Coronavirus prep

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  • T1DCarnivoreRunner
    T1DCarnivoreRunner Posts: 11,462 Member
    kimny72 wrote: »
    kimny72 wrote: »
    kimny72 wrote: »
    They also discussed this report on the Barnstable outbreak:

    www.cdc.gov/mmwr/volumes/70/wr/mm7031e2.htm

    They said there is a lot of info that simply wasn't collected that limits the conclusions you can draw. But what jumped out to them was that only 1% of known vaxxed attendees required hospitalization with 0 deaths. Also that the attendees interviewed described attending densely packed indoor/outdoor events including bars and house parties with minimal if any mitigations. Basically a recipe for breakthroughs.

    There was no clinical tracing done to try to determine who got who sick, so it doesn't really add to the conversation about how much vaxxed people are transmitting.

    This part goes over my head, but maybe it will mean something to someone. The paper notes that the CT values detected by the covid tests were similar between vaxxed and unvaxxed attendees who tested positive. Dr Griffin noted that the CT value is detecting the amount of COVID-19 Rna in the nose, not "necessarily" viral particles. He said public health officials seem to be assuming that similar amounts of RNA mean similar amounts of virus, but it is entirely possible that vaccine-induced antibodies have neutralized many of the viral particles, so the RNA being picked up by the test is in neutralized virus that isn't transmissible. My layman's understanding is he's questioning the assertion that vaxxed folks are "just as contagious" as unvaxxed.

    Interesting. Some may recall that I had pointed out that the area has a 69% vaccinated adult population and that 74% of the people who were infected had been vaccinated. Statistically, that means a vaccine increases your risk of infection. I questioned the data, but acknowledged it could be a statistical outlier. Many Disagreed with my comments on that, but now a specific concern with data collection has been identified.

    As to the gatherings in bars and homes: I'm not sure what everyone expects to happen during bear week; I am not surprised.

    Again, the 69% is for the entire state, not for the attendees of these events in this one town. The 69% and 74% have nothing to do with each other and comparing them statistically means absolutely nothing. It never meant vaccination increases your risk tif infection, regardless of how data was collected.

    I believe the focus on where they were gathering was to stress that this one situation shouldn't be extrapolated to most people's situation. These vaccinated people put themselves into a high risk, concentrated environment for an extended period of time. So it's no reason for some of the panicked reactions many are having if they are still being mindful of spacing and ventilation in places they can't be sure everyone is vaccinated and healthy.

    We will never have vaccinated rates for the exact population directly exposed. Using the state vaccination rate is reliable enough for the CDC to use in its MMWR.

    But you're using the whole state's percentage and assuming it's the rate for this one town's event and drawing a very specific conclusion. That's not how percentages or statistics work. Which is probably why no public health officials or researchers (including the CDC report) came to the conclusion you did. They found it concerning that vaxxed people were testing positive and changed their mask recommendations, but in no way did they suggest vaxxed people were more likely to get infected. Vaxx rates vary dramatically by county and by demographic within states.

    51% of the Virginia population is women, but 65% of the people in my local rural Food Lion this week were men, so statistically that means that men are more likely to go grocery shopping?

    This is fair, and we don't know anything beyond the state data. Having said that, if the vaccinated rate was 74% (pretty high, but possible), then the conclusion is that the vaccine doesn't prevent infections at all. If the vaccination rate was the highest possible at 99% (it can't be 100% because there are some who were infected and not vaccinated), then the vaccine is 23% effective at preventing infection. That's the highest it could possibly be when assuming best case for the unknown details. Why focus on this case?!


    I can't find the first post for this subthread. Do we have a number for the total population at this event? I think we need that to calculate denominators when figuring out relative infection rates among the vaccinated and unvaccinated populations, even if we're willing to make assumptions about the vax rate in that particular crowd. Also, 99% is not the highest; it could be 99.5% or 99.99% etc., which will make a significant difference in calculating the infection rates among vaxed and unvaxed if the crowd was sufficiently large. (At this point, I'm not even sure I remember where this event was. Somewhere in New England, right?)

    Sure, was sticking with whole numbers. We don't have a count for the whole event, nor would it change the conclusions discussed thus far. A vaccine that is only 25.99% effective still makes this case a statistical outlier (no way was the crowd big enough for even 99% even if all of the unvaccinated got infected, but I'll bite on your decimals).

    It was Provincetown, MA.

    I don't understand where you're getting the 25.99% figure from. If we don't know total numbers, we don't have a denominator to calculate effective rate.

    I'm willing to assume equal exposure across the total population at this event (although as @kimny72 points out, that's not something we can know).

    I think comparing total populations of a country or state or county with known vaccination rates, and known hospitalization and death rates with vaccination status of those cases known is a more reasonable way of going about trying to determine real-world, ongoing vaccine effectiveness against variants and with potentially decreasing protection as time-from-vaccination increases, than looking at presumed superspreader events with self-selected populations for whom vaccination status and attitudes toward vaxing and masking are likely to be factors in self-selection and in risk-avoidance during actual attendance. I can imagine a wide range of behaviors once I get to some kind of fair or festival style event that would greatly influence my risk of behavior.

    It's not a controlled experiment, and we can't know enough about the prevalence of characteristics and behavioral factors to draw good conclusions.


    Clearly I'm not explaining very well, so will try again. Here is what we know from the MMWR: 469 cases total, 346 (74%) cases in fully vaccinated persons. In state of Massachusetts, eligible residents were 69% vaccinated (it is the best we have available, so let's make some other assumptions also...).

    There are 2 things we are discussing as far as assumptions - vaccination rate of people in Provincetown at the time and the number of people in Provincetown at the time.

    Looking at differences in number of people (denominator you keep referencing):
    Assume 69% vaccination rate and 10,000 people:
    6,900 vaccinated and 3,100 unvaccinated.
    346 vaccinated got infected: 346/6,900 = 5.014% of vaccinated people got infected
    123 unvaccinated got infected: 123/3,100 = 3.968% of unvaccinated people got infected
    5.014% - 3.968% = 1.047% difference / 3.968% baseline = 26.3815% greater risk of infection if vaccinated

    Assume 69% vaccination rate and 100,000 people:
    69,000 vaccinated and 31,000 unvaccinated.
    346 vaccinated got infected: 346/69,000 = 0.5014% of vaccinated people got infected
    123 unvaccinated got infected: 123/31,000 = 0.3968% of unvaccinated people got infected
    .5014% - .3968% = 0.1047% difference / 0.3968% baseline = 26.3815% greater risk of infection if vaccinated.
    *I'm using Excel for calculations in order to keep decimals. If you round interim calculations, the results will come out different.

    Do you see how the number of people doesn't make a difference?

    Let's now consider differences in the percentage vaccinated:
    Assume 99% vaccination rate and 100,000 people:
    99,000 vaccinated and 1,000 unvaccinated.
    346 vaccinated got infected: 346/99,000 = 0.349% of vaccinated people got infected
    123 unvaccinated got infected: 123/1,000 = 12.300% of vaccinated people got infected
    12.300% - 0.349% = 11.951% difference / 0.349% baseline = 97.159% lower risk of infection if vaccinated. Only when we get to these extremes do we get close to the decreased risk that we are supposed to have when vaccinated.

