Moderator: 3ne2nr Mods
adnj wrote:*sigh*drchaos wrote:Dohplaydat wrote:drchaos wrote:Yuh know the lizard worshiping Bug and his lover adnj smoking some bad weed when they prefer to present guesstimates vs actual numbers then claim its official figures.
CDC estimates vs actual number
Maybe math is a subject you never took or passed but allow me to explain.
Imagine we took 10000 random trinis sprinkled across the country and gave them anti body tests. We then see than 10% of the 10000 so 1000 persons had Covid-19.
We can then use stats to estimate or guesstimate that we can be certain within a certain confidence interval that 10% of trinis had Covid. Compared to official testing which states that 0.6% of people had Covid-19.
Basically that's what CDC and other researchers have been doing, albeit probably using vastly better statistical methods than I just described.
The flaw in this would be how the antibody samples were taken, basically the same flaws that can affect the accuracy of polling.
However, it will be a close enough ballpark figure to make certain conclusions.
This would be because not everyone goes for a test who is sick, 80% of cases are mild to asymptomatic.
In the US mid year studies revealed they were only detecting 15% of cases.
In Trinidad, I believe we have even more mild asymptomatic cases due to higher vitamin D levels.
I think at best we're detecting 1 in 10 cases.
Maybe immunology/microbiology is not your strong point or life in general.
For most of this pandemic antibody tests kits have been terrible at giving actual data on diagnosis, there is a reason why we went to PCR only (and even they had a 30% false positive chance) .
So extrapolating a data point from a wrong data point does not make you wrong ... it makes you Stupid.
Serology kits are only now getting to the point where they are reliable.
Again I will say it guesstimating figures and calling them facts is what got us in this mess of panic and fear. Now you have Bug worshiping lizards saying we all gonna die.
Real science is saying that if you don't have the DATA then say you freaking don't know. Don't freaking claim the Infections are 13 million in Texas and the only way of confirming this accurately is with a test that only showed 2.8 million (which has a false positive rate of 30% mind you).
Lastly if you are admitting that we are detecting 10% of the cases then the death rate (which is already really low) plummets by 90% which means this is not a deadly virus and we have nothing to worry about.
If you don't know what a Monte Carlo analysis is, move on.
Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach
Steven J. Phipps, R. Quentin Grafton and Tom Kompas
Published:18 November 2020 https://doi.org/10.1098/rsos.200909
Abstract
Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.
But you are using the same test data with the assumption that it is incorrect. You then conclude that you have a valid outcome from an incomplete or invalid data set.drchaos wrote:adnj wrote:*sigh*drchaos wrote:Dohplaydat wrote:drchaos wrote:Yuh know the lizard worshiping Bug and his lover adnj smoking some bad weed when they prefer to present guesstimates vs actual numbers then claim its official figures.
CDC estimates vs actual number
Maybe math is a subject you never took or passed but allow me to explain.
Imagine we took 10000 random trinis sprinkled across the country and gave them anti body tests. We then see than 10% of the 10000 so 1000 persons had Covid-19.
We can then use stats to estimate or guesstimate that we can be certain within a certain confidence interval that 10% of trinis had Covid. Compared to official testing which states that 0.6% of people had Covid-19.
Basically that's what CDC and other researchers have been doing, albeit probably using vastly better statistical methods than I just described.
The flaw in this would be how the antibody samples were taken, basically the same flaws that can affect the accuracy of polling.
However, it will be a close enough ballpark figure to make certain conclusions.
This would be because not everyone goes for a test who is sick, 80% of cases are mild to asymptomatic.
In the US mid year studies revealed they were only detecting 15% of cases.
In Trinidad, I believe we have even more mild asymptomatic cases due to higher vitamin D levels.
I think at best we're detecting 1 in 10 cases.
Maybe immunology/microbiology is not your strong point or life in general.
For most of this pandemic antibody tests kits have been terrible at giving actual data on diagnosis, there is a reason why we went to PCR only (and even they had a 30% false positive chance) .
So extrapolating a data point from a wrong data point does not make you wrong ... it makes you Stupid.
Serology kits are only now getting to the point where they are reliable.
Again I will say it guesstimating figures and calling them facts is what got us in this mess of panic and fear. Now you have Bug worshiping lizards saying we all gonna die.
