🤒Intro to Epidemiology Unit 4 – Descriptive Epidemiology

Key Concepts and Definitions

• Epidemiology studies the distribution and determinants of health-related states or events in specified populations and applies this knowledge to control health problems
• Descriptive epidemiology aims to describe the occurrence of disease in terms of person, place, and time
• Incidence refers to the number of new cases of a disease or condition that develop in a population over a specified period
• Prevalence measures the proportion of a population that has a disease or condition at a specific point in time
• Risk factors are characteristics, behaviors, or exposures that increase the likelihood of developing a disease or condition
  • Modifiable risk factors can be changed (smoking, diet, physical activity)
  • Non-modifiable risk factors cannot be changed (age, gender, genetic predisposition)
• Health determinants are factors that influence the health status of individuals or populations (social, economic, environmental, biological)
• Epidemiological triad consists of the agent, host, and environment interacting to cause disease

Types of Descriptive Studies

• Cross-sectional studies measure the prevalence of a disease or condition and associated risk factors at a single point in time
• Ecological studies compare disease rates between populations in relation to risk factors at the group level rather than individual level
• Case reports and case series describe the characteristics and clinical course of one or a few patients with a specific disease or condition
• Correlational studies examine the relationship between two variables (exposure and outcome) without establishing causation
• Surveillance involves the ongoing, systematic collection, analysis, and interpretation of health data to inform public health action
  • Active surveillance actively seeks out cases through regular contact with healthcare providers or the population
  • Passive surveillance relies on healthcare providers or laboratories to report cases to public health authorities
• Outbreak investigations aim to identify the source and mode of transmission of a disease outbreak and implement control measures

Measures of Disease Frequency

• Count is the absolute number of cases or events in a specified population
• Ratio compares the number of cases or events in one group to the number in another group (male-to-female ratio)
• Proportion expresses the number of cases or events as a fraction of the total population at risk
• Rate measures the frequency of cases or events in a population over a specified time period
  • Incidence rate: $\frac{\text{Number of new cases}}{\text{Population at risk} \times \text{Time period}}$
  • Prevalence rate: $\frac{\text{Number of existing cases}}{\text{Total population}}$
• Attack rate is the proportion of an at-risk population that develops a disease over a specified time period during an outbreak
• Case fatality rate is the proportion of cases that result in death from a specific disease

Population Characteristics (Person, Place, Time)

• Person characteristics include demographic factors (age, gender, race/ethnicity), socioeconomic status, occupation, and health behaviors
• Place refers to the geographic location or environment where cases occur (urban/rural, specific regions, clusters)
• Time describes the temporal distribution of cases (seasonal patterns, trends over years or decades, epidemic curves)
• Age-specific rates stratify disease frequency by age groups to identify high-risk populations
• Sex-specific rates compare disease frequency between males and females
• Race/ethnicity-specific rates highlight disparities in disease burden among different racial or ethnic groups
• Socioeconomic status (education, income, occupation) can influence disease risk and access to healthcare
• Occupation-related exposures may contribute to the development of certain diseases (lung cancer in asbestos workers)

Data Collection Methods

• Health surveys gather information from a sample of the population through interviews or questionnaires
  • Cross-sectional surveys collect data at a single point in time
  • Longitudinal surveys follow participants over an extended period
• Disease registries systematically collect and store data on all cases of a specific disease or condition in a defined population (cancer registries)
• Vital statistics include records of births, deaths, marriages, and divorces
  • Birth certificates provide data on maternal age, gestational age, birth weight
  • Death certificates include cause of death, age at death, place of death
• Electronic health records (EHRs) capture patient data during routine clinical care and can be used for epidemiological research
• Administrative databases, such as insurance claims or hospital discharge data, can provide information on healthcare utilization and outcomes
• Environmental monitoring data assess exposures to potential health hazards (air pollution, water quality)

Descriptive Statistics and Data Visualization

• Measures of central tendency summarize the typical value in a dataset (mean, median, mode)
• Measures of dispersion describe the spread or variability of data (range, standard deviation, interquartile range)
• Frequency distributions organize and display the number of observations falling into each category or interval
• Bar charts compare frequencies or proportions across categories using rectangular bars
• Pie charts represent data as slices of a circle, with each slice proportional to the category's frequency or proportion
• Line graphs display trends or changes in a variable over time
• Scatter plots visualize the relationship between two continuous variables
• Maps can display geographic patterns or clusters of disease cases
  • Choropleth maps use color or shading to represent different levels of disease frequency across regions
  • Dot maps plot individual cases as points on a map

Interpreting Descriptive Epidemiological Findings

• Identify patterns and trends in disease occurrence by person, place, and time
• Compare disease frequencies across different populations or subgroups to identify disparities
• Generate hypotheses about potential risk factors or causes of disease based on observed associations
• Recognize limitations of descriptive studies, such as the inability to establish causal relationships
• Consider potential biases or confounding factors that may influence the interpretation of results
  • Selection bias occurs when the study population is not representative of the target population
  • Information bias arises from inaccurate or incomplete data collection
  • Confounding is a distortion of the association between an exposure and outcome due to a third variable
• Assess the public health significance of findings in terms of disease burden, severity, and preventability
• Communicate findings effectively to stakeholders, including policymakers, healthcare providers, and the public

Applications and Case Studies

• Outbreak of Legionnaires' disease associated with a hotel's water system
  • Descriptive epidemiology identified the source and guided control measures
• Racial and ethnic disparities in COVID-19 incidence and mortality
  • Age-adjusted rates revealed disproportionate burden among Black and Hispanic populations
• Temporal trends in obesity prevalence in the United States
  • National Health and Nutrition Examination Survey (NHANES) data showed increasing obesity rates over decades
• Geographic variation in opioid overdose deaths across U.S. states
  • Choropleth maps highlighted high-burden areas and informed targeted interventions
• Occupational exposure to asbestos and risk of mesothelioma
  • Case series and registries documented the association and led to regulations on asbestos use
• Socioeconomic gradients in cardiovascular disease mortality
  • Vital statistics data demonstrated higher rates among lower income and education groups
• Seasonal patterns of influenza activity in temperate regions
  • Surveillance data informed the timing of annual vaccination campaigns