Credit: British Government
The growing number of people who test positive for COVID-19 in the UK is increasingly alarmed. More tests have been made available and more people have done these tests, but that alone does not explain the increase in the number of those who test positive, nor why there are such differences between different parts of the nation.
We can examine a number of theories as the basis for this surge. For example, the children returned to Scottish schools on August 11th and eight days later cases in Scotland peaked at 141 before dipping in and then increasing again. A similar pattern was observed in England. It’s also likely that people returning from vacation with the infection contributed to these increases.
The role of schools
Using the government-provided data dashboard, we can enlarge a map of positive COVID-19 tests across the UK. One of the authors of this play, Danny Dorling, lives in Oxford. When the number of cases rose abruptly for the first time, he identified where the largest increase was near his home. This was a neighborhood mainly made up of one school, Eton College, which is in the town of Windsor some distance to the southeast. In the week leading up to September 16, this neighborhood had one of the largest increases in cases reported in the south of England, but there were similar increases in the north as well.
The dashboard shows that there were ten or more cases in the school area for the week of September 10-16. The students had just returned from vacation and “some” of them got positive results when the school decided to test them all, according to Eton. This is a good example of how the number of positive cases increases as more testing is done, but it also shows how reopening schools can increase the number of cases.
By the way, the Manchester Guardian reported 63 years ago – and in a similar fashion to today – that half of the boys in Eton were affected by this year’s pandemic influenza, which also hit the schools in Glasgow badly.
The map below shows how unusual the Eton Cluster was when it formed. It was one of the first educational outbreaks in England that fall. Oxford can be seen to the north of the map and the school is south of Slough. At the time, it was the only neighborhood with 10 to 19 cases in this very large area. Each neighborhood on the map below is called an MSOA (Middle Layer Super Output Area), and there are 6,791 of them in England.
Photo credit: Danny Dorling, author provided
Former hotspots are less affected
Besides the resumption of teaching by certain schools, what could explain why the rate of new cases has increased more in some areas than in others?
The best predictor for England seems to be how badly each neighborhood was affected when the disease first appeared, which is shown in the graph below. If we look at the percentage of all deaths where COVID-19 was mentioned on the death certificate reported in an area in March, April, May and June, we can see that this percentage was below 30% the first time. As a rule, the number of positive cases found later in these districts fluctuates between 0.4 and 1.4 per 1,000 inhabitants and increases linearly with the severity of the first outbreak. This could be as expected if the disease had stayed at higher (albeit still low compared to the peak) levels in some of these locations, or if people in some areas were older or in nursing homes that made them more vulnerable.
There are other possible interpretations of this finding. For one thing, the new cases merely reflect a proportional resurgence of those earlier outbreaks – that is, a continuation of the first wave, which recurs more strongly when more cases have occurred previously. Other possibilities relate to testing. For example, more testing centers may have been set up in areas with more early deaths, so that a greater proportion of all cases are detected in those regions. Other changes in testing procedures could affect the number of cases.
A potentially more significant possibility is suggested in this diagram if we look to the right. This pattern implies that areas with the highest death rate do not have a significant recovery in cases this time around. Particularly in areas where between half and three quarters of all previous deaths are believed to have been caused or directly caused by COVID-19, the number of people who recently tested positive for the disease is falling dramatically.
It is too early to know exactly what the most recently revealed patterns mean epidemiologically. Every week we get more data to help us research this. Random variability is also important, but there are some possible explanations to consider in the short term and others that we cannot elaborate on here.
It could be that enough people in these areas have already been exposed to the virus to make the population less susceptible to the disease. Overall, this would mean that the levels of some forms of immunity are higher in these particular neighborhoods – at a level that results in a demonstrable reduction in the number of new cases.
Such immunity won’t be all or nothing – it won’t mean people are no longer prone to coronavirus infection in any way – but it would mean that people need more sustained exposure to higher viral loads in order to become infected, or if infected will show fewer symptoms and are less likely to be tested. Test schemes could also influence this pattern.
We don’t know which of the above statements explains the inverted U-shaped pattern, but we can confirm that there are 158 such neighborhoods, mostly in London, where relatively few people who were recently tested had positive results. Over the next few weeks, researchers will be watching closely as the number of cases rises in the areas that suffered the most in the spring, particularly London.
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