2.2. Describe types and sources of data used in epidemiology

This guide will help you answer 2.2. Describe types and sources of data used in epidemiology.

Epidemiology focuses on studying diseases and their patterns, causes, and effects in population groups. Data is essential in epidemiology, as it helps public health professionals understand disease trends, identify risk factors, and plan effective interventions. This guide will explore the types and sources of data used in epidemiology.

Types of Data

Epidemiological data can be classified into several types. Each type serves specific purposes and helps researchers answer distinct questions about health and disease.

Quantitative Data

Quantitative data involves numbers. Examples include the number of cases, mortality rates, or vaccination percentages. It helps measure and compare health outcomes across populations.

Examples:

• Number of COVID-19 cases reported daily
• Infant mortality rates per 1,000 live births
• Average lifespan

Qualitative Data

Qualitative data captures information that cannot be expressed numerically. It includes descriptions, opinions, interviews, or observations about health-related behaviours, attitudes, and perceptions. Health professionals use this data to understand social and cultural factors affecting health.

Examples:

• Patients explaining the barriers they face in accessing healthcare
• Observing hygiene practices in a community
• Conducting focus groups to assess public opinions about vaccination

Routine Data

Routine data is collected regularly as part of normal service delivery or administrative activities. It is useful for tracking trends over time. An example is data collected by the NHS on hospital admissions.

Examples:

• GP attendances recorded weekly
• Birth and death registrations
• Immunisation coverage

Primary Data

Primary data is data researchers collect directly for a specific study. This allows greater control over how the data is gathered, ensuring it fits the study’s objectives.

Examples:

• Conducting surveys about dietary habits
• Observing physical activity levels using wearable devices
• Blood pressure measurements during health assessments

Secondary Data

Secondary data is pre-existing information generated by other organisations or researchers. It saves time and resources but may not fully align with the particular needs of a study.

Examples:

• Census data
• Previous research articles
• Hospital admission statistics

Ecological Data

Ecological data refers to population-level information, rather than individual data. Researchers use this to examine trends, such as disease rates across regions.

Examples:

• Air pollution levels in different cities
• Obesity prevalence in different cities
• Rates of smoking in a population

Categorical and Continuous Data

Categorical data includes distinct groups or categories. These could be gender, disease status, or vaccination status. Continuous data involves measurements that have a range, such as weight, height, or age.

Examples of categorical data:

• Male vs. female participants in a study
• Disease positive vs. negative cases
  Examples of continuous data:
• Weight measured in kilograms
• Number of cigarettes smoked per day

Sources of Data

Data used in epidemiology comes from a variety of sources. These sources vary in reliability, scope, and accessibility. They can be divided into primary sources, which include direct gathering, and secondary sources, which contain pre-existing information.

Surveys

Surveys collect data on knowledge, attitudes, and behaviours directly from participants. They can be conducted through online forms, face-to-face interviews, or phone calls. Surveys provide detailed, individual-level data.

Examples:

• Health surveys asking about alcohol consumption
• National Diet and Nutrition Survey to analyse dietary patterns
• Sexual health surveys conducted among teenagers

Vital Statistics

Vital statistics record life events, such as births, deaths, and marriages. These statistics are crucial for understanding mortality, fertility, and population growth trends.

Examples:

• Birth registration data linked to maternal health outcomes
• Death registration data providing insights into causes of mortality
• Marriage records that can correlate to certain population studies

Hospital and Healthcare Records

Healthcare organisations, such as the NHS, generate records about patient encounters, treatments, and outcomes. These include electronic records and admissions data.

Examples:

• Data on patient hospital stays for heart attacks
• Surgery outcomes recorded for research purposes
• GP-generated prescriptions for chronic diseases

Disease Registries

Disease registries collect data about people diagnosed with specific conditions. They help track the incidence, prevalence, and outcomes of diseases.

Examples:

• Cancer registries monitoring diagnosis and treatment data
• Diabetes registries providing information on complications in diabetic patients
• Tuberculosis registries assessing progress in disease eradication

Laboratory Data

Laboratories conduct tests on samples collected from patients. Lab data is useful for identifying infections, monitoring the effectiveness of treatments, and studying genetic factors.

Examples:

• Pathology reports identifying bacterial or viral infections
• Blood test results showing cholesterol levels
• Genetic testing data indicating risk of inherited conditions

Occupational Data

Data gathered from workplaces helps assess connections between certain jobs and health outcomes. It often supports research into occupational health risks.

Examples:

• Risk of lung diseases among coal miners
• Chemical exposure data among factory workers
• Shift work studies analysing sleep disorders

Environmental Data

Data on environmental factors, such as pollution levels, climate conditions, and water quality, help assess their role in disease development.

Examples:

• PM2.5 air particle data linked to respiratory diseases
• Average temperature figures connected to heat stroke incidence
• Water contamination reports linked to gastrointestinal infections

Surveillance Systems

Surveillance systems continuously monitor, collect, and analyse health data to detect outbreaks and plan interventions. They can be disease-specific, population-based, or syndromic in nature.

Examples:

• Flu surveillance monitoring seasonal influenza trends
• COVID-19 surveillance tracking daily cases and hospitalisation rates
• Syndromic surveillance identifying early signals of respiratory illnesses

Census Data

The national census records demographic information about the population, such as age, ethnicity, income, and housing. This forms the foundation for health studies targeting certain population groups.

Examples:

• Age-related disease trends in census data
• Socioeconomic links to health outcomes
• Regional population growth patterns predicting healthcare needs

Research Studies

Published research supplies epidemiologists with findings from prior investigations. Researchers frequently use these studies for secondary analysis.

Examples:

• Randomised controlled trials on drug effectiveness
• Cohort studies following smoking behaviours over decades
• Case-control studies investigating rare diseases

Media Articles and Reports

Media can provide immediate reports during health crises. While it may contain errors, journalists often uncover early warnings of disease outbreaks.

Examples:

• News reports about emerging infections
• Social media posts indicating self-reported symptoms during pandemics
• Investigative pieces exposing contaminated water supplies

Barriers in Using Epidemiological Data

Epidemiological data can face issues related to accuracy, accessibility, or bias. For instance:

• Some surveys might not reach specific groups, such as rural populations or disabled individuals.
• People may underreport sensitive behaviours, such as excessive drinking.
• Variations in diagnostic definitions between countries can limit studies comparing diseases.

Final Thoughts

Data is at the heart of epidemiology. Types of data like quantitative, qualitative, and routine data help researchers address health-related questions effectively. Primary and secondary sources give additional depth to studies by providing individual-level statistics or aggregated patterns. From surveys to disease registries, these sources allow experts to plan better healthcare policies, detect outbreaks, and reduce inequalities in health.