4 ms·

That first part is a mistaken belief. There's also a useful metric for the "chance of dying" - it's known as a micromort. Each micromort is a one in a million

by shagie 4y ago

That first part is a mistaken belief. There's also a useful metric for the "chance of dying" - it's known as a micromort. Each micromort is a one in a million chance of dying https://en.wikipedia.org/wiki/Micromort https://en.wikipedia.org/wiki/Micromort A fair bit of statistical work has been done on COVID-19 and it is summarized in the wikipedia article. AstraZeneca vaccination against COVID-19 – 2.9 micromorts[31] COVID-19 infection at age 10 – 20 micromorts COVID-19 infection at age 25 – 100 micromorts COVID-19 infection at age 55 – 4,000 micromorts COVID-19 infection at age 65 – 14,000 micromorts COVID-19 infection at age 75 – 46,000 micromorts COVID-19 infection at age 85 – 150,000 micromorts [32] Yes, many people survived - but those are not numbers I want to be betting against on a daily basis. NYT - Putting the Risk of Covid-19 in Perspective Is the risk of dying from Covid-19 comparable to driving to work every day, skydiving or being a soldier in a war? https://www.nytimes.com/2020/05/22/well/live/putting-the-risk-of-covid-19-in-perspective.html?unlocked_article_code=5wGL3Ldunqs5doe7IbbEOj9hC5J9_B2J3G9KZ2CYMSWYpUmjdbxSlalTtn3904J7-gNqmSBWBhyvq6YJqONJ2jjn7-7Vqq7rZUkKbOO1cWFoIkA83LitdH9RpNQ44G5ljZkC5IyHqchq8cvpu3ktP501UeIaodaPqFgGHjTs4R_CBxqIhs6IsmgzfPuV15HMahC1taaApiIg5riiNOhvhOwpzE704EjAQfImLBKEZAs5O3bQij7O--RVS2qXP0vFAEq9BiS54Gx9B9ZnaY-AFlrhyQmyLFDa6tinNrefMrSmk2XNbv7fDRRtY9iQ5PIVDGhSty-oO1Pt5Y6fsW9UOHlZ4Ig7JuTsab0w4GCcmz3hVd4W0tuH&smid=share-url https://www.nytimes.com/2020/05/22/well/live/putting-the-ris... > Converting this to micromort language, an individual living in New York City has experienced roughly 50 additional micromorts of risk per day because of Covid-19. That means you were roughly twice as likely to die as you would have been if you were serving in the U.S. armed forces in Afghanistan throughout 2010, a particularly deadly year. Rare is not zero - but if you are risk adverse, then avoiding things that are fairly high up on the risk counter would be reasonable. Likewise, if there are two options (driving in a car vs driving in a motor cycle), taking the one that adds the least amount of additional risk is reasonable.