    Assume 99% vaccination rate and 10,000 people:
    *Cannot assume this because 123 of those infected were unvaccinated. Even if every unvaccinated person there became sick, that is only 100 people. We know that at least 123 people there were not vaccinated, more than 100% of those possible under this assumption.

    Assume 85% vaccination rate and 100,000 people:
    85,000 vaccinated and 15,000 unvaccinated.
    346 vaccinated got infected: 346/85,000 = 0.407% of vaccinated people got infected
    123 unvaccinated got infected: 123/15,000 = 0.820% of vaccinated people got infected
    0.820% - 0.407% = 0.413% difference / 0.407% baseline = 50.359% lower risk of infection if vaccinated.

    Assume 74% vaccination rate (i.e. assume the population and the infected group are both at 74% vaccinated) and 100,000 people:
    74,000 vaccinated and 26,000 unvaccinated.
    346 vaccinated got infected: 346/74,000 = 0.468% of vaccinated people got infected
    123 unvaccinated got infected: 123/26,000 = 0.473% of vaccinated people got infected
    0.473% - 0.468% = 0.006% difference / 0.468% baseline = 1.165% lower risk of infection if vaccinated.

    In the end, the "denominator" / how many people were there is irrelevant in determining how much the vaccine decreases risk. The only fact that would make a difference is what percentage of the people in that location at that time were vaccinated. The very best information we have is 69% for the state.


  • lynn_glenmont
    lynn_glenmont Posts: 9,425 Member
    edited August 2021
    kimny72 wrote: »
    kimny72 wrote: »
    kimny72 wrote: »
    They also discussed this report on the Barnstable outbreak:

    www.cdc.gov/mmwr/volumes/70/wr/mm7031e2.htm

    They said there is a lot of info that simply wasn't collected that limits the conclusions you can draw. But what jumped out to them was that only 1% of known vaxxed attendees required hospitalization with 0 deaths. Also that the attendees interviewed described attending densely packed indoor/outdoor events including bars and house parties with minimal if any mitigations. Basically a recipe for breakthroughs.

    There was no clinical tracing done to try to determine who got who sick, so it doesn't really add to the conversation about how much vaxxed people are transmitting.

    This part goes over my head, but maybe it will mean something to someone. The paper notes that the CT values detected by the covid tests were similar between vaxxed and unvaxxed attendees who tested positive. Dr Griffin noted that the CT value is detecting the amount of COVID-19 Rna in the nose, not "necessarily" viral particles. He said public health officials seem to be assuming that similar amounts of RNA mean similar amounts of virus, but it is entirely possible that vaccine-induced antibodies have neutralized many of the viral particles, so the RNA being picked up by the test is in neutralized virus that isn't transmissible. My layman's understanding is he's questioning the assertion that vaxxed folks are "just as contagious" as unvaxxed.

    Interesting. Some may recall that I had pointed out that the area has a 69% vaccinated adult population and that 74% of the people who were infected had been vaccinated. Statistically, that means a vaccine increases your risk of infection. I questioned the data, but acknowledged it could be a statistical outlier. Many Disagreed with my comments on that, but now a specific concern with data collection has been identified.

    As to the gatherings in bars and homes: I'm not sure what everyone expects to happen during bear week; I am not surprised.

    Again, the 69% is for the entire state, not for the attendees of these events in this one town. The 69% and 74% have nothing to do with each other and comparing them statistically means absolutely nothing. It never meant vaccination increases your risk tif infection, regardless of how data was collected.

    I believe the focus on where they were gathering was to stress that this one situation shouldn't be extrapolated to most people's situation. These vaccinated people put themselves into a high risk, concentrated environment for an extended period of time. So it's no reason for some of the panicked reactions many are having if they are still being mindful of spacing and ventilation in places they can't be sure everyone is vaccinated and healthy.

    We will never have vaccinated rates for the exact population directly exposed. Using the state vaccination rate is reliable enough for the CDC to use in its MMWR.

    But you're using the whole state's percentage and assuming it's the rate for this one town's event and drawing a very specific conclusion. That's not how percentages or statistics work. Which is probably why no public health officials or researchers (including the CDC report) came to the conclusion you did. They found it concerning that vaxxed people were testing positive and changed their mask recommendations, but in no way did they suggest vaxxed people were more likely to get infected. Vaxx rates vary dramatically by county and by demographic within states.

    51% of the Virginia population is women, but 65% of the people in my local rural Food Lion this week were men, so statistically that means that men are more likely to go grocery shopping?

    This is fair, and we don't know anything beyond the state data. Having said that, if the vaccinated rate was 74% (pretty high, but possible), then the conclusion is that the vaccine doesn't prevent infections at all. If the vaccination rate was the highest possible at 99% (it can't be 100% because there are some who were infected and not vaccinated), then the vaccine is 23% effective at preventing infection. That's the highest it could possibly be when assuming best case for the unknown details. Why focus on this case?!


    I can't find the first post for this subthread. Do we have a number for the total population at this event? I think we need that to calculate denominators when figuring out relative infection rates among the vaccinated and unvaccinated populations, even if we're willing to make assumptions about the vax rate in that particular crowd. Also, 99% is not the highest; it could be 99.5% or 99.99% etc., which will make a significant difference in calculating the infection rates among vaxed and unvaxed if the crowd was sufficiently large. (At this point, I'm not even sure I remember where this event was. Somewhere in New England, right?)

    Sure, was sticking with whole numbers. We don't have a count for the whole event, nor would it change the conclusions discussed thus far. A vaccine that is only 25.99% effective still makes this case a statistical outlier (no way was the crowd big enough for even 99% even if all of the unvaccinated got infected, but I'll bite on your decimals).

    It was Provincetown, MA.

    I don't understand where you're getting the 25.99% figure from. If we don't know total numbers, we don't have a denominator to calculate effective rate.

    I'm willing to assume equal exposure across the total population at this event (although as @kimny72 points out, that's not something we can know).

    I think comparing total populations of a country or state or county with known vaccination rates, and known hospitalization and death rates with vaccination status of those cases known is a more reasonable way of going about trying to determine real-world, ongoing vaccine effectiveness against variants and with potentially decreasing protection as time-from-vaccination increases, than looking at presumed superspreader events with self-selected populations for whom vaccination status and attitudes toward vaxing and masking are likely to be factors in self-selection and in risk-avoidance during actual attendance. I can imagine a wide range of behaviors once I get to some kind of fair or festival style event that would greatly influence my risk of behavior.

    It's not a controlled experiment, and we can't know enough about the prevalence of characteristics and behavioral factors to draw good conclusions.


    Clearly I'm not explaining very well, so will try again. Here is what we know from the MMWR: 469 cases total, 346 (74%) cases in fully vaccinated persons. In state of Massachusetts, eligible residents were 69% vaccinated (it is the best we have available, so let's make some other assumptions also...).

    There are 2 things we are discussing as far as assumptions - vaccination rate of people in Provincetown at the time and the number of people in Provincetown at the time.