Real science is saying that if you don't have the DATA then say you freaking don't know. Don't freaking claim the Infections are 13 million in Texas and the only way of confirming this accurately is with a test that only showed 2.8 million (which has a false positive rate of 30% mind you).
Lastly if you are admitting that we are detecting 10% of the cases then the death rate (which is already really low) plummets by 90% which means this is not a deadly virus and we have nothing to worry about.
If you don't know what a Monte Carlo analysis is, move on.
Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach
Steven J. Phipps, R. Quentin Grafton and Tom Kompas
Published:18 November 2020 https://doi.org/10.1098/rsos.200909
Abstract
Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.
Didn't bother to read the limitations of the Monte Carlo model when you learned about it on Wikipedia this morning did you?
Like any computational data model your results is only as good as your input information.
So poor sampling data, along with covid 19 test accuracy from a false positive/false negative standpoint makes your results a weak guesstimate.
In any case if your data set was accurate and the cases number are higher by magnitudes then your death rate plummets.
Your data suggests that this virus has a 6 times higher case rate which drops your death rate by magnitudes. Which means this is not a Deadly virus .
So which is it? Way higher number of virus cases, which makes it no where near as deadly as you thought it was or do you think the use of inaccurate data to extrapolate a model using the Monte Carlo method is giving us data we cant use so you admit that you and your BUG was using false data to make false claims.
adnj wrote:But you are using the same test data with the assumption that it is incorrect. You then conclude that you have a valid outcome from an incomplete or invalid data set.drchaos wrote:adnj wrote:*sigh*drchaos wrote:Dohplaydat wrote:drchaos wrote:Yuh know the lizard worshiping Bug and his lover adnj smoking some bad weed when they prefer to present guesstimates vs actual numbers then claim its official figures.
CDC estimates vs actual number
Maybe math is a subject you never took or passed but allow me to explain.
Imagine we took 10000 random trinis sprinkled across the country and gave them anti body tests. We then see than 10% of the 10000 so 1000 persons had Covid-19.
We can then use stats to estimate or guesstimate that we can be certain within a certain confidence interval that 10% of trinis had Covid. Compared to official testing which states that 0.6% of people had Covid-19.
Basically that's what CDC and other researchers have been doing, albeit probably using vastly better statistical methods than I just described.
The flaw in this would be how the antibody samples were taken, basically the same flaws that can affect the accuracy of polling.
However, it will be a close enough ballpark figure to make certain conclusions.
This would be because not everyone goes for a test who is sick, 80% of cases are mild to asymptomatic.
In the US mid year studies revealed they were only detecting 15% of cases.
In Trinidad, I believe we have even more mild asymptomatic cases due to higher vitamin D levels.
I think at best we're detecting 1 in 10 cases.
Maybe immunology/microbiology is not your strong point or life in general.
For most of this pandemic antibody tests kits have been terrible at giving actual data on diagnosis, there is a reason why we went to PCR only (and even they had a 30% false positive chance) .
So extrapolating a data point from a wrong data point does not make you wrong ... it makes you Stupid.
Serology kits are only now getting to the point where they are reliable.
Again I will say it guesstimating figures and calling them facts is what got us in this mess of panic and fear. Now you have Bug worshiping lizards saying we all gonna die.
Real science is saying that if you don't have the DATA then say you freaking don't know. Don't freaking claim the Infections are 13 million in Texas and the only way of confirming this accurately is with a test that only showed 2.8 million (which has a false positive rate of 30% mind you).
Lastly if you are admitting that we are detecting 10% of the cases then the death rate (which is already really low) plummets by 90% which means this is not a deadly virus and we have nothing to worry about.
If you don't know what a Monte Carlo analysis is, move on.
Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach
Steven J. Phipps, R. Quentin Grafton and Tom Kompas
Published:18 November 2020 https://doi.org/10.1098/rsos.200909
Abstract
Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.
Didn't bother to read the limitations of the Monte Carlo model when you learned about it on Wikipedia this morning did you?
Like any computational data model your results is only as good as your input information.
So poor sampling data, along with covid 19 test accuracy from a false positive/false negative standpoint makes your results a weak guesstimate.
In any case if your data set was accurate and the cases number are higher by magnitudes then your death rate plummets.
Your data suggests that this virus has a 6 times higher case rate which drops your death rate by magnitudes. Which means this is not a Deadly virus .
