deptfordmarmoset
Full time tea drinker
- Location
- Armonmy Way
Reuters ok as a source?
https://www.reuters.com/article/us-...patients-testing-positive-again-idUSKCN21S15X
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https://www.reuters.com/article/us-...patients-testing-positive-again-idUSKCN21S15X
delb0y
Legendary Member
- Location
- Quedgeley, Glos
Link for my Korean story is the Beeb:
https://www.bbc.co.uk/news/live/world-52239925
Update was at 14:58
Mod note.
Source checked and confirmed and here is the content:
South Korean patients thought cured test positive again
South Korean health authorities say 91 people thought recovered after contracting coronavirus have tested positive for the disease again.
The Korea Centers for Disease Control and Prevention (KCDC) said on Friday it was not clear why the patients had tested positive for a second time.
KCDC director Jeong Eun-kyeong told a news conference it was possible that the virus had “reactivated” in the patients, as opposed to them being re-infected.
Other health experts suggested the patients may have "relapsed” or been misdiagnosed by faulty tests.
The results will be of keen interest internationally, as health experts worldwide hope people infected by Covid-19 will develop immunity to the disease, allowing them to return to work.
https://www.bbc.co.uk/news/live/world-52239925
Update was at 14:58
Mod note.
Source checked and confirmed and here is the content:
South Korean patients thought cured test positive again
South Korean health authorities say 91 people thought recovered after contracting coronavirus have tested positive for the disease again.
The Korea Centers for Disease Control and Prevention (KCDC) said on Friday it was not clear why the patients had tested positive for a second time.
KCDC director Jeong Eun-kyeong told a news conference it was possible that the virus had “reactivated” in the patients, as opposed to them being re-infected.
Other health experts suggested the patients may have "relapsed” or been misdiagnosed by faulty tests.
The results will be of keen interest internationally, as health experts worldwide hope people infected by Covid-19 will develop immunity to the disease, allowing them to return to work.
Last edited by a moderator:
The Crofted Crest
Veteran
A lengthy but relevant article from the Royal Statistical Society
All models are wrong, but some are completely wrong
At this critical time in the modern history of the human race, mathematical models have been pushed into the foreground. Epidemic forecasting informs policy and even individual decision-making. Sadly, scientists and journalists have completely failed to communicate how these models work.
Last week the Financial Times published the headline ‘Coronavirus may have infected half of UK population’, reporting on a new mathematical model of COVID-19 epidemic progression. The model produced radically different results when the researchers changed the value of a parameter named ρ – the rate of severe disease amongst the infected. The FT chose to run with an inflammatory headline, assuming an extreme value of ρ that most researchers consider highly implausible. [1]
Since its publication, hundreds of scientists have attacked the work, forcing the original authors to state publicly that they were not trying to make a forecast at all. But the damage had already been done: many other media organisations, such as the BBC, had already broadcast the headline.
Epidemiologists are making the same mistakes that the climate science community made a decade ago. A series of crises forced climatologists to learn painful lessons on how (not) to communicate with policy-makers and the public.
In 2010 the 4th IPCC report was attacked for containing a single error – a claim that the Himalayan glaciers would likely have completely melted by 2035 (‘Glacier Gate’). Climate denialists and recalcitrant nations such as Russia and Saudi Arabia seized on this error as a way to discredit the entire 3000 page report, which was otherwise irreproachable.
When the emails of the Climatic Research Unit (CRU) of University of East Anglia were hacked in 2009, doubt arose over the trustworthiness of the entire climate science community. Trust was diminished because the head of the CRU refused to openly share computer code and data. The crisis was to cast a pall over the climate science community for many years.
By the time of the 5th IPPC report, mechanisms had been developed to enforce clear communication about the uncertainty surrounding predictive models; and transparency about models and data. The infectious disease community needs to learn these lessons. And learn them quickly.
Over the last days, several infectious disease non-experts have gained media coverage for various ‘too good to be true’ (and plain wrong) coronavirus forecasts. Ideologically-driven commentators have used these results to justify easing of social distancing rules, with potentially devastating consequences.
Scientists and journalists have a moral responsibility to convey the uncertainty inherent in modelling work. There is much at stake. Here we recommend a handful of rules for policy-makers, journalists and scientists.