    Looking at differences in number of people (denominator you keep referencing):
    Assume 69% vaccination rate and 10,000 people:
    6,900 vaccinated and 3,100 unvaccinated.
    346 vaccinated got infected: 346/6,900 = 5.014% of vaccinated people got infected
    123 unvaccinated got infected: 123/3,100 = 3.968% of unvaccinated people got infected
    5.014% - 3.968% = 1.047% difference / 3.968% baseline = 26.3815% greater risk of infection if vaccinated

    Assume 69% vaccination rate and 100,000 people:
    69,000 vaccinated and 31,000 unvaccinated.
    346 vaccinated got infected: 346/69,000 = 0.5014% of vaccinated people got infected
    123 unvaccinated got infected: 123/31,000 = 0.3968% of unvaccinated people got infected
    .5014% - .3968% = 0.1047% difference / 0.3968% baseline = 26.3815% greater risk of infection if vaccinated.
    *I'm using Excel for calculations in order to keep decimals. If you round interim calculations, the results will come out different.

    Do you see how the number of people doesn't make a difference?

    Let's now consider differences in the percentage vaccinated:
    Assume 99% vaccination rate and 100,000 people:
    99,000 vaccinated and 1,000 unvaccinated.
    346 vaccinated got infected: 346/99,000 = 0.349% of vaccinated people got infected
    123 unvaccinated got infected: 123/1,000 = 12.300% of vaccinated people got infected
    12.300% - 0.349% = 11.951% difference / 0.349% baseline = 97.159% lower risk of infection if vaccinated. Only when we get to these extremes do we get close to the decreased risk that we are supposed to have when vaccinated.

    Assume 99% vaccination rate and 10,000 people:
    *Cannot assume this because 123 of those infected were unvaccinated. Even if every unvaccinated person there became sick, that is only 100 people. We know that at least 123 people there were not vaccinated, more than 100% of those possible under this assumption.

    Assume 85% vaccination rate and 100,000 people:
    85,000 vaccinated and 15,000 unvaccinated.
    346 vaccinated got infected: 346/85,000 = 0.407% of vaccinated people got infected
    123 unvaccinated got infected: 123/15,000 = 0.820% of vaccinated people got infected
    0.820% - 0.407% = 0.413% difference / 0.407% baseline = 50.359% lower risk of infection if vaccinated.

    Assume 74% vaccination rate (i.e. assume the population and the infected group are both at 74% vaccinated) and 100,000 people:
    74,000 vaccinated and 26,000 unvaccinated.
    346 vaccinated got infected: 346/74,000 = 0.468% of vaccinated people got infected
    123 unvaccinated got infected: 123/26,000 = 0.473% of vaccinated people got infected
    0.473% - 0.468% = 0.006% difference / 0.468% baseline = 1.165% lower risk of infection if vaccinated.

    In the end, the "denominator" / how many people were there is irrelevant in determining how much the vaccine decreases risk. The only fact that would make a difference is what percentage of the people in that location at that time were vaccinated. The very best information we have is 69% for the state.


    Thanks for showing your work. Shouldn't the baseline be the percentage of unvaccinated people who get infected, not the percentage of vaccinated people who get infected? It's a bit confusing to follow, since you have said vaccinated in some places where it appears you meant unvaccinated, but I think you're using % of vaccinated as the baseline.

    It does appear your actual calculations may have been done using the correct baselines: When I divide 0.413 by 0.407, I get 1.058, which is too much different from the 50.359% you show to be accounted for rounding error from retaining a different number of digits. But when I divide 0.413 by 0.82, I get 50.365%, close enough to assume the difference is rounding error.

    I'm afraid I'm not interested enough to check all the others. If this one event, for which we have poor data about the subject pool and their individual behaviors, is showing a radically different indication of vaccine efficacy than months of pre-approval tests and then wide-scale tests in the millions, I'm going to assume outlier or poor data, at least until the results are replicated a half-dozen or so times. I'm not going to throw out massive amounts of data to accommodate this one case.


    Edited to fix grammar and one of the run-on sentences.
  • T1DCarnivoreRunner
    T1DCarnivoreRunner Posts: 11,462 Member
    kimny72 wrote: »
    kimny72 wrote: »
    kimny72 wrote: »
    They also discussed this report on the Barnstable outbreak:

    www.cdc.gov/mmwr/volumes/70/wr/mm7031e2.htm

    They said there is a lot of info that simply wasn't collected that limits the conclusions you can draw. But what jumped out to them was that only 1% of known vaxxed attendees required hospitalization with 0 deaths. Also that the attendees interviewed described attending densely packed indoor/outdoor events including bars and house parties with minimal if any mitigations. Basically a recipe for breakthroughs.

    There was no clinical tracing done to try to determine who got who sick, so it doesn't really add to the conversation about how much vaxxed people are transmitting.

    This part goes over my head, but maybe it will mean something to someone. The paper notes that the CT values detected by the covid tests were similar between vaxxed and unvaxxed attendees who tested positive. Dr Griffin noted that the CT value is detecting the amount of COVID-19 Rna in the nose, not "necessarily" viral particles. He said public health officials seem to be assuming that similar amounts of RNA mean similar amounts of virus, but it is entirely possible that vaccine-induced antibodies have neutralized many of the viral particles, so the RNA being picked up by the test is in neutralized virus that isn't transmissible. My layman's understanding is he's questioning the assertion that vaxxed folks are "just as contagious" as unvaxxed.

    Interesting. Some may recall that I had pointed out that the area has a 69% vaccinated adult population and that 74% of the people who were infected had been vaccinated. Statistically, that means a vaccine increases your risk of infection. I questioned the data, but acknowledged it could be a statistical outlier. Many Disagreed with my comments on that, but now a specific concern with data collection has been identified.

    As to the gatherings in bars and homes: I'm not sure what everyone expects to happen during bear week; I am not surprised.

    Again, the 69% is for the entire state, not for the attendees of these events in this one town. The 69% and 74% have nothing to do with each other and comparing them statistically means absolutely nothing. It never meant vaccination increases your risk tif infection, regardless of how data was collected.

    I believe the focus on where they were gathering was to stress that this one situation shouldn't be extrapolated to most people's situation. These vaccinated people put themselves into a high risk, concentrated environment for an extended period of time. So it's no reason for some of the panicked reactions many are having if they are still being mindful of spacing and ventilation in places they can't be sure everyone is vaccinated and healthy.

    We will never have vaccinated rates for the exact population directly exposed. Using the state vaccination rate is reliable enough for the CDC to use in its MMWR.

    But you're using the whole state's percentage and assuming it's the rate for this one town's event and drawing a very specific conclusion. That's not how percentages or statistics work. Which is probably why no public health officials or researchers (including the CDC report) came to the conclusion you did. They found it concerning that vaxxed people were testing positive and changed their mask recommendations, but in no way did they suggest vaxxed people were more likely to get infected. Vaxx rates vary dramatically by county and by demographic within states.

    51% of the Virginia population is women, but 65% of the people in my local rural Food Lion this week were men, so statistically that means that men are more likely to go grocery shopping?

    This is fair, and we don't know anything beyond the state data. Having said that, if the vaccinated rate was 74% (pretty high, but possible), then the conclusion is that the vaccine doesn't prevent infections at all. If the vaccination rate was the highest possible at 99% (it can't be 100% because there are some who were infected and not vaccinated), then the vaccine is 23% effective at preventing infection. That's the highest it could possibly be when assuming best case for the unknown details. Why focus on this case?!