So which is it? Way higher number of virus cases, which makes it no where near as deadly as you thought it was or do you think the use of inaccurate data to extrapolate a model using the Monte Carlo method is giving us data we cant use so you admit that you and your BUG was using false data to make false claims.
Either the data is right and you are wrong. Or the data is wrong and your conclusion is wrong.
Which do you prefer?
drchaos wrote:adnj wrote:But you are using the same test data with the assumption that it is incorrect. You then conclude that you have a valid outcome from an incomplete or invalid data set.drchaos wrote:adnj wrote:*sigh*drchaos wrote:Dohplaydat wrote:drchaos wrote:Yuh know the lizard worshiping Bug and his lover adnj smoking some bad weed when they prefer to present guesstimates vs actual numbers then claim its official figures.
CDC estimates vs actual number
Maybe math is a subject you never took or passed but allow me to explain.
Imagine we took 10000 random trinis sprinkled across the country and gave them anti body tests. We then see than 10% of the 10000 so 1000 persons had Covid-19.
We can then use stats to estimate or guesstimate that we can be certain within a certain confidence interval that 10% of trinis had Covid. Compared to official testing which states that 0.6% of people had Covid-19.
Basically that's what CDC and other researchers have been doing, albeit probably using vastly better statistical methods than I just described.
The flaw in this would be how the antibody samples were taken, basically the same flaws that can affect the accuracy of polling.
However, it will be a close enough ballpark figure to make certain conclusions.
This would be because not everyone goes for a test who is sick, 80% of cases are mild to asymptomatic.
In the US mid year studies revealed they were only detecting 15% of cases.
In Trinidad, I believe we have even more mild asymptomatic cases due to higher vitamin D levels.
I think at best we're detecting 1 in 10 cases.
Maybe immunology/microbiology is not your strong point or life in general.
For most of this pandemic antibody tests kits have been terrible at giving actual data on diagnosis, there is a reason why we went to PCR only (and even they had a 30% false positive chance) .
So extrapolating a data point from a wrong data point does not make you wrong ... it makes you Stupid.
Serology kits are only now getting to the point where they are reliable.
Again I will say it guesstimating figures and calling them facts is what got us in this mess of panic and fear. Now you have Bug worshiping lizards saying we all gonna die.
Real science is saying that if you don't have the DATA then say you freaking don't know. Don't freaking claim the Infections are 13 million in Texas and the only way of confirming this accurately is with a test that only showed 2.8 million (which has a false positive rate of 30% mind you).
Lastly if you are admitting that we are detecting 10% of the cases then the death rate (which is already really low) plummets by 90% which means this is not a deadly virus and we have nothing to worry about.
If you don't know what a Monte Carlo analysis is, move on.
Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach
Steven J. Phipps, R. Quentin Grafton and Tom Kompas
Published:18 November 2020 https://doi.org/10.1098/rsos.200909
Abstract
Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.
Didn't bother to read the limitations of the Monte Carlo model when you learned about it on Wikipedia this morning did you?
Like any computational data model your results is only as good as your input information.
So poor sampling data, along with covid 19 test accuracy from a false positive/false negative standpoint makes your results a weak guesstimate.
In any case if your data set was accurate and the cases number are higher by magnitudes then your death rate plummets.
Your data suggests that this virus has a 6 times higher case rate which drops your death rate by magnitudes. Which means this is not a Deadly virus .
So which is it? Way higher number of virus cases, which makes it no where near as deadly as you thought it was or do you think the use of inaccurate data to extrapolate a model using the Monte Carlo method is giving us data we cant use so you admit that you and your BUG was using false data to make false claims.
Either the data is right and you are wrong. Or the data is wrong and your conclusion is wrong.
Which do you prefer?
Your above statement is another false extrapolation. I never claimed I have a valid outcome, just that we only have actual cases numbers and fully vaccinated numbers to run with and therefore cannot declare with certainty that herd immunity has been achieved.
You and Bug made and continued a claim that an extrapolated data set is the actual number of cases, thus declaring that Texas has achieved herd immunity.
The falsifying of information keeps racking up with you two.
drchaos wrote:adnj wrote:But you are using the same test data with the assumption that it is incorrect. You then conclude that you have a valid outcome from an incomplete or invalid data set.drchaos wrote:adnj wrote:*sigh*drchaos wrote:Dohplaydat wrote:drchaos wrote:Yuh know the lizard worshiping Bug and his lover adnj smoking some bad weed when they prefer to present guesstimates vs actual numbers then claim its official figures.
