• Prevalence: Proportion of a population having a particular disease or condition at a specific point in time or over a specified period.
• Proportions: Fractions in which the numerator is included in the denominator. Prevalence is calculated by (# of cases/# of people in the population) X 100).
• Incidence Rate: The number of new cases of a disease or condition in a specific period within a population at risk. Unique from prevalence in how numerator and denominator use different measurement units for rates, i.e., new observed cases per unit of observation time period divided by the total person-time at risk.
• Mortality Rate: Number of deaths due to a particular cause per unit of population, usually per 100,000 people per year. (Crude death rate formula = # of deaths/midpoint population x 1000 population.
• Crude Birth Rate, Infant Mortality, Age Specific and Maternal Mortality, Neonatal Mortality Rate: Calculations for these are provided in the handout.
• Morbidity Rate: Frequency or rate of disease within a population. Measures burden of illness and provides insight into health needs (ex: high Morbidity Rate for diabetes shows need for better management).

Interpreting Key Components of Epidemiologic Data

• Risk: Proportion of persons unaffected at the beginning of a study period but who undergo a risk event (death, disease, injury) during the study period.
• Relative Risk (RR): Measures the risk of a health event among those exposed to a risk factor compared to those not exposed. A RR greater than 1 indicates increased risk of exposure; less than 1 indicates decreased risk.
• Odds Ratio (OR): Measure of association between exposure and outcome. Calculated by comparing odds in exposed vs unexposed groups. A greater than 1 suggests an association; less than 1 suggests protective effect of exposure.
• 2x2 Table: Used in case-control and cohort studies, showing exposure and outcome. The OR and RR are calculated from the values in this table.
• Cohort Study: Prospective or retrospective observational study following a group of individuals over time to see how exposure to a risk factor affects disease or outcome.
• Case-Control Study: Retrospective study comparing individuals with a specific condition to those without, to assess if exposure to a risk factor is associated with the condition.
• Attributable Risk: The difference in health outcome rate between exposed and unexposed groups, indicating the attributable proportion of risk to the exposure.

Scenario

• Cohort study scenario: In a cohort study, among 100 smokers, 40 developed lung cancer; and among 100 non-smokers, 10 developed lung cancer. Calculate and interpret results.
• Case-control study scenario: Among 100 smokers, 40 developed lung cancer; and among 100 non-smokers, 10 developed lung cancer. Calculate and interpret results.
• Calculate Attributable Risk: Calculate the attributable risk from the scenarios above. Interpret the results.