‘Gabriela Gomes studies chaos. Specifically, patterns in nonlinear dynamics... So with all its apparently chaotic eccentricities, the coronavirus was an ideal challenge for Gomes, a professor at the University of Strathclyde, in Glasgow, Scotland... Based on data from several countries in Europe, she said, her results show a herd-immunity threshold much lower than that of other models. “We just keep running the models, and it keeps coming back at less than 20 percent,” Gomes said. “It’s very striking.”
‘If that proves correct, it would be life-altering news. It wouldn’t mean that the virus is gone. But by Gomes’s estimates, if roughly one out of every five people in a given population is immune to the virus, that seems to be enough to slow its spread to a level where each infectious person is infecting an average of less than one other person. The number of infections would steadily decline...
There are two more arguments in the story, citing levels from 20 to 70 percent... The conclusion, as stated in the subhead: ‘The portion of the population that needs to get sick is not fixed. We can change it.’
Read here (The Atlantic, July 13, 2020)
Showing posts with label mathematical modelling. Show all posts
Showing posts with label mathematical modelling. Show all posts
Monday, 13 July 2020
Wednesday, 1 April 2020
Mathematical modelling, "herd immunity" and the resultant failure of "test, test, test" in Britain
‘According to Richard Horton, editor-in-chief of the Lancet medical journal, the dominant voices in the Scientific Advisory Group for Emergencies (Sage), the scientific expert group advising the government, were mathematical modellers and behavioural scientists, including [David] Halpern...
‘Testing, isolation and quarantine – basic public health interventions – were barely on the agenda. Warnings from Chinese scientists of the severity of Covid-19 had not been understood.
‘“We thought we could have a controlled epidemic. We thought we could manage that epidemic over the course of March and April, push the curve to the right, build up herd immunity and that way we could protect people,” said Horton. “The reason why that strategy was wrong is it didn’t recognise that 20% of people infected would end up with severe critical illness. The evidence was there at the end of January.”
‘Anthony Costello, a UK paediatrician and former director of the WHO, also fiercely criticised the decision to stop tests. “For me and the WHO people I have spoken to, this is absolutely the wrong policy,” he said. “The basic public health approach is playing second fiddle to mathematical modelling.”
Read here (The Guardian, April 1, 2020)
‘Testing, isolation and quarantine – basic public health interventions – were barely on the agenda. Warnings from Chinese scientists of the severity of Covid-19 had not been understood.
‘“We thought we could have a controlled epidemic. We thought we could manage that epidemic over the course of March and April, push the curve to the right, build up herd immunity and that way we could protect people,” said Horton. “The reason why that strategy was wrong is it didn’t recognise that 20% of people infected would end up with severe critical illness. The evidence was there at the end of January.”
‘Anthony Costello, a UK paediatrician and former director of the WHO, also fiercely criticised the decision to stop tests. “For me and the WHO people I have spoken to, this is absolutely the wrong policy,” he said. “The basic public health approach is playing second fiddle to mathematical modelling.”
Read here (The Guardian, April 1, 2020)
Monday, 4 April 2016
The new astrology: By fetishising mathematical models, economists turned economics into a highly paid pseudoscience
‘Nonetheless, surveys indicate that economists see their discipline as ‘the most scientific of the social sciences’. What is the basis of this collective faith, shared by universities, presidents and billionaires? Shouldn’t successful and powerful people be the first to spot the exaggerated worth of a discipline, and the least likely to pay for it?
‘In the hypothetical worlds of rational markets, where much of economic theory is set, perhaps. But real-world history tells a different story, of mathematical models masquerading as science and a public eager to buy them, mistaking elegant equations for empirical accuracy.’
[Note: This is an old article published April 4, 2016. We should read this in the context of the epidemiological modelling being used now to forecast Covid-19.]
Read here (Aeon, April 4, 2016)
‘In the hypothetical worlds of rational markets, where much of economic theory is set, perhaps. But real-world history tells a different story, of mathematical models masquerading as science and a public eager to buy them, mistaking elegant equations for empirical accuracy.’
[Note: This is an old article published April 4, 2016. We should read this in the context of the epidemiological modelling being used now to forecast Covid-19.]
Read here (Aeon, April 4, 2016)
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