CDC estimates vs actual number
Maybe math is a subject you never took or passed but allow me to explain.
Imagine we took 10000 random trinis sprinkled across the country and gave them anti body tests. We then see than 10% of the 10000 so 1000 persons had Covid-19.
We can then use stats to estimate or guesstimate that we can be certain within a certain confidence interval that 10% of trinis had Covid. Compared to official testing which states that 0.6% of people had Covid-19.
Basically that's what CDC and other researchers have been doing, albeit probably using vastly better statistical methods than I just described.
The flaw in this would be how the antibody samples were taken, basically the same flaws that can affect the accuracy of polling.
However, it will be a close enough ballpark figure to make certain conclusions.
This would be because not everyone goes for a test who is sick, 80% of cases are mild to asymptomatic.
In the US mid year studies revealed they were only detecting 15% of cases.
In Trinidad, I believe we have even more mild asymptomatic cases due to higher vitamin D levels.
I think at best we're detecting 1 in 10 cases.
Maybe immunology/microbiology is not your strong point or life in general.
For most of this pandemic antibody tests kits have been terrible at giving actual data on diagnosis, there is a reason why we went to PCR only (and even they had a 30% false positive chance) .
So extrapolating a data point from a wrong data point does not make you wrong ... it makes you Stupid.
Serology kits are only now getting to the point where they are reliable.
Again I will say it guesstimating figures and calling them facts is what got us in this mess of panic and fear. Now you have Bug worshiping lizards saying we all gonna die.
Real science is saying that if you don't have the DATA then say you freaking don't know. Don't freaking claim the Infections are 13 million in Texas and the only way of confirming this accurately is with a test that only showed 2.8 million (which has a false positive rate of 30% mind you).
Lastly if you are admitting that we are detecting 10% of the cases then the death rate (which is already really low) plummets by 90% which means this is not a deadly virus and we have nothing to worry about.
If you don't know what a Monte Carlo analysis is, move on.
Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach
Steven J. Phipps, R. Quentin Grafton and Tom Kompas
Published:18 November 2020 https://doi.org/10.1098/rsos.200909
Abstract
Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions. Monte Carlo methods were used to robustly sample parameter uncertainty. We found a strong and statistically significant negative relationship between the proportion of the population who test positive and the implied true detection rate. Despite an overall improvement in detection rates as the pandemic has progressed, our estimates showed that, as at 31 August 2020, the true number of people to have been infected across our sample of 15 countries was 6.2 (95% CI: 4.3–10.9) times greater than the reported number of cases. In individual countries, the true number of cases exceeded the reported figure by factors that range from 2.6 (95% CI: 1.8–4.5) for South Korea to 17.5 (95% CI: 12.2–30.7) for Italy.
Didn't bother to read the limitations of the Monte Carlo model when you learned about it on Wikipedia this morning did you?
Like any computational data model your results is only as good as your input information.
So poor sampling data, along with covid 19 test accuracy from a false positive/false negative standpoint makes your results a weak guesstimate.
In any case if your data set was accurate and the cases number are higher by magnitudes then your death rate plummets.
Your data suggests that this virus has a 6 times higher case rate which drops your death rate by magnitudes. Which means this is not a Deadly virus .
So which is it? Way higher number of virus cases, which makes it no where near as deadly as you thought it was or do you think the use of inaccurate data to extrapolate a model using the Monte Carlo method is giving us data we cant use so you admit that you and your BUG was using false data to make false claims.
Either the data is right and you are wrong. Or the data is wrong and your conclusion is wrong.
Which do you prefer?
Your above statement is another false extrapolation. I never claimed I have a valid outcome, just that we only have actual cases numbers and fully vaccinated numbers to run with and therefore cannot declare with certainty that herd immunity has been achieved.
You and Bug made and continued a claim that an extrapolated data set is the actual number of cases, thus declaring that Texas has achieved herd immunity.
The falsifying of information keeps racking up with you two.
Dohplaydat wrote:
wait restaurants open tonight? nice i organizing a lil small lime
redmanjp wrote:Dohplaydat wrote:
wait restaurants open tonight? nice i organizing a lil small lime
breaking quarantine?
Les Bain wrote:How come our legion of freethinkers eh expose covid for the sheeple generating scam it is yet?
drchaos wrote:Les Bain wrote:How come our legion of freethinkers eh expose covid for the sheeple generating scam it is yet?
