Trademark symptoms of seasonal flu could be mistaken for symptoms of Covid-19, it is claimed
People with common colds who are testing positive for Covid-19 may simply be asymptomatic cases, experts have said.
Trademark symptoms of seasonal flu could be mistaken for symptoms of Covid-19 if the individual tests positive for the virus, it is claimed.
More than eight in ten people who test positive for coronavirus show none of the main symptoms at the time they are tested, a major study by UCL previously revealed.
- SAGE admitted early virus modelling based on figures from online encyclopedia
- Committee of scientists advising PM also had no expert on human coronavirus
- Dubious data formed the basis for the group’s calls for first national lockdown
- Experts predicted that the peak would be in June – but it actually came in April
- Impact of care home staff spreading Covid by working in multiple sites not considered
- Scientists failed to consider the impact agency workers would have on spreading Covid in care homes by moving between several different sites to work
- There were more than 30,000 excess deaths in care homes because of Covid in 2020
Professor Mark Jit, an epidemiologist at the London School of Hygiene and Tropical Medicine and member of SPI-M, said the group used data from Wikipedia in the UK along with hospitalisations in China and Northern Italy to inform their modelling.
On March 25, just a day after Britain shut down, economist Professor Philip Thomas, of Bristol University, made a grim prediction.
If the country remained in lockdown for longer than two months, he warned, any lives saved would be wiped out by those lost from the impact of the inevitable recession.
Britain hit that timeline more than a fortnight ago, but restrictions largely remain in place and there is growing alarm among economists that the cure has become far deadlier than the disease.
Prof Thomas now estimates that 150,000 people could die from Covid-19 over five years under the intermittent lockdown conditions necessary to keep infection rates, or the reproduction ‘R’ number, below one if a vaccine is not found.
Modelling by Professor Simon Wood, of the school of mathematics at the University of Bristol, shows that the majority of people who died at the peak would have been infected roughly five days before the lockdown was introduced.
By simply separating out weekly reporting variability, the long-term death rate profile becomes clear, and its peak can be located with confidence. Using the distribution of times from disease onset to death, it is possible to extend the model to infer the time course of fatal infections required to produce the later deaths. Because of the wide variability in onset to death times, a quite sharply peaked infection curve produces a death curve that declines only slowly. The inferred infection curve peaks a few days before lockdown, with fatal infections now likely to be occurring at a much-reduced rate.