vikingerik 4y ago
These numbers are useless going forward if they are based on the original Covid-19 strains and not the Omicron strains, which now account for virtually every case and are tens of times less lethal.
- gdavisson 4y ago
  That's not true. Death rates are now much lower, but that seems to be mostly due to people having (partial) immunity due to vaccination and/or previous infection, and better treatment. Omicron variants are less intrinsically severe than delta, but delta was more intrinsically severe than the earlier variants, so it's not clear omicron's actually any lower than the original strain, alpha, etc. For example, according to "Challenges in Inferring Intrinsic Severity of the SARS-CoV-2 Omicron Variant" (https://www.nejm.org/doi/full/10.1056/NEJMp2119682?query=featured_home https://www.nejm.org/doi/full/10.1056/NEJMp2119682?query=fea...): "This meaningful but fairly small difference [vs Delta] implies that omicron, alpha, and wild-type SARS-CoV-2 have similar intrinsic severity."
  - incrudible 4y ago
    The argument does not hold water. As Omikron replaced Delta, case mortality reduced immediately, despite skyrocketing cases. Population immunity does not explain this. The figure of 75% is only arrived at by correcting for underascertainment, which is an arbitrary estimate.
nradov 4y ago
How do those numbers change when you adjust for presence or absence of pre-existing conditions such as obesity and type-2 diabetes?
- ajross 4y ago
  Please don't. What you are doing is called "P-hacking". Yes, if you keep selecting for subsets of a dataset you'll eventually find one that, just due to random chance, looks like a statistically significant result that proves whatever it is you want to see. That's not the way you do science. As always, xkcd explains it best: https://www.explainxkcd.com/wiki/index.php/882:_Significant https://www.explainxkcd.com/wiki/index.php/882:_Significant
  - nradov 4y ago
    No that's not P-hacking. The majority of US residents have been infected at this point. The sizes of those population groups both with and without serious pre-existing conditions are so huge that there is minimal chance of an incorrect random result. Your link is not relevant to this issue so I don't know what point you're trying to make. To be clear I support vaccination. But patients should make their own decisions free of coercion based on informed consent with full knowledge of the risks on both sides. Don't presume to patronize them with spurious, bad faith comments about "P-hacking". Let's see the actual data.
    - ajross 4y ago
      Right, you have a hypothesis. But you don't have data. Trying to tease out evidence for your hypothesis from existing data by slicing the data set up is the very definition of p-hacking. If you refuse to believe existing work on the basis of an unmeasured hypothesis, well, that's a different sort of logical fallacy on top of the bad statistics. And FWIW, if you want a more complete (but much less amusing) explainer on the subject, wikipedia always comes through: https://en.wikipedia.org/wiki/Data_dredging https://en.wikipedia.org/wiki/Data_dredging
      - 4y ago
VancouverMan 4y ago
We have to be extremely cautious when considering any of the death-related statistics for this particular situation. For example, we know that a dubious methodology was used for counting deaths in Toronto (Canada's most populous city, and the fourth most populous city in North America). This was publicly admitted to by Toronto Public Health itself, as early as June 2020: "Individuals who have died with COVID-19, but not as a result of COVID-19 are included in the case counts for COVID-19 deaths in Toronto." https://twitter.com/TOPublicHealth/status/1275888390060285967 https://twitter.com/TOPublicHealth/status/127588839006028596... I can't see how that significant city's death stats could be considered reliable or usable for analytic purposes, after considering how the counting was done. The provincial and national stats would also be affected to some extent. This makes me quite doubtful about the stats coming out of other regions, too.
- shagie 4y ago
  The paper those numbers are based on is Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721859/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721859/ The meta-analysis is looking at that question that you are asking. It also has all the papers that it cites for analysis and an analysis of its own limitations. > The systematic review encompassed 113 studies, of which 27 studies (covering 34 geographical locations) satisfied the inclusion criteria and were included in the meta-analysis.
- cthulha 4y ago
  The question nobody else has been able to answer is "What is a satisfactory analysis for these purposes?" The closest I've seen to an answer is to remove accidental deaths (eg, hit by a car, firearms fatality, etc) but there's a huge range of arguable cases like stroke which is plausibly covid-affected. Second, you have the problem of comparing stats between locations that used different definitions, so it's harder to do post-hoc correlations. The decisions seems to have been avoiding false-negative mistakes by increasing false positives in the first wave of analysis: "Let's include everything under a simple rule for covid stats so that we at least have some kind of worst-case baseline modelling with similar datasets, and we can figure out afterwards which are real and which aren't" Anyway, just wanted to see if you actually have a better answer to the problem than the standard that was used.
Mawr 4y ago
> "Converting this to micromort language, an individual living in New York City has experienced roughly 50 additional micromorts of risk per day because of Covid-19. That means you were roughly twice as likely to die as you would have been if you were serving in the U.S. armed forces in Afghanistan throughout 2010, a particularly deadly year." This is highly misleading. The average individual may be at such risk, just like humans have ~1.9 legs on average, but that doesn't mean that everyone walks around with their 1.9 legs. So those statistics are based on the risk to the general population and therefore have approximately zero relevance to any single person. Almost by definition, the disease will claim those most vulnerable first, so questioning whether vaccination is worth it for those less vulnerable is valid. What're the risks of vaccination vs covid for a healthy 25 year old who works from home?
- s1artibartfast 4y ago
  This exactly. You would want to see the micromort breakdown for the same populations as covid infection. You might also want to dive deeper and see if there's more specific populations and how they compare.
- shagie 4y ago
  The 50 micromorts per day is from the excess deaths in NYC during spring of 2020 and comparing that mortality to being a soldier in Afghanistan in 2010. I don't believe that comparing those two is unreasonable. However, to your last question that is what micomorts can answer. The risk of death from a vaccination is 2.9 micromorts. The risk of death from contracting Covid-19 for a 25 year old is 100 micromorts. So 30x greater risk.. and those are directly comparable numbers. The other point to consider - you're not always going to be 25. I'm much closer to the 55 bracket than the 25 bracket, and that represents a 40x increase in risk... so about 1200x greater risk than vaccination. Assuming you remain a hermit for some number of years (and Covid-19 remains endemic), is there a point where you would change your mind on the value proposition of a vaccination? And if the answer is yes - why not do it now? Yea, currently you're comparing 2.9 micromorts vs 100 micromorts. At 25, that comparison doesn't have too much to it. 100 micromorts is not something that I think too much about either (comparable to the risk of death while giving birth for the women out there). I've done road trips that racked up 100 micromorts cumulative (more if you add in the hiking and skiing micromorts on that trip). I'll also note I'm older now than when I was when I did that roadtrip... and there are things that I would do now to further mitigate the risks that I took back then. It's not wrong for your age, but it is something that should be said "yes, its a risk and it is a lot riskier." That said, there's a number even beyond that 100 micromorts to consider. New data shows long Covid is keeping as many as 4 million people out of work - https://www.brookings.edu/research/new-data-shows-long-covid-is-keeping-as-many-as-4-million-people-out-of-work/ https://www.brookings.edu/research/new-data-shows-long-covid... > 1.6 million full-time equivalent workers could be out of work due to long Covid. With 10.6 million unfilled jobs at the time, long Covid potentially accounted for 15% of the labor shortage. That 4M number is not part that I want to be part of. While I have better than average health insurance, the not-dying also has a significant risk to it too. It is harder to quantify as it isn't an accurate cause of mortality - but it is not something that should be ignored. Many people here enjoy better than average salaries - consider the risk of going on long term disability for the next 40 to 60 years with the corresponding reduction in compensation. And yes, I know people who are no longer able to work on anything that has a deadline or expectations of attendance in meetings; their lifestyle has changed significantly from three years ago.
jtc331 4y ago
You didn’t stratify vaccination risk by age which immediately calls into question your comparative data. Indeed the myocarditis risk appears to be inversely correlated with age (exactly the opposite of the positive correlation of risk COVID itself has with age).