How you talking like Yoda so?
Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
https://edition.cnn.com/2021/04/14/heal ... index.html
drchaos wrote:Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
https://edition.cnn.com/2021/04/14/heal ... index.html
Shhhhhh ... Bug and Adnj will claim its not true ... make up their own stats and claims. Then when its disproven, say they never said it.
Dum faen.drchaos wrote:Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
https://edition.cnn.com/2021/04/14/heal ... index.html
Shhhhhh ... Bug and Adnj will claim its not true ... make up their own stats and claims. Then when its disproven, say they never said it.
Dohplaydat wrote:drchaos wrote:Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
https://edition.cnn.com/2021/04/14/heal ... index.html
Shhhhhh ... Bug and Adnj will claim its not true ... make up their own stats and claims. Then when its disproven, say they never said it.
'
Bro people die all the time of natural causes. Given that we're vaccinating the most vulnerable first you'd reason that a lot would die after the vaccine.
And yes it could be in many cases the vaccine self causing it, but that was always a possibility given the harsh initial reaction.
Skanky wrote:Dohplaydat wrote:drchaos wrote:Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
https://edition.cnn.com/2021/04/14/heal ... index.html
Shhhhhh ... Bug and Adnj will claim its not true ... make up their own stats and claims. Then when its disproven, say they never said it.
'
Bro people die all the time of natural causes. Given that we're vaccinating the most vulnerable first you'd reason that a lot would die after the vaccine.
And yes it could be in many cases the vaccine self causing it, but that was always a possibility given the harsh initial reaction.
You taking the vaccine to prevent yourself from dying in the first place but it's okay to die from the vaccine???
Allyuh fellas logic way too advanced for me yes Daran.
Dohplaydat wrote:Skanky wrote:Dohplaydat wrote:drchaos wrote:Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
<a class="vglnk" href="https://edition.cnn.com/2021/04/14/health/breakthrough-infections-covid-vaccines-cdc/index.html[/quote" rel="nofollow"><span>https</span><span>://</span><span>edition</span><span>.</span><span>cnn</span><span>.</span><span>com</span><span>/</span><span>2021</span><span>/</span><span>04</span><span>/</span><span>14</span><span>/</span><span>health</span><span>/</span><span>breakthrough</span><span>-</span><span>infections</span><span>-</span><span>covid</span><span>-</span><span>vaccines</span><span>-</span><span>cdc</span><span>/</span><span>index</span><span>.</span><span>html</span><span>[/</span><span>quote</span></a>]
Shhhhhh ... Bug and Adnj will claim its not true ... make up their own stats and claims. Then when its disproven, say they never said it.
'
Bro people die all the time of natural causes. Given that we're vaccinating the most vulnerable first you'd reason that a lot would die after the vaccine.
And yes it could be in many cases the vaccine self causing it, but that was always a possibility given the harsh initial reaction.
You taking the vaccine to prevent yourself from dying in the first place but it's okay to die from the vaccine???
Allyuh fellas logic way too advanced for me yes Daran.
I'm saying simply some ppl are too old and sick for the vaccine and yes death is a risk for them. 99.999% of people have nothing to worry about.
Few Facts, Millions Of Clicks: Fearmongering Vaccine Stories Go Viral OnlineSkanky wrote:Dohplaydat wrote:Skanky wrote:Dohplaydat wrote:drchaos wrote:Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
<a class="vglnk" href="https://edition.cnn.com/2021/04/14/health/breakthrough-infections-covid-vaccines-cdc/index.html[/quote" rel="nofollow"><span>https</span><span>://</span><span>edition</span><span>.</span><span>cnn</span><span>.</span><span>com</span><span>/</span><span>2021</span><span>/</span><span>04</span><span>/</span><span>14</span><span>/</span><span>health</span><span>/</span><span>breakthrough</span><span>-</span><span>infections</span><span>-</span><span>covid</span><span>-</span><span>vaccines</span><span>-</span><span>cdc</span><span>/</span><span>index</span><span>.</span><span>html</span><span>[/</span><span>quote</span></a>]
Shhhhhh ... Bug and Adnj will claim its not true ... make up their own stats and claims. Then when its disproven, say they never said it.
'
Bro people die all the time of natural causes. Given that we're vaccinating the most vulnerable first you'd reason that a lot would die after the vaccine.
