i give statistics from an actual study, and you respond with a list of anecdotes?
you are the problem. you can convince yourself of anything, just by cherry picking the right anecdotes. you’ll believe exactly what you want to believe, with no consideration for the truth.
“You are parrotong(sp) what you have been fed by authorities” - Right - they’re authorities because they’re the top relevant medical experts and scientists involved. Reading a twitter thread doesn’t make you an authority. See the difference? What you are doing is parroting (spelling matters) typical antivax conjecture.
What you gave is, as previously mentioned, anecdotes. You could provide a million of them, they’re still anecdotes.
Exposure to the field of statistics? Would you like to talk to the experts involved with VAERS and the like so you can actually get educated about what they find significant?
They are authorities, because they are authorities. Good one. I am really convinced now.
Forget twitter. Mind reading something from the authorities? Check table 2, page number 13, of 41st week review of vaccination by PHE. Last two columns specifically. It states, statistically, that if you are over 30, and vaccinated, you are more likely to to get covid positive than if you are unvaccinated.
And remember, I am not yet referring you to any “antivax conjecture”.
Is being contrarian a good or a bad thing? Sounds like you think it’s a bad thing.
I used to think it’s neither. Some people naturally go with the crowd, some go against it. Going against it doesn’t make you a free thinker, it’s just a different tendency.
But now I think that being a contrarian starts off that way, as just a neutral natural tendency. But it forces you to frequently think deeply about things, because you keep getting in arguments. If you agree with most people you never have to think deeply about anything.
So now I think contrarians are crucial to society, and we should all try to be contradict our natures by engaging seriously (not condescendingly) with them. It foces us to also think deeply about things.
That was interesting, thanks. So table 2 has to looked at together with table 3 and 4. But the same information shown much more clearly in figure 2 on pages 17 and 18.
And page 12 is a fairly good summary, there’s not much I could add to that. Do you agree with page 12 or is there another way of looking at it?
Table 2, 3 and 4 are about different aspects. Table 2 deals with cases testing positive without going into severity of disease while Table 3 and 4 deal only with data about severe cases and terminal ones. Figure 2 makes bar charts of parts of these tables, which maybe clarifying for some.
While it puts the maths right, Page 12 is outright misleading about possible causes. The interpretations therein are carefully worded to guide the uninitiated reader to look away from the vaccines themselves as cause of anything bad.
Another pertinent aspect is that only table 2 (and corresponding figure on page 17) has data relevant to the spread of the virus itself and how vaccination is affecting it; and it does appear that covid is spreading faster in the vaccinated, at least for higher age groups.
While Table 3 and 4 may hint that vaccines are reducing serious illness and deaths, the virus has already proven that it mutates and faster spreading of it will ultimately accelerate mutations and Table 3 and 4 will progressively look worse with passage of time.
These quotes come immediately before and after the cited graph in the report, I’ve shortened them for clarity and brevity:
These data should be considered in the context of vaccination status of the population groups … The vaccination status of cases … is not the
most appropriate method to assess vaccine effectiveness and there is a high risk of
misinterpretation.
it is expected that a large proportion of cases, hospitalisations and deaths would occur in vaccinated individuals, simply because a larger proportion of the population are vaccinated than unvaccinated … This is especially true because vaccination has been prioritised in individuals who are more susceptible or more at risk of severe disease. Individuals in risk groups … thus may be hospitalised or die with COVID-19 rather than because of COVID-19.
Interpretation of the case rates in vaccinated and unvaccinated population is particularly susceptible to changes in denominators
and should be interpreted with extra caution.
Because the elderly and the chronically sick are the most likely to get vaccinated, and the young and healthy are the least likely to get vaccinated, it distorts the numbers to look like getting the vaccine increases your chance of contracting covid.
The report you cited is overflowing with warnings not to misinterpret the data, but you missed all the warnings. Ironically, your own argument is an excellent example why we need authorities to interpret findings for the general public, and why those authorities are deserving of more trust than any stranger on social media.
Of course it is not the most appropriate way to assess vaccine effectiveness. The most appropriate way is isolate the vector (which hasn’t been done till date), then administer it to test subjects (good luck finding willing test subjects), both vaccinated and unvaccinated, and then check the covid positive rates for these test subjects. And then there have to be replication studies to verify results, etc. You’ll need no less than a dictator to get this done.
This is a generalised conjecture which can be refuted by one single appropriate example. As it happens, an appropriate example exists. Waterford, Ireland which has nearly 100% vaccination rate, became a covid positive hotbed soon after vaccination reached high percentage ( check here ).
As it happens, the denominators in the tables have been uniquely specified and rates given in proportion to them. If the PHE have not made any mistakes in making the table, it is highly unlikely that my interpretations have erred on this count.
As for your own interpretation about difference in vaccination rate by age and illness distorting rates of covid contraction, that cannot be addressed without more comprehensive data. But there are distortions from other side as well. For instance, those more likely to contract covid may also be taking more social distancing precautions and maintaining stricter personal hygeine, etc.
Here is a twitter thread listing deaths of vaccinated Indians due to medical issues.