    I can't find the first post for this subthread. Do we have a number for the total population at this event? I think we need that to calculate denominators when figuring out relative infection rates among the vaccinated and unvaccinated populations, even if we're willing to make assumptions about the vax rate in that particular crowd. Also, 99% is not the highest; it could be 99.5% or 99.99% etc., which will make a significant difference in calculating the infection rates among vaxed and unvaxed if the crowd was sufficiently large. (At this point, I'm not even sure I remember where this event was. Somewhere in New England, right?)

    Sure, was sticking with whole numbers. We don't have a count for the whole event, nor would it change the conclusions discussed thus far. A vaccine that is only 25.99% effective still makes this case a statistical outlier (no way was the crowd big enough for even 99% even if all of the unvaccinated got infected, but I'll bite on your decimals).

    It was Provincetown, MA.

    I don't understand where you're getting the 25.99% figure from. If we don't know total numbers, we don't have a denominator to calculate effective rate.

    I'm willing to assume equal exposure across the total population at this event (although as @kimny72 points out, that's not something we can know).

    I think comparing total populations of a country or state or county with known vaccination rates, and known hospitalization and death rates with vaccination status of those cases known is a more reasonable way of going about trying to determine real-world, ongoing vaccine effectiveness against variants and with potentially decreasing protection as time-from-vaccination increases, than looking at presumed superspreader events with self-selected populations for whom vaccination status and attitudes toward vaxing and masking are likely to be factors in self-selection and in risk-avoidance during actual attendance. I can imagine a wide range of behaviors once I get to some kind of fair or festival style event that would greatly influence my risk of behavior.

    It's not a controlled experiment, and we can't know enough about the prevalence of characteristics and behavioral factors to draw good conclusions.


    Clearly I'm not explaining very well, so will try again. Here is what we know from the MMWR: 469 cases total, 346 (74%) cases in fully vaccinated persons. In state of Massachusetts, eligible residents were 69% vaccinated (it is the best we have available, so let's make some other assumptions also...).

    There are 2 things we are discussing as far as assumptions - vaccination rate of people in Provincetown at the time and the number of people in Provincetown at the time.

    Looking at differences in number of people (denominator you keep referencing):
    Assume 69% vaccination rate and 10,000 people:
    6,900 vaccinated and 3,100 unvaccinated.
    346 vaccinated got infected: 346/6,900 = 5.014% of vaccinated people got infected
    123 unvaccinated got infected: 123/3,100 = 3.968% of unvaccinated people got infected
    5.014% - 3.968% = 1.047% difference / 3.968% baseline = 26.3815% greater risk of infection if vaccinated

    Assume 69% vaccination rate and 100,000 people:
    69,000 vaccinated and 31,000 unvaccinated.
    346 vaccinated got infected: 346/69,000 = 0.5014% of vaccinated people got infected
    123 unvaccinated got infected: 123/31,000 = 0.3968% of unvaccinated people got infected
    .5014% - .3968% = 0.1047% difference / 0.3968% baseline = 26.3815% greater risk of infection if vaccinated.
    *I'm using Excel for calculations in order to keep decimals. If you round interim calculations, the results will come out different.

    Do you see how the number of people doesn't make a difference?

    Let's now consider differences in the percentage vaccinated:
    Assume 99% vaccination rate and 100,000 people:
    99,000 vaccinated and 1,000 unvaccinated.
    346 vaccinated got infected: 346/99,000 = 0.349% of vaccinated people got infected
    123 unvaccinated got infected: 123/1,000 = 12.300% of vaccinated people got infected
    12.300% - 0.349% = 11.951% difference / 0.349% baseline = 97.159% lower risk of infection if vaccinated. Only when we get to these extremes do we get close to the decreased risk that we are supposed to have when vaccinated.

    Assume 99% vaccination rate and 10,000 people:
    *Cannot assume this because 123 of those infected were unvaccinated. Even if every unvaccinated person there became sick, that is only 100 people. We know that at least 123 people there were not vaccinated, more than 100% of those possible under this assumption.

    Assume 85% vaccination rate and 100,000 people:
    85,000 vaccinated and 15,000 unvaccinated.
    346 vaccinated got infected: 346/85,000 = 0.407% of vaccinated people got infected
    123 unvaccinated got infected: 123/15,000 = 0.820% of vaccinated people got infected
    0.820% - 0.407% = 0.413% difference / 0.407% baseline = 50.359% lower risk of infection if vaccinated.

    Assume 74% vaccination rate (i.e. assume the population and the infected group are both at 74% vaccinated) and 100,000 people:
    74,000 vaccinated and 26,000 unvaccinated.
    346 vaccinated got infected: 346/74,000 = 0.468% of vaccinated people got infected
    123 unvaccinated got infected: 123/26,000 = 0.473% of vaccinated people got infected
    0.473% - 0.468% = 0.006% difference / 0.468% baseline = 1.165% lower risk of infection if vaccinated.

    In the end, the "denominator" / how many people were there is irrelevant in determining how much the vaccine decreases risk. The only fact that would make a difference is what percentage of the people in that location at that time were vaccinated. The very best information we have is 69% for the state.


    Thanks for showing your work. Shouldn't the baseline be the percentage of unvaccinated people who get infected, not the percentage of vaccinated people who get infected? It's a bit confusing to follow, since you have said vaccinated in some places where it appears you meant unvaccinated, but I think you're using % of vaccinated as the baseline.

    It does appear your actual calculations may have been done using the correct baselines: When I divide 0.413 by 0.407, I get 1.058, which is too much different from the 50.359% you show to be accounted for rounding error from retaining a different number of digits. But when I divide 0.413 by 0.82, I get 50.365%, close enough to assume the difference is rounding error.

    I'm afraid I'm not interested enough to check all the others. If this one event, for which we have poor data about the subject pool and their individual behaviors, is showing a radically different indication of vaccine efficacy than months of pre-approval tests and then wide-scale tests in the millions, I'm going to assume outlier or poor data, at least until the results are replicated a half-dozen or so times. I'm not going to throw out massive amounts of data to accommodate this one case.


    Edited to fix grammar and one of the run-on sentences.

    This is exactly my kitten point!!! Why would the CDC and media focus so much on a statistical outlier?!
  • T1DCarnivoreRunner
    T1DCarnivoreRunner Posts: 11,462 Member
    kimny72 wrote: »
    kimny72 wrote: »
    kimny72 wrote: »
    They also discussed this report on the Barnstable outbreak:

    www.cdc.gov/mmwr/volumes/70/wr/mm7031e2.htm

    They said there is a lot of info that simply wasn't collected that limits the conclusions you can draw. But what jumped out to them was that only 1% of known vaxxed attendees required hospitalization with 0 deaths. Also that the attendees interviewed described attending densely packed indoor/outdoor events including bars and house parties with minimal if any mitigations. Basically a recipe for breakthroughs.

    There was no clinical tracing done to try to determine who got who sick, so it doesn't really add to the conversation about how much vaxxed people are transmitting.

    This part goes over my head, but maybe it will mean something to someone. The paper notes that the CT values detected by the covid tests were similar between vaxxed and unvaxxed attendees who tested positive. Dr Griffin noted that the CT value is detecting the amount of COVID-19 Rna in the nose, not "necessarily" viral particles. He said public health officials seem to be assuming that similar amounts of RNA mean similar amounts of virus, but it is entirely possible that vaccine-induced antibodies have neutralized many of the viral particles, so the RNA being picked up by the test is in neutralized virus that isn't transmissible. My layman's understanding is he's questioning the assertion that vaxxed folks are "just as contagious" as unvaxxed.