Rule 1. Scientists and journalists should express the level of uncertainty associated with a forecast
All mathematical models contain uncertainty. This should be explicit – researchers should communicate their own certainty that a result is true. A range of plausible results should be provided, not just one extreme result.
Rule 2. Journalists must get quotes from other experts before publishing
The worst cases of poor COVID-19 journalism have broken this simple rule. Other scientists have weighed in after publication. But by then a misleading article has reached an audience of millions and taken hold in the public consciousness.
Rule 3. Scientists should clearly describe the critical inputs and assumptions of their models
How sensitive is the model to the input parameters? How sure are you of those parameters? Do other researchers disagree?
Rule 4. Be as transparent as possible
Release data and code so that scientific scrutiny can take place. Consider open peer-review so that other experts can quickly give their opinion on a piece of work.
Rule 5. Policy-makers should use multiple models to inform policy
The Imperial college model created by Neil Ferguson has been reported on almost exclusively as the modelling input to UK pandemic policy. Have other models from other groups been considered? What is the degree of agreement between the models?
Rule 6. Indicate when a model was produced by somebody without a background in infectious diseases
Would we encourage an epidemiologist to apply ‘fresh thinking’ to the design of an electrical substation? Perhaps we should treat with caution the predictions of electrical engineers about pandemic disease outbreaks.
Martin Goodson (Chair of the RSS Data Science Section)
Notes
[1] Post-publication, the FT have modified the report text but have left the headline unchanged.
All models are wrong, but some are completely wrong
At this critical time in the modern history of the human race, mathematical models have been pushed into the foreground. Epidemic forecasting informs policy and even individual decision-making. Sadly, scientists and journalists have completely failed to communicate how these models work.
Last week the Financial Times published the headline ‘Coronavirus may have infected half of UK population’, reporting on a new mathematical model of COVID-19 epidemic progression. The model produced radically different results when the researchers changed the value of a parameter named ρ – the rate of severe disease amongst the infected. The FT chose to run with an inflammatory headline, assuming an extreme value of ρ that most researchers consider highly implausible. [1]
Since its publication, hundreds of scientists have attacked the work, forcing the original authors to state publicly that they were not trying to make a forecast at all. But the damage had already been done: many other media organisations, such as the BBC, had already broadcast the headline.
Epidemiologists are making the same mistakes that the climate science community made a decade ago. A series of crises forced climatologists to learn painful lessons on how (not) to communicate with policy-makers and the public.
In 2010 the 4th IPCC report was attacked for containing a single error – a claim that the Himalayan glaciers would likely have completely melted by 2035 (‘Glacier Gate’). Climate denialists and recalcitrant nations such as Russia and Saudi Arabia seized on this error as a way to discredit the entire 3000 page report, which was otherwise irreproachable.
When the emails of the Climatic Research Unit (CRU) of University of East Anglia were hacked in 2009, doubt arose over the trustworthiness of the entire climate science community. Trust was diminished because the head of the CRU refused to openly share computer code and data. The crisis was to cast a pall over the climate science community for many years.
By the time of the 5th IPPC report, mechanisms had been developed to enforce clear communication about the uncertainty surrounding predictive models; and transparency about models and data. The infectious disease community needs to learn these lessons. And learn them quickly.
Over the last days, several infectious disease non-experts have gained media coverage for various ‘too good to be true’ (and plain wrong) coronavirus forecasts. Ideologically-driven commentators have used these results to justify easing of social distancing rules, with potentially devastating consequences.
Scientists and journalists have a moral responsibility to convey the uncertainty inherent in modelling work. There is much at stake. Here we recommend a handful of rules for policy-makers, journalists and scientists.
Rule 1. Scientists and journalists should express the level of uncertainty associated with a forecast
All mathematical models contain uncertainty. This should be explicit – researchers should communicate their own certainty that a result is true. A range of plausible results should be provided, not just one extreme result.
Rule 2. Journalists must get quotes from other experts before publishing
The worst cases of poor COVID-19 journalism have broken this simple rule. Other scientists have weighed in after publication. But by then a misleading article has reached an audience of millions and taken hold in the public consciousness.
Rule 3. Scientists should clearly describe the critical inputs and assumptions of their models
How sensitive is the model to the input parameters? How sure are you of those parameters? Do other researchers disagree?
