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3.7.12Additional lessons

Evaluating COVID-19 Data- Skills — IB Biology HL Revision Notes & Topical Questions

5 min read 5 parts Lesson 9 of 101

📚 IB Biology HL Hub / Topical Revision
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Part 1 of 5Reading Epidemic Data

1
Check what each axis shows, including units, the time period and whether the vertical scale is linear or logarithmic.
2
Decide whether numbers are absolute counts or rates per 100 000, because only rates allow fair comparison between countries of different size.
3
Identify trends, such as the shape of waves, peaks and the time lag between cases, hospital admissions and deaths.
4
Consider how the data were collected, for example whether testing rates changed and so altered the number of reported cases.
5
Draw conclusions that the data support, and avoid claiming that correlation proves cause.

Part 2 of 5Key Calculations

Case fatality rate
  • Case fatality rate Deaths divided by confirmed cases, multiplied by 100, gives the percentage of identified cases that died.
Incidence
  • Incidence The number of new cases in a time period, often expressed per 100 000 people to allow comparison.
Vaccine efficacy
  • Vaccine efficacy The percentage reduction in disease among vaccinated people compared with an unvaccinated placebo group in a trial.
Percentage change
  • Percentage change Change divided by the original value times 100, useful for comparing cases before and after an intervention.
MeasureFormulaMeaning
Case fatality rateDeaths ÷ cases × 100Risk of death among cases
Vaccine efficacy(Risk placebo − risk vaccine) ÷ risk placebo × 100Reduction in risk
Incidence rateCases ÷ population × 100 000Cases per 100 000

Part 3 of 5Evaluating Reliability

Evaluating Reliability
Sample size
  • Sample size Trials with tens of thousands of volunteers give narrow uncertainty, so their results are more trustworthy.
Controls
  • Controls Comparing vaccinated people with a placebo group, ideally in a double-blind design, removes bias.
Data quality
  • Data quality Under-reporting, differences in testing and delays in recording deaths limit comparisons between places.
Confounding variables
  • Confounding variables Age, health, season and lockdown measures also change case numbers and can be mistaken for the effect of one factor.

Part 4 of 5Worked Example

Question

  • In a trial, 160 of 18 000 people given placebo developed COVID-19 and 8 of 18 000 given the vaccine did.
  • Calculate vaccine efficacy.
  • Another region reports 2 000 deaths among 80 000 confirmed cases;
    • calculate the case fatality rate.

  1. Risk in placebo group = 160 ÷ 18 000 = 0.00889; risk in vaccine group = 8 ÷ 18 000 = 0.00044.
  2. Efficacy = (0.00889 − 0.00044) ÷ 0.00889 × 100 = 95%.
  3. Case fatality rate = 2 000 ÷ 80 000 × 100 = 2.5%.

Answer Vaccine efficacy is 95%, and the case fatality rate is 2.5%.

Part 5 of 5Exam Checklist & Tips

3.7.12 – Key Points for the Exam

  • Case fatality rate Percentage of confirmed cases that result in death.
  • Vaccine efficacy Percentage reduction in disease in vaccinated people compared with a placebo group.
  • Placebo An inactive treatment given to a control group.
  • Confounding variable A factor other than the one being tested that affects the result.

Common Mistakes

  • Comparing raw case numbers between countries of different population size.
  • Confusing case fatality rate (among cases) with the death rate of the whole population.
  • Concluding that a vaccine caused a fall in cases when other factors changed at the same time.

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