    Interesting. Some may recall that I had pointed out that the area has a 69% vaccinated adult population and that 74% of the people who were infected had been vaccinated. Statistically, that means a vaccine increases your risk of infection. I questioned the data, but acknowledged it could be a statistical outlier. Many Disagreed with my comments on that, but now a specific concern with data collection has been identified.

    As to the gatherings in bars and homes: I'm not sure what everyone expects to happen during bear week; I am not surprised.

    Again, the 69% is for the entire state, not for the attendees of these events in this one town. The 69% and 74% have nothing to do with each other and comparing them statistically means absolutely nothing. It never meant vaccination increases your risk tif infection, regardless of how data was collected.

    I believe the focus on where they were gathering was to stress that this one situation shouldn't be extrapolated to most people's situation. These vaccinated people put themselves into a high risk, concentrated environment for an extended period of time. So it's no reason for some of the panicked reactions many are having if they are still being mindful of spacing and ventilation in places they can't be sure everyone is vaccinated and healthy.

    We will never have vaccinated rates for the exact population directly exposed. Using the state vaccination rate is reliable enough for the CDC to use in its MMWR.

    But you're using the whole state's percentage and assuming it's the rate for this one town's event and drawing a very specific conclusion. That's not how percentages or statistics work. Which is probably why no public health officials or researchers (including the CDC report) came to the conclusion you did. They found it concerning that vaxxed people were testing positive and changed their mask recommendations, but in no way did they suggest vaxxed people were more likely to get infected. Vaxx rates vary dramatically by county and by demographic within states.

    51% of the Virginia population is women, but 65% of the people in my local rural Food Lion this week were men, so statistically that means that men are more likely to go grocery shopping?

    This is fair, and we don't know anything beyond the state data. Having said that, if the vaccinated rate was 74% (pretty high, but possible), then the conclusion is that the vaccine doesn't prevent infections at all. If the vaccination rate was the highest possible at 99% (it can't be 100% because there are some who were infected and not vaccinated), then the vaccine is 23% effective at preventing infection. That's the highest it could possibly be when assuming best case for the unknown details. Why focus on this case?!


    I can't find the first post for this subthread. Do we have a number for the total population at this event? I think we need that to calculate denominators when figuring out relative infection rates among the vaccinated and unvaccinated populations, even if we're willing to make assumptions about the vax rate in that particular crowd. Also, 99% is not the highest; it could be 99.5% or 99.99% etc., which will make a significant difference in calculating the infection rates among vaxed and unvaxed if the crowd was sufficiently large. (At this point, I'm not even sure I remember where this event was. Somewhere in New England, right?)

    Sure, was sticking with whole numbers. We don't have a count for the whole event, nor would it change the conclusions discussed thus far. A vaccine that is only 25.99% effective still makes this case a statistical outlier (no way was the crowd big enough for even 99% even if all of the unvaccinated got infected, but I'll bite on your decimals).

    It was Provincetown, MA.

    I don't understand where you're getting the 25.99% figure from. If we don't know total numbers, we don't have a denominator to calculate effective rate.

    I'm willing to assume equal exposure across the total population at this event (although as @kimny72 points out, that's not something we can know).

    I think comparing total populations of a country or state or county with known vaccination rates, and known hospitalization and death rates with vaccination status of those cases known is a more reasonable way of going about trying to determine real-world, ongoing vaccine effectiveness against variants and with potentially decreasing protection as time-from-vaccination increases, than looking at presumed superspreader events with self-selected populations for whom vaccination status and attitudes toward vaxing and masking are likely to be factors in self-selection and in risk-avoidance during actual attendance. I can imagine a wide range of behaviors once I get to some kind of fair or festival style event that would greatly influence my risk of behavior.

    It's not a controlled experiment, and we can't know enough about the prevalence of characteristics and behavioral factors to draw good conclusions.


    Clearly I'm not explaining very well, so will try again. Here is what we know from the MMWR: 469 cases total, 346 (74%) cases in fully vaccinated persons. In state of Massachusetts, eligible residents were 69% vaccinated (it is the best we have available, so let's make some other assumptions also...).

    There are 2 things we are discussing as far as assumptions - vaccination rate of people in Provincetown at the time and the number of people in Provincetown at the time.

    Looking at differences in number of people (denominator you keep referencing):
    Assume 69% vaccination rate and 10,000 people:
    6,900 vaccinated and 3,100 unvaccinated.
    346 vaccinated got infected: 346/6,900 = 5.014% of vaccinated people got infected
    123 unvaccinated got infected: 123/3,100 = 3.968% of unvaccinated people got infected
    5.014% - 3.968% = 1.047% difference / 3.968% baseline = 26.3815% greater risk of infection if vaccinated

    Assume 69% vaccination rate and 100,000 people:
    69,000 vaccinated and 31,000 unvaccinated.
    346 vaccinated got infected: 346/69,000 = 0.5014% of vaccinated people got infected
    123 unvaccinated got infected: 123/31,000 = 0.3968% of unvaccinated people got infected
    .5014% - .3968% = 0.1047% difference / 0.3968% baseline = 26.3815% greater risk of infection if vaccinated.
    *I'm using Excel for calculations in order to keep decimals. If you round interim calculations, the results will come out different.

    Do you see how the number of people doesn't make a difference?

    Let's now consider differences in the percentage vaccinated:
    Assume 99% vaccination rate and 100,000 people:
    99,000 vaccinated and 1,000 unvaccinated.
    346 vaccinated got infected: 346/99,000 = 0.349% of vaccinated people got infected
    123 unvaccinated got infected: 123/1,000 = 12.300% of vaccinated people got infected
    12.300% - 0.349% = 11.951% difference / 0.349% baseline = 97.159% lower risk of infection if vaccinated. Only when we get to these extremes do we get close to the decreased risk that we are supposed to have when vaccinated.

    Assume 99% vaccination rate and 10,000 people:
    *Cannot assume this because 123 of those infected were unvaccinated. Even if every unvaccinated person there became sick, that is only 100 people. We know that at least 123 people there were not vaccinated, more than 100% of those possible under this assumption.

    Assume 85% vaccination rate and 100,000 people:
    85,000 vaccinated and 15,000 unvaccinated.
    346 vaccinated got infected: 346/85,000 = 0.407% of vaccinated people got infected
    123 unvaccinated got infected: 123/15,000 = 0.820% of vaccinated people got infected
    0.820% - 0.407% = 0.413% difference / 0.407% baseline = 50.359% lower risk of infection if vaccinated.

    Assume 74% vaccination rate (i.e. assume the population and the infected group are both at 74% vaccinated) and 100,000 people:
    74,000 vaccinated and 26,000 unvaccinated.
    346 vaccinated got infected: 346/74,000 = 0.468% of vaccinated people got infected
    123 unvaccinated got infected: 123/26,000 = 0.473% of vaccinated people got infected
    0.473% - 0.468% = 0.006% difference / 0.468% baseline = 1.165% lower risk of infection if vaccinated.

