Body & Soul7 mins ago
When Releasing Covid Infection Figures, Shouldn't They Also Release The Number Of Tests Carried Out?
This would give us a running daily actual proportion of tests against positive results.
Answers
//It’s all there if you want to blind yourself with statistics// It’s those who are blind to those statistics whom the government depends upon for its message. Some people who are a little inquisitive may find it extremely odd that on the day that the “truly astonishing” infection figures of 77k were announced, there were also the highest number of tests...
10:56 Fri 17th Dec 2021
Have a look at my answer at 17:00 yesterday to this question, dave:
https:/
I'm off out for a while. Will reply fully later.
https:/
I'm off out for a while. Will reply fully later.
Someone asked that before and the answer is still the same: it might be interesting but what on earth benefit would it have? And how would you do it anyway as I’m sure many people don’t bother to report negative tests. We never have.
I agree that what matters more is the actual number of cases and the actual number who would test positive: I suspect you wouldn’t be so keen on that :-)
I agree that what matters more is the actual number of cases and the actual number who would test positive: I suspect you wouldn’t be so keen on that :-)
//but what on earth benefit would it have? //
Well it would go a long way to being open, honest and operating with integrity, which at the moment is lacking in spades.
Being open with the data also ensures you dont lend credence to conspiracy theorists who will constantly latch onto the twisted data currently given out. It also means you are not accused of crying wolve. Something else that is currently happening.
Of course, being open also means its more difficult to scare people. If that is your aim(RE Fergusons comments last year)
Well it would go a long way to being open, honest and operating with integrity, which at the moment is lacking in spades.
Being open with the data also ensures you dont lend credence to conspiracy theorists who will constantly latch onto the twisted data currently given out. It also means you are not accused of crying wolve. Something else that is currently happening.
Of course, being open also means its more difficult to scare people. If that is your aim(RE Fergusons comments last year)
Having a dedicated website that provides all the information you required, and more, seems to me to be pretty open. I'm also pretty sure that these announcements, including testing data, are made in the Press conferences, while the page I provided is regularly linked to in the daily update on the UK HSA's twitter feed.
It's true that the testing data gets less emphasis than case data, but it's still easily available, requires barely any digging, and is probably more of a distraction than anything else. For example, since multiple tests can often refer to a single individual, it follows that interpreting the positivity rate from the cases/tests ratio alone is misleading.
It's true that the testing data gets less emphasis than case data, but it's still easily available, requires barely any digging, and is probably more of a distraction than anything else. For example, since multiple tests can often refer to a single individual, it follows that interpreting the positivity rate from the cases/tests ratio alone is misleading.
Yes, on the subject of misleading...
Firstly, a case figure for any given day is almost certainly an undercount. You'd need to test everybody, and you'd need a perfectly reliable test, to obtain the true figure, neither of which is the case. So we had more than 35,000 cases this time last year, and we had more than 90,000 cases yesterday, it's just that we missed some.
Secondly, if testing were performed in the same volumes, then this wouldn't matter, and you'd be able presumably to say that the correction factor to get the true figure would probably be the same. But this is not true. The UK performed approximately five times as many tests yesterday as opposed to this time last year. It's difficult to translate this meaningfully to the "true" count last year, for reasons I mentioned above, but still, one could fairly deduce that the "correction factor" to recover true is much larger last year than this year, making the true figures likely similar (rather than differing by almost three times).
Finally, although vaccines do have an impact on the spread of Covid (davebro is partially wrong in this regard, although it's clear that for Omicron the impact is somewhat reduced), the main benefit of vaccination is in ensuring that once you catch the disease you are (a) less likely to pass it on yourself, and (b) far less likely to have a serious case. Both of these will be enhanced by taking the third shot.
As to Khandro's post, I suspect this is the "post hoc ergo propter hoc" fallacy. Like any medical intervention, vaccines can never be perfectly safe, but the risk factors are significantly less than implied by his post/ancedotal evidence. It's more likely to be sadly the inevitable consequence of getting older, as the chances of a mini-stroke increase as we age.
Firstly, a case figure for any given day is almost certainly an undercount. You'd need to test everybody, and you'd need a perfectly reliable test, to obtain the true figure, neither of which is the case. So we had more than 35,000 cases this time last year, and we had more than 90,000 cases yesterday, it's just that we missed some.
Secondly, if testing were performed in the same volumes, then this wouldn't matter, and you'd be able presumably to say that the correction factor to get the true figure would probably be the same. But this is not true. The UK performed approximately five times as many tests yesterday as opposed to this time last year. It's difficult to translate this meaningfully to the "true" count last year, for reasons I mentioned above, but still, one could fairly deduce that the "correction factor" to recover true is much larger last year than this year, making the true figures likely similar (rather than differing by almost three times).
Finally, although vaccines do have an impact on the spread of Covid (davebro is partially wrong in this regard, although it's clear that for Omicron the impact is somewhat reduced), the main benefit of vaccination is in ensuring that once you catch the disease you are (a) less likely to pass it on yourself, and (b) far less likely to have a serious case. Both of these will be enhanced by taking the third shot.
As to Khandro's post, I suspect this is the "post hoc ergo propter hoc" fallacy. Like any medical intervention, vaccines can never be perfectly safe, but the risk factors are significantly less than implied by his post/ancedotal evidence. It's more likely to be sadly the inevitable consequence of getting older, as the chances of a mini-stroke increase as we age.
we are covering ground already well covered by the prof
a few says ago - when everyone bowed and thanked him prettily and (as I suspected) didnt understand a word
Jim's first para misinterprets sampling - the bigger the sample the closer it is to the population figure ( of whatever it is you are measuring)
His second para can be countered with ratios - in which case total number tested is relevant. This is called scaling by most of us (rates by NJ but he is an outlier, pun intended)
Final para - scarred by mutation - that was then R=1 about and now R=2,3 or 4
so - - - either correct for R
OR use the differences to estimate R
in short, in AB-speak, more cases because 'more contagious' -
and finally - we have the total tests 1.5m - and the total pozzies cd estimate the prevalence ( how much there is in the community as a ratio and not a rate - that would be incidence)
BUT - they are self selected as some are testing because they are symptomatic, so the ratio is likely to be higher
so the simple question
"foo why dont day do the bottom line" ( denominator ) or total number done
has some quite complex statistical points hidden away
which quite honestly i dont understand so I dont expect you to.
a few says ago - when everyone bowed and thanked him prettily and (as I suspected) didnt understand a word
Jim's first para misinterprets sampling - the bigger the sample the closer it is to the population figure ( of whatever it is you are measuring)
His second para can be countered with ratios - in which case total number tested is relevant. This is called scaling by most of us (rates by NJ but he is an outlier, pun intended)
Final para - scarred by mutation - that was then R=1 about and now R=2,3 or 4
so - - - either correct for R
OR use the differences to estimate R
in short, in AB-speak, more cases because 'more contagious' -
and finally - we have the total tests 1.5m - and the total pozzies cd estimate the prevalence ( how much there is in the community as a ratio and not a rate - that would be incidence)
BUT - they are self selected as some are testing because they are symptomatic, so the ratio is likely to be higher
so the simple question
"foo why dont day do the bottom line" ( denominator ) or total number done
has some quite complex statistical points hidden away
which quite honestly i dont understand so I dont expect you to.
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