The relationship between Year 9 data and illness absence data nationwide

Looking at our schools aggregated absences, there is a slight correlation with the data from all schools in England. However, due to a small sample at our school than national, there is more fluctuation, which makes the trend difficult to see and so it makes it hard to draw any accurate conclusions. Although the trend is similar, it is also slightly lower than the national data, which could be due to the positive environment in our school compared to other schools and the willingness of pupils to come to school and put more effort into learning. On the other hand, the reason could be that England is a big place and it snowed a lot more up north, which disrupted pupil’s journeys more and generally made them more ill. Around Christmas, the weather in London was generally milder than in northern England.
The Year 9 data of absences is very similar to the school aggregate, which could be because the majority of the school (including Year 9) do not have exams in January and so would not have pretended to be ill in order to do last minute revision. The most interesting results were that for Year 7 where their absences peaked much higher than our school’s average and national average after the Christmas holidays. This may be the result of their weaker immune systems and the fact that they maybe spend a lot more time touching things and biting nails. Also, it could be due to more of them being on holiday and not coming back in time for school.
The aim was to see the school absences data peak just before people went to their GP and reported flu-like symptoms. However, the most important part of the graph is missing due to the unfortunate timing of the Christmas holidays. The main two weeks of school data is missing which is where it should have peaked and shown a definite correlation. It is therefore unclear what to conclude and we just have to wait until another good, strong outbreak during school time.

One Response to The relationship between Year 9 data and illness absence data nationwide

  1. Dr Rob says:

    Great, you’ve made some really interesting observations on the data. Do you think that Year 7 might also socialise differently to other year groups as this could also impact on how likely they are to get flu? Also, are they also more likely to have younger brothers or sisters in other schools which might also increase their chances of coming into contact with flu?

    In relation to not being able to see a clear trend in your data due to the weekly fluctuations: one thing you might want to try in order to smooth things out is to calculate three week rolling averages. It’s a trick we use in epidemiology quite a lot when we want to smooth out the data. There’s a nice clip about how to do this on you tube here – The clip shows how to do this for sales results, but it’s the same method for our epidemiological data. Let me know if you get stuck and I can try and help out.