    In the end, the "denominator" / how many people were there is irrelevant in determining how much the vaccine decreases risk. The only fact that would make a difference is what percentage of the people in that location at that time were vaccinated. The very best information we have is 69% for the state.

    Again, the attendees who entered bars and venues were required to show proof of vaccination, which throws the vax rate for the state right out the window. Since it’s much more likely to become infected indoors, and only vaccinated people were indoors, it becomes a matter of comparing apples to oranges very quickly. What percent of unvaxxed people wandering outside in the streets, unable to enter a venue, were infected, versus what percentage of vaxxed people grinding in a tightly packed club?

    I had not heard that bars were requiring proof of vaccinations, but my understanding is that infections were blamed on both gatherings in bars and private homes. If 100% of people in bars were vaccinated (i.e. no forged vaccination cards, no claims for exemption), then that covers the bars, but not the private residences... and then we still don't know what percentage in Provincetown at that time were truly vaccinated.
  • rheddmobile
    rheddmobile Posts: 6,841 Member
    kimny72 wrote: »
    kimny72 wrote: »
    kimny72 wrote: »
    They also discussed this report on the Barnstable outbreak:

    www.cdc.gov/mmwr/volumes/70/wr/mm7031e2.htm

    They said there is a lot of info that simply wasn't collected that limits the conclusions you can draw. But what jumped out to them was that only 1% of known vaxxed attendees required hospitalization with 0 deaths. Also that the attendees interviewed described attending densely packed indoor/outdoor events including bars and house parties with minimal if any mitigations. Basically a recipe for breakthroughs.

    There was no clinical tracing done to try to determine who got who sick, so it doesn't really add to the conversation about how much vaxxed people are transmitting.

    This part goes over my head, but maybe it will mean something to someone. The paper notes that the CT values detected by the covid tests were similar between vaxxed and unvaxxed attendees who tested positive. Dr Griffin noted that the CT value is detecting the amount of COVID-19 Rna in the nose, not "necessarily" viral particles. He said public health officials seem to be assuming that similar amounts of RNA mean similar amounts of virus, but it is entirely possible that vaccine-induced antibodies have neutralized many of the viral particles, so the RNA being picked up by the test is in neutralized virus that isn't transmissible. My layman's understanding is he's questioning the assertion that vaxxed folks are "just as contagious" as unvaxxed.

    Interesting. Some may recall that I had pointed out that the area has a 69% vaccinated adult population and that 74% of the people who were infected had been vaccinated. Statistically, that means a vaccine increases your risk of infection. I questioned the data, but acknowledged it could be a statistical outlier. Many Disagreed with my comments on that, but now a specific concern with data collection has been identified.

    As to the gatherings in bars and homes: I'm not sure what everyone expects to happen during bear week; I am not surprised.

    Again, the 69% is for the entire state, not for the attendees of these events in this one town. The 69% and 74% have nothing to do with each other and comparing them statistically means absolutely nothing. It never meant vaccination increases your risk tif infection, regardless of how data was collected.

    I believe the focus on where they were gathering was to stress that this one situation shouldn't be extrapolated to most people's situation. These vaccinated people put themselves into a high risk, concentrated environment for an extended period of time. So it's no reason for some of the panicked reactions many are having if they are still being mindful of spacing and ventilation in places they can't be sure everyone is vaccinated and healthy.

    We will never have vaccinated rates for the exact population directly exposed. Using the state vaccination rate is reliable enough for the CDC to use in its MMWR.

    But you're using the whole state's percentage and assuming it's the rate for this one town's event and drawing a very specific conclusion. That's not how percentages or statistics work. Which is probably why no public health officials or researchers (including the CDC report) came to the conclusion you did. They found it concerning that vaxxed people were testing positive and changed their mask recommendations, but in no way did they suggest vaxxed people were more likely to get infected. Vaxx rates vary dramatically by county and by demographic within states.

    51% of the Virginia population is women, but 65% of the people in my local rural Food Lion this week were men, so statistically that means that men are more likely to go grocery shopping?

    This is fair, and we don't know anything beyond the state data. Having said that, if the vaccinated rate was 74% (pretty high, but possible), then the conclusion is that the vaccine doesn't prevent infections at all. If the vaccination rate was the highest possible at 99% (it can't be 100% because there are some who were infected and not vaccinated), then the vaccine is 23% effective at preventing infection. That's the highest it could possibly be when assuming best case for the unknown details. Why focus on this case?!


    I can't find the first post for this subthread. Do we have a number for the total population at this event? I think we need that to calculate denominators when figuring out relative infection rates among the vaccinated and unvaccinated populations, even if we're willing to make assumptions about the vax rate in that particular crowd. Also, 99% is not the highest; it could be 99.5% or 99.99% etc., which will make a significant difference in calculating the infection rates among vaxed and unvaxed if the crowd was sufficiently large. (At this point, I'm not even sure I remember where this event was. Somewhere in New England, right?)

    Sure, was sticking with whole numbers. We don't have a count for the whole event, nor would it change the conclusions discussed thus far. A vaccine that is only 25.99% effective still makes this case a statistical outlier (no way was the crowd big enough for even 99% even if all of the unvaccinated got infected, but I'll bite on your decimals).

    It was Provincetown, MA.

    I don't understand where you're getting the 25.99% figure from. If we don't know total numbers, we don't have a denominator to calculate effective rate.

    I'm willing to assume equal exposure across the total population at this event (although as @kimny72 points out, that's not something we can know).

    I think comparing total populations of a country or state or county with known vaccination rates, and known hospitalization and death rates with vaccination status of those cases known is a more reasonable way of going about trying to determine real-world, ongoing vaccine effectiveness against variants and with potentially decreasing protection as time-from-vaccination increases, than looking at presumed superspreader events with self-selected populations for whom vaccination status and attitudes toward vaxing and masking are likely to be factors in self-selection and in risk-avoidance during actual attendance. I can imagine a wide range of behaviors once I get to some kind of fair or festival style event that would greatly influence my risk of behavior.

    It's not a controlled experiment, and we can't know enough about the prevalence of characteristics and behavioral factors to draw good conclusions.


    Clearly I'm not explaining very well, so will try again. Here is what we know from the MMWR: 469 cases total, 346 (74%) cases in fully vaccinated persons. In state of Massachusetts, eligible residents were 69% vaccinated (it is the best we have available, so let's make some other assumptions also...).

    There are 2 things we are discussing as far as assumptions - vaccination rate of people in Provincetown at the time and the number of people in Provincetown at the time.

    Looking at differences in number of people (denominator you keep referencing):
    Assume 69% vaccination rate and 10,000 people:
    6,900 vaccinated and 3,100 unvaccinated.
    346 vaccinated got infected: 346/6,900 = 5.014% of vaccinated people got infected
    123 unvaccinated got infected: 123/3,100 = 3.968% of unvaccinated people got infected
    5.014% - 3.968% = 1.047% difference / 3.968% baseline = 26.3815% greater risk of infection if vaccinated

    Assume 69% vaccination rate and 100,000 people:
    69,000 vaccinated and 31,000 unvaccinated.
    346 vaccinated got infected: 346/69,000 = 0.5014% of vaccinated people got infected
    123 unvaccinated got infected: 123/31,000 = 0.3968% of unvaccinated people got infected
    .5014% - .3968% = 0.1047% difference / 0.3968% baseline = 26.3815% greater risk of infection if vaccinated.
    *I'm using Excel for calculations in order to keep decimals. If you round interim calculations, the results will come out different.