by shagie 4y ago

vikingerik 4y ago

These numbers are useless going forward if they are based on the original Covid-19 strains and not the Omicron strains, which now account for virtually every case and are tens of times less lethal.

gdavisson 4y ago
That's not true. Death rates are now much lower, but that seems to be mostly due to people having (partial) immunity due to vaccination and/or previous infection, and better treatment. Omicron variants are less intrinsically severe than delta, but delta was more intrinsically severe than the earlier variants, so it's not clear omicron's actually any lower than the original strain, alpha, etc. For example, according to "Challenges in Inferring Intrinsic Severity of the SARS-CoV-2 Omicron Variant" (https://www.nejm.org/doi/full/10.1056/NEJMp2119682?query=featured_home https://www.nejm.org/doi/full/10.1056/NEJMp2119682?query=fea...): "This meaningful but fairly small difference [vs Delta] implies that omicron, alpha, and wild-type SARS-CoV-2 have similar intrinsic severity."
- incrudible 4y ago
  The argument does not hold water. As Omikron replaced Delta, case mortality reduced immediately, despite skyrocketing cases. Population immunity does not explain this. The figure of 75% is only arrived at by correcting for underascertainment, which is an arbitrary estimate.

nradov 4y ago

How do those numbers change when you adjust for presence or absence of pre-existing conditions such as obesity and type-2 diabetes?

ajross 4y ago
Please don't. What you are doing is called "P-hacking". Yes, if you keep selecting for subsets of a dataset you'll eventually find one that, just due to random chance, looks like a statistically significant result that proves whatever it is you want to see. That's not the way you do science. As always, xkcd explains it best: https://www.explainxkcd.com/wiki/index.php/882:_Significant https://www.explainxkcd.com/wiki/index.php/882:_Significant
- nradov 4y ago
  No that's not P-hacking. The majority of US residents have been infected at this point. The sizes of those population groups both with and without serious pre-existing conditions are so huge that there is minimal chance of an incorrect random result. Your link is not relevant to this issue so I don't know what point you're trying to make. To be clear I support vaccination. But patients should make their own decisions free of coercion based on informed consent with full knowledge of the risks on both sides. Don't presume to patronize them with spurious, bad faith comments about "P-hacking". Let's see the actual data.
  - ajross 4y ago
    Right, you have a hypothesis. But you don't have data. Trying to tease out evidence for your hypothesis from existing data by slicing the data set up is the very definition of p-hacking. If you refuse to believe existing work on the basis of an unmeasured hypothesis, well, that's a different sort of logical fallacy on top of the bad statistics. And FWIW, if you want a more complete (but much less amusing) explainer on the subject, wikipedia always comes through: https://en.wikipedia.org/wiki/Data_dredging https://en.wikipedia.org/wiki/Data_dredging
    - 4y ago

VancouverMan 4y ago

We have to be extremely cautious when considering any of the death-related statistics for this particular situation. For example, we know that a dubious methodology was used for counting deaths in Toronto (Canada's most populous city, and the fourth most populous city in North America). This was publicly admitted to by Toronto Public Health itself, as early as June 2020: "Individuals who have died with COVID-19, but not as a result of COVID-19 are included in the case counts for COVID-19 deaths in Toronto." https://twitter.com/TOPublicHealth/status/1275888390060285967 https://twitter.com/TOPublicHealth/status/127588839006028596... I can't see how that significant city's death stats could be considered reliable or usable for analytic purposes, after considering how the counting was done. The provincial and national stats would also be affected to some extent. This makes me quite doubtful about the stats coming out of other regions, too.