Rule 4. Be as transparent as possible
Release data and code so that scientific scrutiny can take place. Consider open peer-review so that other experts can quickly give their opinion on a piece of work.
Rule 5. Policy-makers should use multiple models to inform policy
The Imperial college model created by Neil Ferguson has been reported on almost exclusively as the modelling input to UK pandemic policy. Have other models from other groups been considered? What is the degree of agreement between the models?
Rule 6. Indicate when a model was produced by somebody without a background in infectious diseases
Would we encourage an epidemiologist to apply ‘fresh thinking’ to the design of an electrical substation? Perhaps we should treat with caution the predictions of electrical engineers about pandemic disease outbreaks.
Martin Goodson (Chair of the RSS Data Science Section)
Notes
[1] Post-publication, the FT have modified the report text but have left the headline unchanged.
midlife
Guru
deptfordmarmoset
Full time tea drinker
- Location
- Armonmy Way
And the BBC report is a summary of the Reuters link posted above.
LCpl Boiled Egg
Three word soundbite
The Reuters link says
"Jeong Eun-kyeong, director of the Korea Centers for Disease Control and Prevention (KCDC), told a briefing that the virus may have been “reactivated” rather than the patients being re-infected.
The KCDC’s Jeong raised the possibility that rather than patients being re-infected, the virus may have been “reactivated”.
Kim also said patients had likely “relapsed” rather than been re-infected."
which means
isn't what the article says.
"Jeong Eun-kyeong, director of the Korea Centers for Disease Control and Prevention (KCDC), told a briefing that the virus may have been “reactivated” rather than the patients being re-infected.
The KCDC’s Jeong raised the possibility that rather than patients being re-infected, the virus may have been “reactivated”.
Kim also said patients had likely “relapsed” rather than been re-infected."
which means
isn't what the article says.
deptfordmarmoset
Full time tea drinker
- Location
- Armonmy Way
And, overlapping with the question of immunity, no information is given about the gravity of the illness in these reinfected, reactivated or relapsed patients. Do they feel tickety-boo, are they laid low for a couple of weeks, are they hospitalised, on ventilators or dying? If there is a lower risk factor for them, there is some indication of a degree of immunity having been acquired.
AuroraSaab
Veteran
I might have posted this before, but I don't see why shops like B and M, The Range etc. can't cordon off their non food, non meds, non toiletries aisles. I am sure it would even be possible to make it so the software on the tills wouldn't process non food/non meds. It make the current recreational shopping a bit less attractive, whereas now it's possible to supposedly go out for an essential packet of aspirin and come home with 3 rugs and a mirror.
I think as a nation we are just so addicted to recreational shopping it's very hard to give up. Grocery shopping doesn't have the same appeal.
I think as a nation we are just so addicted to recreational shopping it's very hard to give up. Grocery shopping doesn't have the same appeal.
1st old Matt come out with his 5 pillars of testing now he's come up with a 3 part plan for PPE.
His 5 pillars look to have got lost in the post now the 3 part plan look's like making things even worse.
All we need is less big statements and posh looking diagrams and more of just handing it over.
To ones who can just get on with it and make it work.
His 5 pillars look to have got lost in the post now the 3 part plan look's like making things even worse.
All we need is less big statements and posh looking diagrams and more of just handing it over.
To ones who can just get on with it and make it work.
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Rocky
Hello decadence
I’m afraid I’ve stopped listening to him and Van Tam. I don’t like being told lies or threatened or mislead.....in some aspects they are not following the science (public wearing masks for example)
BoldonLad
Not part of the Elite
- Location
- South Tyneside
Not all shopping in the non-food section is recreational. There are many homeless people who have recently been housed, but, because of “the virus”, the back up systems to provide basic household items (eg kettle etc) are struggling to cope. BM, Wilco are invaluable in this situation.
The questions they get asked are even worse. The HSJ guy asked a question which was so long I still have now idea what it was.
I've read shorter academic papers.
- Location
- Somewhere wet & hilly in NW England.
From the Beeb - update on Apple/Google Covid tracking protocol:
https://www.bbc.co.uk/news/technology-52246319
https://www.bbc.co.uk/news/technology-52246319
BoldonLad
Not part of the Elite
- Location
- South Tyneside