    Do you see how the number of people doesn't make a difference?

    Let's now consider differences in the percentage vaccinated:
    Assume 99% vaccination rate and 100,000 people:
    99,000 vaccinated and 1,000 unvaccinated.
    346 vaccinated got infected: 346/99,000 = 0.349% of vaccinated people got infected
    123 unvaccinated got infected: 123/1,000 = 12.300% of vaccinated people got infected
    12.300% - 0.349% = 11.951% difference / 0.349% baseline = 97.159% lower risk of infection if vaccinated. Only when we get to these extremes do we get close to the decreased risk that we are supposed to have when vaccinated.

    Assume 99% vaccination rate and 10,000 people:
    *Cannot assume this because 123 of those infected were unvaccinated. Even if every unvaccinated person there became sick, that is only 100 people. We know that at least 123 people there were not vaccinated, more than 100% of those possible under this assumption.

    Assume 85% vaccination rate and 100,000 people:
    85,000 vaccinated and 15,000 unvaccinated.
    346 vaccinated got infected: 346/85,000 = 0.407% of vaccinated people got infected
    123 unvaccinated got infected: 123/15,000 = 0.820% of vaccinated people got infected
    0.820% - 0.407% = 0.413% difference / 0.407% baseline = 50.359% lower risk of infection if vaccinated.

    Assume 74% vaccination rate (i.e. assume the population and the infected group are both at 74% vaccinated) and 100,000 people:
    74,000 vaccinated and 26,000 unvaccinated.
    346 vaccinated got infected: 346/74,000 = 0.468% of vaccinated people got infected
    123 unvaccinated got infected: 123/26,000 = 0.473% of vaccinated people got infected
    0.473% - 0.468% = 0.006% difference / 0.468% baseline = 1.165% lower risk of infection if vaccinated.

    In the end, the "denominator" / how many people were there is irrelevant in determining how much the vaccine decreases risk. The only fact that would make a difference is what percentage of the people in that location at that time were vaccinated. The very best information we have is 69% for the state.

    Again, the attendees who entered bars and venues were required to show proof of vaccination, which throws the vax rate for the state right out the window. Since it’s much more likely to become infected indoors, and only vaccinated people were indoors, it becomes a matter of comparing apples to oranges very quickly. What percent of unvaxxed people wandering outside in the streets, unable to enter a venue, were infected, versus what percentage of vaxxed people grinding in a tightly packed club?

    I had not heard that bars were requiring proof of vaccinations, but my understanding is that infections were blamed on both gatherings in bars and private homes. If 100% of people in bars were vaccinated (i.e. no forged vaccination cards, no claims for exemption), then that covers the bars, but not the private residences... and then we still don't know what percentage in Provincetown at that time were truly vaccinated.

    Yep, it’s very difficult to calculate. But if we assume that the vax requirements skew the numbers such that 85% of meaningful exposures occurred in vaccinated individuals, we get a 50% effective rate, per your calculations, which would match what’s on paper for Pfizer. 50% effective in preventing infection from delta.
  • lemurcat2
    lemurcat2 Posts: 7,870 Member
    edited August 2021
    kimny72 wrote: »
    kimny72 wrote: »
    kimny72 wrote: »
    They also discussed this report on the Barnstable outbreak:

    www.cdc.gov/mmwr/volumes/70/wr/mm7031e2.htm

    They said there is a lot of info that simply wasn't collected that limits the conclusions you can draw. But what jumped out to them was that only 1% of known vaxxed attendees required hospitalization with 0 deaths. Also that the attendees interviewed described attending densely packed indoor/outdoor events including bars and house parties with minimal if any mitigations. Basically a recipe for breakthroughs.

    There was no clinical tracing done to try to determine who got who sick, so it doesn't really add to the conversation about how much vaxxed people are transmitting.

    This part goes over my head, but maybe it will mean something to someone. The paper notes that the CT values detected by the covid tests were similar between vaxxed and unvaxxed attendees who tested positive. Dr Griffin noted that the CT value is detecting the amount of COVID-19 Rna in the nose, not "necessarily" viral particles. He said public health officials seem to be assuming that similar amounts of RNA mean similar amounts of virus, but it is entirely possible that vaccine-induced antibodies have neutralized many of the viral particles, so the RNA being picked up by the test is in neutralized virus that isn't transmissible. My layman's understanding is he's questioning the assertion that vaxxed folks are "just as contagious" as unvaxxed.

    Interesting. Some may recall that I had pointed out that the area has a 69% vaccinated adult population and that 74% of the people who were infected had been vaccinated. Statistically, that means a vaccine increases your risk of infection. I questioned the data, but acknowledged it could be a statistical outlier. Many Disagreed with my comments on that, but now a specific concern with data collection has been identified.

    As to the gatherings in bars and homes: I'm not sure what everyone expects to happen during bear week; I am not surprised.

    Again, the 69% is for the entire state, not for the attendees of these events in this one town. The 69% and 74% have nothing to do with each other and comparing them statistically means absolutely nothing. It never meant vaccination increases your risk tif infection, regardless of how data was collected.

    I believe the focus on where they were gathering was to stress that this one situation shouldn't be extrapolated to most people's situation. These vaccinated people put themselves into a high risk, concentrated environment for an extended period of time. So it's no reason for some of the panicked reactions many are having if they are still being mindful of spacing and ventilation in places they can't be sure everyone is vaccinated and healthy.

    We will never have vaccinated rates for the exact population directly exposed. Using the state vaccination rate is reliable enough for the CDC to use in its MMWR.

    But you're using the whole state's percentage and assuming it's the rate for this one town's event and drawing a very specific conclusion. That's not how percentages or statistics work. Which is probably why no public health officials or researchers (including the CDC report) came to the conclusion you did. They found it concerning that vaxxed people were testing positive and changed their mask recommendations, but in no way did they suggest vaxxed people were more likely to get infected. Vaxx rates vary dramatically by county and by demographic within states.

    51% of the Virginia population is women, but 65% of the people in my local rural Food Lion this week were men, so statistically that means that men are more likely to go grocery shopping?

    This is fair, and we don't know anything beyond the state data. Having said that, if the vaccinated rate was 74% (pretty high, but possible), then the conclusion is that the vaccine doesn't prevent infections at all. If the vaccination rate was the highest possible at 99% (it can't be 100% because there are some who were infected and not vaccinated), then the vaccine is 23% effective at preventing infection. That's the highest it could possibly be when assuming best case for the unknown details. Why focus on this case?!


    I can't find the first post for this subthread. Do we have a number for the total population at this event? I think we need that to calculate denominators when figuring out relative infection rates among the vaccinated and unvaccinated populations, even if we're willing to make assumptions about the vax rate in that particular crowd. Also, 99% is not the highest; it could be 99.5% or 99.99% etc., which will make a significant difference in calculating the infection rates among vaxed and unvaxed if the crowd was sufficiently large. (At this point, I'm not even sure I remember where this event was. Somewhere in New England, right?)

    Sure, was sticking with whole numbers. We don't have a count for the whole event, nor would it change the conclusions discussed thus far. A vaccine that is only 25.99% effective still makes this case a statistical outlier (no way was the crowd big enough for even 99% even if all of the unvaccinated got infected, but I'll bite on your decimals).

