Scientists have called for transparency over delays in reporting coronavirus cases – blamed by the prime minister on a “computing issue” – amid warnings they could hamper efforts to monitor the spread of the disease.
The number of UK lab-confirmed cases soared to nearly 13,000 on Saturday after a “technical issue” prevented many from 24 September to 1 October from being included in official data.
While health officials claimed that all those tested received their results on time, and would know they had to self-isolate if positive, they did not explain what caused the delay or which groups it affected.
“Openness is essential for public trust,” said Dr Duncan Robertson of Loughborough University, an expert in modelling and policy analytics. “If this is a reporting delay, that’s bad enough, but if there have been delays in putting these cases into the NHS Test and Trace database, that can have serious implications for spreading the disease.”
Boris Johnson told the BBC’s Andrew Marr show on Sunday that the problem was “a failure in the counting system which has now been rectified”. But a spokesperson for the Department for Health and Social Care said more cases from the last week of September would be reported soon.
The delay has held up the publication of positive test results from community testing – pillar two of the government’s testing programme. As well as what caused the fault, it is still unclear why some of the delayed cases will not be made public for days.
“If the technical issue has been resolved, why are we expecting extra cases to be reported over the coming days?” said Robertson. “It would be useful to know which labs have been affected by this technical issue. Is it one particular Lighthouse lab or an independent lab, for example, those being set up at universities or companies?”
The information would help scientists work out whether a particular group of people were affected, such as older people, or those in a certain region.
Accurate data on infection rates are vital for monitoring the spread of the disease and predicting the future evolution of the pandemic. Delays in the reporting can undermine the process, leading to underestimates or overestimates in the R value, the average number of people an infected person infects.
Professor Graham Medley, an outbreak modeller at the London School of Hygiene and Tropical Medicine and a member of Sage, tweeted: “Reporting delays play havoc with data streams and make them very difficult to analyse in real time. If the delays change or vary by group then they can distort a lot. Wonder what these will do to the R estimates next week?”
Jonathan Read, a biostatistician at Lancaster University who sits on the Sage outbreak modelling subgroup, added: “An apparent surge in cases due to a change in reporting delays, unless accounted for, will look like the epidemic is growing and so the reproduction number could be overestimated.”