And yes it could be in many cases the vaccine self causing it, but that was always a possibility given the harsh initial reaction.
You taking the vaccine to prevent yourself from dying in the first place but it's okay to die from the vaccine???
Allyuh fellas logic way too advanced for me yes Daran.
I'm saying simply some ppl are too old and sick for the vaccine and yes death is a risk for them. 99.999% of people have nothing to worry about.
Please Dr Daran let us know where you got this information that 99.999% of people have nothing to worry about.
adnj wrote:Few Facts, Millions Of Clicks: Fearmongering Vaccine Stories Go Viral OnlineSkanky wrote:Dohplaydat wrote:Skanky wrote:Dohplaydat wrote:drchaos wrote:Skanky wrote:Saw some figures from CNN where 74 people died after getting the vaccine(out of approximately 5800) and many of those,396, had to be hospitalized as they became seriously ill.
So people getting the vaccine and dying but most people getting the actual virus and living.... and lots asymptomatic to boot.
<a class="vglnk" href="https://edition.cnn.com/2021/04/14/health/breakthrough-infections-covid-vaccines-cdc/index.html[/quote" rel="nofollow"><span>https</span><span>://</span><span>edition</span><span>.</span><span>cnn</span><span>.</span><span>com</span><span>/</span><span>2021</span><span>/</span><span>04</span><span>/</span><span>14</span><span>/</span><span>health</span><span>/</span><span>breakthrough</span><span>-</span><span>infections</span><span>-</span><span>covid</span><span>-</span><span>vaccines</span><span>-</span><span>cdc</span><span>/</span><span>index</span><span>.</span><span>html</span><span>[/</span><span>quote</span></a>]
Shhhhhh ... Bug and Adnj will claim its not true ... make up their own stats and claims. Then when its disproven, say they never said it.
'
Bro people die all the time of natural causes. Given that we're vaccinating the most vulnerable first you'd reason that a lot would die after the vaccine.
And yes it could be in many cases the vaccine self causing it, but that was always a possibility given the harsh initial reaction.
You taking the vaccine to prevent yourself from dying in the first place but it's okay to die from the vaccine???
Allyuh fellas logic way too advanced for me yes Daran.
I'm saying simply some ppl are too old and sick for the vaccine and yes death is a risk for them. 99.999% of people have nothing to worry about.
Please Dr Daran let us know where you got this information that 99.999% of people have nothing to worry about.
March 25, 202 15:00 AM ET
The odds of dying after getting a COVID-19 vaccine are virtually nonexistent.
According to recent data from the Centers For Disease Control and Prevention, you're three times more likely to get struck by lightning.
But you might not know that from looking at your social media feed.
A new NPR analysis finds that articles connecting vaccines and death have been among the most highly engaged with content online this year, going viral in a way that could hinder people's ability to judge the true risk in getting a shot.
The findings also illustrate a broader trend in online misinformation: With social media platforms making more of an effort to take down patently false health claims, bad actors are turning to cherry-picked truths to drive misleading narratives.
https://www.npr.org/2021/03/25/98003570 ... nformation
Lightning is one of the leading causes of weather-related fatalities. But the odds of being struck by lightning in a given year are only around 1 in 500,000. However, some factors can put you at greater risk for being struck.
https://www.cdc.gov/disasters/lightning ... g%20struck.
drchaos wrote:The truth is some of us will have to be sacrificed for the "greater good".
The system doesn't care about individuals, it works on the basis of the masses. If more of you survive from covid with some dying from the vaccine then its fine from a leadership point of view.
Only you are responsible for your individual health. The Lizard overlords are responsible for the masses.
redmanjp wrote:drchaos wrote:The truth is some of us will have to be sacrificed for the "greater good".
The system doesn't care about individuals, it works on the basis of the masses. If more of you survive from covid with some dying from the vaccine then its fine from a leadership point of view.
Only you are responsible for your individual health. The Lizard overlords are responsible for the masses.
nobody forcing u to take it
redmanjp wrote:drchaos wrote:The truth is some of us will have to be sacrificed for the "greater good".
The system doesn't care about individuals, it works on the basis of the masses. If more of you survive from covid with some dying from the vaccine then its fine from a leadership point of view.
Only you are responsible for your individual health. The Lizard overlords are responsible for the masses.
nobody forcing u to take it
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