Analysing Disease Data and Epidemiology Revision Notes | GCSE OCR Foundation Biology

What this lesson covers

Learn to interpret disease incidence data using graphs, charts, and statistical methods, and understand the principles of sampling in epidemiological st...

• Interpret disease data presented in different graphical and numerical forms
• Construct frequency tables, bar charts and histograms from epidemiological data
• Use scatter diagrams to identify correlations between disease variables
• Apply sampling principles to analyse scientific and epidemiological data

Key ideas to keep in view

Use this lesson to stay inside B6.3 Monitoring and maintaining health while connecting the detail back to the wider B6: Global challenges topic.

• B6: Global challenges
• B6.3 Monitoring and maintaining health
• GCSE OCR Foundation Biology

Lesson notes preview

Read the core explanations from Analysing Disease Data and Epidemiology before testing yourself from memory.

• When COVID-19 hit, governments needed answers fast. How many people were infected? Where was it spreading fastest? Which groups were most at risk?
• Scientists couldn't test everyone, so they used samples and data analysis to track the pandemic. This is epidemiology - the detective work of disease investigation. You'll learn how to read the clues hidden in health data and spot the patterns that save lives.
• The number of new cases of a disease in a population during a specific time period. Usually expressed as cases per 1000 people per year.
• Disease data comes in many forms - tables of numbers, bar charts, line graphs, and scatter plots. Each tells a different part of the story. The key is knowing which format reveals what you're looking for.
• Trap: Many students think incidence and prevalence are the same. Incidence counts NEW cases over time. Prevalence counts ALL existing cases at one moment.
• This catches students out in exams. Can you spot why comparing raw numbers would be misleading?
• Numbers in tables are hard to interpret quickly. Charts reveal patterns instantly. But different chart types highlight different aspects of the data.
• Bar charts compare categories (like disease rates in different age groups). Histograms show distributions (like how many people fall into different BMI ranges). Line graphs track changes over time.
• Notice how the frequency table reveals the pattern - most people cluster around 130-149 mmHg. This distribution shape tells us about the health of this population.
• Scatter diagrams are powerful tools for finding relationships between two health variables. Do people who smoke more get lung cancer more often? Does exercise reduce heart disease risk?

Continue through the topic

Move to the related lessons or back to the topic page when you need the wider sequence before exam-style practice.