A new website that predicts COVID-19 ‘hotspots’ in England and Wales has suggested Cardiff, Leeds and Breckland could all see a major uptick in cases.
Imperial College London has used reported cases and deaths to estimate the probability of different regions becoming hotspots for the virus in the next three weeks and has published the results on an interactive website.
Using data and mathematical modelling, each local authority is given a percentage probability that it will become a hotspot in the following week.
Places already experiencing high levels of coronavirus cases appear higher up the list. Bolton, currently at the top, has a 98% chance of being a hotspot in the week starting September 13.
However, other areas currently not experiencing high numbers of cases are also on the list.
Leeds, which had 32.2 cases per 100,000 in the week starting August 23, only has a 20% chance of becoming a hotspot this week. However, the website predicts it has an 85% chance of becoming a hotspot by September 19.
Cardiff is another city seeing low case numbers at the moment, with just 18 per 100,000 in the week starting August 23. It currently has only an 8% chance of becoming a hotspot this week, but this rockets to 71% by September 19.
Breckland in Norfolk is also one of the most at-risk areas, with 31.6 cases per 100,000 in the last week of August and a 32% chance of becoming a hotspot this week, but an 81% chance by September 19.
Oldham, which is currently on local lockdown, is one of the few places in the country where the website predicts the chances of it remaining a hotspot actually decrease over the next few weeks.
The town, in Greater Manchester, is already a hotspot by the website’s definition, with 58.1 cases per 100,000. However, it’s predicted that its chances of remaining a hotspot fall to just 45% by September 19.
The team behind the website define a hotspot as a local authority where there are more than 50 cases of COVID-19 per 100,000 of the population per week.
The site also provides estimates for each local authority in England and Wales, on whether cases are likely to be increasing or decreasing in the following week and the probability of the important R number being greater than one by September 19.
Leeds, Cardiff, and Breckland have a 99% chance of seeing an R number higher than one, in three weeks’ time.
Oldham’s chance of having an R number higher than one, in three weeks’ time, is just 25%.
The R number indicates the number of people each infected person will pass the virus on to. An R number greater than 1 indicates the outbreak is not under control and cases will continue to increase.
The team who manage the site say they will update it daily.
Lead researcher Professor Axel Gandy, from the Department of Mathematics at Imperial, said: “The model allows us to project where local hotspots of COVID-19 are likely to develop in England and Wales based on the trends that we are seeing in those areas.
“COVID-19 is, unfortunately, very much still with us, but we hope this will be a useful tool for local and national governments trying to bring hotspots under control.”
The website generally predicts an increase in coronavirus cases across the country, with the only places seeing a major decline in infections being the ones currently under local lockdowns.
Coronavirus cases have reached their highest rate since June recently, fuelling fears of a second wave.
A total of 6,732 people tested positive for COVID-19 in the last week of August, the highest seven-day number since June 3.
However, the percentage of positive tests compared to the number of tests carried out is lower than in early June as the government continues to ramp up testing.
Health secretary Matt Hancock told the BBC’s Today programme earlier he believed efforts to combat the virus was going well, but he remained “very worried” about a second wave.
The predictions on the website assume no change in current interventions in a local authority beyond those already taken about a week before the end of observations.
Each local authority is also treated independently of its neighbours in the modelling so the epidemic in one local authority does not affect or is not affected by the situation in any adjacent local authority.
The team also noted that an increase in cases in a local authority can be due to an increase in testing, which the model does not currently account for.
The model also assumes all individuals within each local authority are equally likely to be infected, so demographic factors, such as age, are not considered.
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