The "second wave" of Covid-19 in November was somewhat exacerbated by the presence of the students, but the "third wave" in January definitely was not.
Interpretation: Once students returned, infection numbers within the University were rather high but quickly brought under control. Then, at the beginning of November, roughly two weeks after the University's initial peak, city numbers rose rapidly, possible as a consequence. Shortly afterwards, University numbers went up sharply, but were again very quickly brought under control and are were almost at zero in early December. Assuming that all University staff and students get tested by the University and not elsewhere, the fact that the overall city numbers were falling much more slowly than the University's implies that net numbers in the city were risingi by late November, and keep doing so, if at a slower rate than elsewhere.
"Cambridge minus University" shows the Cambridge data, as the red curve, but with the number of positive results from the two University testing programmes subtracted and the Cambridge population () reduced by the University population () for all dates between 4 Oct and 6 Dec. The same was done to obtain the "Greater Cambridge minus University" curve. This is because positive tests obtained by the University also feed into the government figures and therefore also show in the regional data. We wanted to separate these out.
"Cambridge University" shows positive tests taken under the University's testing programme from people who show Covid-19 symptoms and are either staff or students at the University. This programme started operating on 5 Oct and appears to have ended on 6 Dec.
"Cambridge University asymptomatic" shows positive tests taken under the University's asymptomatic testing programme of college-resident undergraduate and postgraduate students who show no Covid-19 symptoms. This programme also ran from 5 Oct to 6 Dec. The number of students tested is reported explicitly, and it is this number on which we base the "per 100000" quotient. In contrast to other testing, the participants are randomly chosen from each student "household" and represent a very good sample (about one third of the total number of resident students each week). These are the first good data we know of that show the actual prevalence of infections in a good sample of an albeit very specific population.
University data are reported weekly. If no new data have yet been reported, we use the previous week's rate.
- The upwards bumps in the official data for Cambridge over the month of October and again in early November were due to the influx of students. If University testing results are taken out of the data, the resulting curve for Cambridge shows only a slightly greater increase than the curve for South Cambridgeshire over the same time.
- The outbreaks at the University were quickly brought under control, presumably by testing of further co-resident students and isolation measures.
- The "hidden number" of asymptomatic but nevertheless infectious Covid-19 infections may well be up to 3-4 times as high as the number of people actually falling ill, but —
- The "hidden number"will include an unknown number of pre-symptomatic cases, i.e. people who will in fact develop symptoms later and would then have been included in the official data anyway. We are fairly confident that various research teams at the University are busy studying the numbers and will develop a fuller picture of the typical course of infections at least in young people. As always, the deliberate changing of the natural course of events (such as self-isolation) will distort the statistics but save lives!
- We have treated the data as if all members of the University were resident in Cambridge City. This is probably true for the approximately 24000 undergraduate and postgraduate students but a good number of staff members live in South Cambridgeshire or further afield.