Updated 12 October 2026 · By Pete Bromfield, former Head of Maths with IB examining experience

How fast did COVID-19 spread at the start? Comparing doubling times

AA SLAA HLAI SLAI HL Solid Also in: Modelling, Differential equations

Research question

What were the doubling times of confirmed COVID-19 cases in the first 30 days after the 100th case in [several countries], and how did they change after lockdown measures?

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Why it makes a good exploration

In spring 2020 the world learned about exponential growth the hard way. Fitting exponential models to the early data, and measuring how quickly growth slowed, is a powerful, well-sourced IA.

The mathematics you'll need

Exponential models and doubling time
Log-linear regression
Piecewise models before and after an intervention
Comparing rates between countries

Modelling the data, step by step

This idea usually needs exponential, piecewise or straight-line models. See it worked step by step, with a criterion tip at every step: Exponential y = a e^(kx) + c and y = a·bˣ · Piecewise models · Straight line y = mx + c.

Model your own data Paste it from Desmos, GeoGebra or a spreadsheet and get the same play-by-play with your numbers. New to modelling? Start with the modelling workflow. Writing it up? The IA modelling planner comments on each paragraph as you draft — it never writes it for you.

Where the data comes from

Daily cumulative cases from the archived Johns Hopkins repository or Our World in Data.

Johns Hopkins CSSE COVID-19 repository (archived) — Daily cases and deaths by country, Jan 2020 – Mar 2023. No longer updated.

Real data for this idea

Primary source: WHO Global Health Observatory: WHO COVID-19 dashboard. Download cases for one country and take the first weeks of its first wave. Licence: CC BY-NC-SA 3.0 IGO: non-commercial use only, credit WHO, share alike.
Also useful: Johns Hopkins CSSE COVID-19 data (archived): COVID-19 time series (archived). The csse_covid_19_time_series folder holds cumulative confirmed cases by country and date. Licence: CC BY 4.0 (see the repository's README).
Readable chart: Our World in Data: Weekly confirmed COVID-19 cases. Use it to see the pattern; download your numbers from the primary source or the chart's own download. Cite as: Our World in Data, ‘Weekly confirmed COVID-19 cases’, CC BY 4.0. Original source: World Health Organization (2026).

WHO data is licensed for non-commercial use only (CC BY-NC-SA 3.0 IGO): fine for a school project, and credit WHO. Links checked October 2026; we link to the data and never copy it. More free data sets.

A possible outline

Align countries by the day of the 100th case.
Fit exponential models to early data.
Compute doubling times.
Fit before/after intervention periods.
Reflect on testing rates and reporting delays.

Pitfalls that cost marks

Treating confirmed cases as infections.
Choosing intervention dates after seeing the data.
Ignoring weekend reporting dips.

Showing personal engagement

Include your own country and explain its timeline.
Compare with deaths, which are less affected by testing.
Explain doubling time to a younger student.

See Criterion C: personal engagement for what examiners look for.

Which course is it for?

Course	Fit	Maths to lean on
AA SL	Good fit	Exponential models and doubling time; Log-linear regression
AA HL	Good fit	Exponential models and doubling time; Log-linear regression
AI SL	Good fit	Exponential models and doubling time; Log-linear regression
AI HL	Good fit	Exponential models and doubling time; Log-linear regression

Level: Solid. Needs some independent work beyond class examples. See how the IA differs between AA and AI, SL and HL.

How this idea reaches the top bands

Reflection (D)

For this idea, start with the weak points: treating confirmed cases as infections; and choosing intervention dates after seeing the data. Say how each one affects your answer.

Use of mathematics (E)

SL: exponential models and doubling time; log-linear regression; piecewise models before and after an intervention; comparing rates between countries, each explained in your own words and carried out correctly.

How health & biology explorations reach the top bands in general: Health, biology & medicine IA ideas. Guides: A · B · C · D · E · self-grade sheet.

Taking it further

Fit a logistic model and compare its predicted final size with what happened.

Extending it for HL

Add an HL technique the question genuinely needs: what an HL health & biology exploration adds.

See a complete IA, marked

Is it cheaper to leave the heating on low overnight? A two-temperature model of my bedroom (AI HL) is a complete health & biology exploration, marked on every criterion.

Frequently asked questions

Which IB Maths course is this IA idea for?

It works for AA SL, AA HL, AI SL and AI HL. We rate it Solid: it needs some independent work beyond class examples.

What mathematics does this IA use?

Exponential models and doubling time, log-linear regression, piecewise models before and after an intervention and comparing rates between countries.

Where can I get data for this IA?

Daily cumulative cases from the archived Johns Hopkins repository or Our World in Data. Checked sources and tools: WHO Global Health Observatory, Johns Hopkins CSSE COVID-19 data (archived), Our World in Data and Johns Hopkins CSSE COVID-19 repository (archived).

Turn this idea into your IA

The planner opens with “How fast did COVID-19 spread at the start? Comparing doubling times” filled in: the question, the maths and the data sources.

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