CO2, flu, COVID & you (schools)

This is the homepage for schools event Jan 2026. It is just to bring together the materials for the day in one place.

The intro/context talk/demo is done with this Python Jupyter notebook on Google Colab.

The event has a Streamlit app, this app is available on

which fits (built in to the app) 6 data sets, each is for the CO3 ppm (parts per million) concentration in air, for one day. The code for the app is here on GitHub.

So run the app, pick one of the 6 data sets and then look at the plot, and ask the questions a scientist would, eg:

  1. When is the CO2 level high? When is it low? Bearing in mind that good air quality is often defined at around 1000 ppm CO2 (1.5 % second-hand air) or less, is the air quality always good? Sometimes bad?
  2. In most cases (almost) all CO2 in a room comes from humans, and it is removed by ventilation (out of open window or door, mechanical ventilation in larger buildings). So if the ppm CO2 is increasing (plot has upward slope) then more CO2 is being breathed out, than is leaving via windows/mechanical ventilation. So when ppm CO2 is increasing in a plot, why is this? What does this tell you about what is happening in the room? When ppm CO2 is decreasing (downwards slope), why is this?
  3. If the ppm CO2 is too high, or increasing too fast, what can you do to stop this?

The app will fit to data between start and end times that you can set in the app. It will also (if you toggle to this mode) estimate the average fraction of second-hand air in any hour-long period with a start time you set.

For more thoughts on COVID transmission you can read some blog posts, from my blog.