Just Indians alone.
i give statistics from an actual study, and you respond with a list of anecdotes?
you are the problem. you can convince yourself of anything, just by cherry picking the right anecdotes. you’ll believe exactly what you want to believe, with no consideration for the truth.
Dude, that pretty much proves you are parrotong what you have been fed by authorities.
What I gave you is much more than the statistical aggregates you are talking about. Newspapers have published the names, age, etc for each of them.
And I don’t know what is your exposure to the field of statistics, but 5000 “anecdotes” are statistically significant.
Antivaxxer arguments are so incredibly sad.
“You are parrotong(sp) what you have been fed by authorities” - Right - they’re authorities because they’re the top relevant medical experts and scientists involved. Reading a twitter thread doesn’t make you an authority. See the difference? What you are doing is parroting (spelling matters) typical antivax conjecture.
What you gave is, as previously mentioned, anecdotes. You could provide a million of them, they’re still anecdotes.
Exposure to the field of statistics? Would you like to talk to the experts involved with VAERS and the like so you can actually get educated about what they find significant?
They are authorities, because they are authorities. Good one. I am really convinced now.
Forget twitter. Mind reading something from the authorities? Check table 2, page number 13, of 41st week review of vaccination by PHE. Last two columns specifically. It states, statistically, that if you are over 30, and vaccinated, you are more likely to to get covid positive than if you are unvaccinated.
And remember, I am not yet referring you to any “antivax conjecture”.
And yet another problem with antivaxxers - refusal to read unless it fits their narrative.
Sorry, try again.
“Narrative” doesn’t come from anti-establishment folks like me. Our job is to point to holes in the narrative. Ontology 101.
And I don’t need to “try” anything, including vaccines. You can take your jab. Or jabs. Mix and match them, whatever.
“Contrarian” is the word you’re looking for.
Is being contrarian a good or a bad thing? Sounds like you think it’s a bad thing.
I used to think it’s neither. Some people naturally go with the crowd, some go against it. Going against it doesn’t make you a free thinker, it’s just a different tendency.
But now I think that being a contrarian starts off that way, as just a neutral natural tendency. But it forces you to frequently think deeply about things, because you keep getting in arguments. If you agree with most people you never have to think deeply about anything.
So now I think contrarians are crucial to society, and we should all try to be contradict our natures by engaging seriously (not condescendingly) with them. It foces us to also think deeply about things.
Skeptic.
post a link to your source. if you haven’t misunderstood it, that would be very interesting.
Can be accessed from here.
That was interesting, thanks. So table 2 has to looked at together with table 3 and 4. But the same information shown much more clearly in figure 2 on pages 17 and 18.
And page 12 is a fairly good summary, there’s not much I could add to that. Do you agree with page 12 or is there another way of looking at it?
Table 2, 3 and 4 are about different aspects. Table 2 deals with cases testing positive without going into severity of disease while Table 3 and 4 deal only with data about severe cases and terminal ones. Figure 2 makes bar charts of parts of these tables, which maybe clarifying for some.
While it puts the maths right, Page 12 is outright misleading about possible causes. The interpretations therein are carefully worded to guide the uninitiated reader to look away from the vaccines themselves as cause of anything bad.
Another pertinent aspect is that only table 2 (and corresponding figure on page 17) has data relevant to the spread of the virus itself and how vaccination is affecting it; and it does appear that covid is spreading faster in the vaccinated, at least for higher age groups.
While Table 3 and 4 may hint that vaccines are reducing serious illness and deaths, the virus has already proven that it mutates and faster spreading of it will ultimately accelerate mutations and Table 3 and 4 will progressively look worse with passage of time.
These quotes come immediately before and after the cited graph in the report, I’ve shortened them for clarity and brevity:
Because the elderly and the chronically sick are the most likely to get vaccinated, and the young and healthy are the least likely to get vaccinated, it distorts the numbers to look like getting the vaccine increases your chance of contracting covid.
The report you cited is overflowing with warnings not to misinterpret the data, but you missed all the warnings. Ironically, your own argument is an excellent example why we need authorities to interpret findings for the general public, and why those authorities are deserving of more trust than any stranger on social media.
source: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1025358/Vaccine-surveillance-report-week-41.pdf
All three of your quotes can be addressed:
Of course it is not the most appropriate way to assess vaccine effectiveness. The most appropriate way is isolate the vector (which hasn’t been done till date), then administer it to test subjects (good luck finding willing test subjects), both vaccinated and unvaccinated, and then check the covid positive rates for these test subjects. And then there have to be replication studies to verify results, etc. You’ll need no less than a dictator to get this done.
This is a generalised conjecture which can be refuted by one single appropriate example. As it happens, an appropriate example exists. Waterford, Ireland which has nearly 100% vaccination rate, became a covid positive hotbed soon after vaccination reached high percentage ( check here ).
As it happens, the denominators in the tables have been uniquely specified and rates given in proportion to them. If the PHE have not made any mistakes in making the table, it is highly unlikely that my interpretations have erred on this count.
As for your own interpretation about difference in vaccination rate by age and illness distorting rates of covid contraction, that cannot be addressed without more comprehensive data. But there are distortions from other side as well. For instance, those more likely to contract covid may also be taking more social distancing precautions and maintaining stricter personal hygeine, etc.