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02 July 2020

New potential COVID hotspots detected by app

Data modelling from King's using data from the COVID Symptom Study app is able to identify potential COVID hotspots in the UK.

Transmission electron micrograph of SARS-CoV-2 virus particles captured by NIAID.
Transmission electron micrograph of SARS-CoV-2 virus particles captured by NIAID.

The modelling highlights key local authorities as potential new hotspots. As well as Leicester which is already back in lockdown, the data has highlighted Dudley and Wolverhampton as other areas in The Midlands that could be heading in the same direction.

There are three key criteria for identifying hotspots. The local authority area must:

  • have significantly higher prevalence than its neighbouring authorities;
  • be in the top 10th percentile of prevalence for the UK, and;
  • that prevalence is higher today than 10 days ago.

This method for estimating prevalence is based on the assessments of 3.7M UK app users, using the validated model to predict COVID-19 positivity based on symptoms and combine it with swab test results reported by app users.

This model can find areas in the country that have a prevalence which is higher than its neighbours and is likely to lead to an increase in confirmed cases and hospitalisation in the following 5 and 12 days respectively. The same model predicted Barnsley and Rochdale to be hotspots back on June 17th but these areas no longer rank highly.

According to the latest figures from the app, there are currently an estimated 1,445 daily new cases of COVID in the UK on average over the two weeks, 14 to 27 June 2020. The number of cases has continued to fall nationally, and this week the number fell by 34 % since last week. The highest rates of new cases are still found in The Midlands.

The figures were based on 10,393 swab tests from 14 to 24 June based on 31 positive results.


Incidence of total new cases per day





South East






East of England


South West


North East and Yorkshire


North West






The prevalence figures are available here. The prediction model used to estimate prevalence has been peer-reviewed in Nature Medicine.

Tim Spector, Professor of Genetic Epidemiology at King's, said: 'This fresh look at the data was inspired by the local lockdown in Leicester, we challenged ourselves to see if our app data could highlight any other local hotspots and we are really pleased that it does. The new model picked up Leicester as a consistent hotspot back on the 17th June which suggests it is accurately picking up places of concern.'

With our data now flagging up potential new hotspots, it will allow for greater surveillance and focussed testing that could detect problems like Leicester much earlier and hopefully reduce the number of major lockdowns. But to do this more successfully we still need more people to join us by logging how they are feeling each day so we can send out kits to those feeling unwell and catch these outbreaks and help us closely monitor what is going on in the UK population.

Tim Spector, Professor of Genetic Epidemiology

In this story

Tim Spector

Professor of Genetic Epidemiology