shagie 4y ago
The paper those numbers are based on is Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721859/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721859/ The meta-analysis is looking at that question that you are asking. It also has all the papers that it cites for analysis and an analysis of its own limitations. > The systematic review encompassed 113 studies, of which 27 studies (covering 34 geographical locations) satisfied the inclusion criteria and were included in the meta-analysis.
cthulha 4y ago
The question nobody else has been able to answer is "What is a satisfactory analysis for these purposes?" The closest I've seen to an answer is to remove accidental deaths (eg, hit by a car, firearms fatality, etc) but there's a huge range of arguable cases like stroke which is plausibly covid-affected. Second, you have the problem of comparing stats between locations that used different definitions, so it's harder to do post-hoc correlations. The decisions seems to have been avoiding false-negative mistakes by increasing false positives in the first wave of analysis: "Let's include everything under a simple rule for covid stats so that we at least have some kind of worst-case baseline modelling with similar datasets, and we can figure out afterwards which are real and which aren't" Anyway, just wanted to see if you actually have a better answer to the problem than the standard that was used.

Mawr 4y ago

> "Converting this to micromort language, an individual living in New York City has experienced roughly 50 additional micromorts of risk per day because of Covid-19. That means you were roughly twice as likely to die as you would have been if you were serving in the U.S. armed forces in Afghanistan throughout 2010, a particularly deadly year." This is highly misleading. The average individual may be at such risk, just like humans have ~1.9 legs on average, but that doesn't mean that everyone walks around with their 1.9 legs. So those statistics are based on the risk to the general population and therefore have approximately zero relevance to any single person. Almost by definition, the disease will claim those most vulnerable first, so questioning whether vaccination is worth it for those less vulnerable is valid. What're the risks of vaccination vs covid for a healthy 25 year old who works from home?

s1artibartfast 4y ago
This exactly. You would want to see the micromort breakdown for the same populations as covid infection. You might also want to dive deeper and see if there's more specific populations and how they compare.
shagie 4y ago
The 50 micromorts per day is from the excess deaths in NYC during spring of 2020 and comparing that mortality to being a soldier in Afghanistan in 2010. I don't believe that comparing those two is unreasonable. However, to your last question that is what micomorts can answer. The risk of death from a vaccination is 2.9 micromorts. The risk of death from contracting Covid-19 for a 25 year old is 100 micromorts. So 30x greater risk.. and those are directly comparable numbers. The other point to consider - you're not always going to be 25. I'm much closer to the 55 bracket than the 25 bracket, and that represents a 40x increase in risk... so about 1200x greater risk than vaccination. Assuming you remain a hermit for some number of years (and Covid-19 remains endemic), is there a point where you would change your mind on the value proposition of a vaccination? And if the answer is yes - why not do it now? Yea, currently you're comparing 2.9 micromorts vs 100 micromorts. At 25, that comparison doesn't have too much to it. 100 micromorts is not something that I think too much about either (comparable to the risk of death while giving birth for the women out there). I've done road trips that racked up 100 micromorts cumulative (more if you add in the hiking and skiing micromorts on that trip). I'll also note I'm older now than when I was when I did that roadtrip... and there are things that I would do now to further mitigate the risks that I took back then. It's not wrong for your age, but it is something that should be said "yes, its a risk and it is a lot riskier." That said, there's a number even beyond that 100 micromorts to consider. New data shows long Covid is keeping as many as 4 million people out of work - https://www.brookings.edu/research/new-data-shows-long-covid-is-keeping-as-many-as-4-million-people-out-of-work/ https://www.brookings.edu/research/new-data-shows-long-covid... > 1.6 million full-time equivalent workers could be out of work due to long Covid. With 10.6 million unfilled jobs at the time, long Covid potentially accounted for 15% of the labor shortage. That 4M number is not part that I want to be part of. While I have better than average health insurance, the not-dying also has a significant risk to it too. It is harder to quantify as it isn't an accurate cause of mortality - but it is not something that should be ignored. Many people here enjoy better than average salaries - consider the risk of going on long term disability for the next 40 to 60 years with the corresponding reduction in compensation. And yes, I know people who are no longer able to work on anything that has a deadline or expectations of attendance in meetings; their lifestyle has changed significantly from three years ago.

jtc331 4y ago

You didn’t stratify vaccination risk by age which immediately calls into question your comparative data. Indeed the myocarditis risk appears to be inversely correlated with age (exactly the opposite of the positive correlation of risk COVID itself has with age).