    It was Provincetown, MA.

    I don't understand where you're getting the 25.99% figure from. If we don't know total numbers, we don't have a denominator to calculate effective rate.

    I'm willing to assume equal exposure across the total population at this event (although as @kimny72 points out, that's not something we can know).

    I think comparing total populations of a country or state or county with known vaccination rates, and known hospitalization and death rates with vaccination status of those cases known is a more reasonable way of going about trying to determine real-world, ongoing vaccine effectiveness against variants and with potentially decreasing protection as time-from-vaccination increases, than looking at presumed superspreader events with self-selected populations for whom vaccination status and attitudes toward vaxing and masking are likely to be factors in self-selection and in risk-avoidance during actual attendance. I can imagine a wide range of behaviors once I get to some kind of fair or festival style event that would greatly influence my risk of behavior.

    It's not a controlled experiment, and we can't know enough about the prevalence of characteristics and behavioral factors to draw good conclusions.


    Clearly I'm not explaining very well, so will try again. Here is what we know from the MMWR: 469 cases total, 346 (74%) cases in fully vaccinated persons. In state of Massachusetts, eligible residents were 69% vaccinated (it is the best we have available, so let's make some other assumptions also...).

    There are 2 things we are discussing as far as assumptions - vaccination rate of people in Provincetown at the time and the number of people in Provincetown at the time.

    Looking at differences in number of people (denominator you keep referencing):
    Assume 69% vaccination rate and 10,000 people:
    6,900 vaccinated and 3,100 unvaccinated.
    346 vaccinated got infected: 346/6,900 = 5.014% of vaccinated people got infected
    123 unvaccinated got infected: 123/3,100 = 3.968% of unvaccinated people got infected
    5.014% - 3.968% = 1.047% difference / 3.968% baseline = 26.3815% greater risk of infection if vaccinated

    Assume 69% vaccination rate and 100,000 people:
    69,000 vaccinated and 31,000 unvaccinated.
    346 vaccinated got infected: 346/69,000 = 0.5014% of vaccinated people got infected
    123 unvaccinated got infected: 123/31,000 = 0.3968% of unvaccinated people got infected
    .5014% - .3968% = 0.1047% difference / 0.3968% baseline = 26.3815% greater risk of infection if vaccinated.
    *I'm using Excel for calculations in order to keep decimals. If you round interim calculations, the results will come out different.

    Do you see how the number of people doesn't make a difference?

    Let's now consider differences in the percentage vaccinated:
    Assume 99% vaccination rate and 100,000 people:
    99,000 vaccinated and 1,000 unvaccinated.
    346 vaccinated got infected: 346/99,000 = 0.349% of vaccinated people got infected
    123 unvaccinated got infected: 123/1,000 = 12.300% of vaccinated people got infected
    12.300% - 0.349% = 11.951% difference / 0.349% baseline = 97.159% lower risk of infection if vaccinated. Only when we get to these extremes do we get close to the decreased risk that we are supposed to have when vaccinated.

    Assume 99% vaccination rate and 10,000 people:
    *Cannot assume this because 123 of those infected were unvaccinated. Even if every unvaccinated person there became sick, that is only 100 people. We know that at least 123 people there were not vaccinated, more than 100% of those possible under this assumption.

    Assume 85% vaccination rate and 100,000 people:
    85,000 vaccinated and 15,000 unvaccinated.
    346 vaccinated got infected: 346/85,000 = 0.407% of vaccinated people got infected
    123 unvaccinated got infected: 123/15,000 = 0.820% of vaccinated people got infected
    0.820% - 0.407% = 0.413% difference / 0.407% baseline = 50.359% lower risk of infection if vaccinated.

    Assume 74% vaccination rate (i.e. assume the population and the infected group are both at 74% vaccinated) and 100,000 people:
    74,000 vaccinated and 26,000 unvaccinated.
    346 vaccinated got infected: 346/74,000 = 0.468% of vaccinated people got infected
    123 unvaccinated got infected: 123/26,000 = 0.473% of vaccinated people got infected
    0.473% - 0.468% = 0.006% difference / 0.468% baseline = 1.165% lower risk of infection if vaccinated.

    In the end, the "denominator" / how many people were there is irrelevant in determining how much the vaccine decreases risk. The only fact that would make a difference is what percentage of the people in that location at that time were vaccinated. The very best information we have is 69% for the state.

    Again, the attendees who entered bars and venues were required to show proof of vaccination, which throws the vax rate for the state right out the window. Since it’s much more likely to become infected indoors, and only vaccinated people were indoors, it becomes a matter of comparing apples to oranges very quickly. What percent of unvaxxed people wandering outside in the streets, unable to enter a venue, were infected, versus what percentage of vaxxed people grinding in a tightly packed club?

    Right, and most of those infected likely came specifically for the event and can't be looked at based on MA overall vaxx rate. We simply don't know what the percentage is, but it was likely quite high.

    For example, the Lolla attendees were 88% vaxxed, according to what I've read, and Suzy's post upthread. That is far higher than IL's overall vax rate, or Chicago's.

    That aside, I agree with Carnivore's overall point, which is that we don't have the relevant information to use this as some significant example of how easily it spreads in vaxxed people.
  • hansep0012
    hansep0012 Posts: 383 Member
    kimny72 wrote: »
    33gail33 wrote: »
    PAV8888 wrote: »
    33gail33 wrote: »

    It would be awesome to just write off the unvaccinated, but in order for that to work we'd need to quarantine them on an island. There are too many of them to ignore. They are a fertile breeding ground for mutations, one of which that could blow right thru the vaccines being a possibility. And it seems with covid-19, the volume of shedding and time and closeness of exposure is important. So if you walk past a shedder in the grocery, your risk is really low. But if you sit next to an unvaxxed shedding person on a bus for 20 minutes, even vaxxed there is a better chance you will get legit sick. I follow a guy on Twitter whose family of 4, three vaxxed and a little one not vaxxed, went on a road trip. They all felt fluish by the time they got home, and all tested positive and were sick at home for a week or so. The assumption being the little one caught it and spread it to the rest of the family over hours in a car.


    .....and we call that island Texas....and we grant the wish of Texas to secede from the USA....and then we close the border of Texas....and enforce travel bans to and from .......
  • lemurcat2
    lemurcat2 Posts: 7,870 Member
    edited August 2021
    kshama2001 wrote: »
    ahoy_m8 wrote: »
    I get your point -- don't focus on a statistical outlier. But to respond to your question -- why focus on it -- the answer is to see if anything new can be learned from it. Maybe nothing can be learned. Maybe something can be learned. But they have to examine it if anything is to be learned. IMHO, I want the CDC to be examining all the new data to enhance their observations and understanding of this novel virus.

    Frankly, I'm disappointed that they are NOT tracking vaccine breakthrough infection data unless it results in hospitalization or death (which, because vaccines work, is an incredibly small fraction of total breakthrough infections). There is a lot that people want to know about breakthrough infections, e.g.
    - is the incidence higher in some vaccine brands than others?
    - is there a relationship between incidence and time since vaccination?
    - do the incidents correlate to particular vaccine administration sites (suggesting handling might impact efficacy)?

    What disappoints me is reduction in testing. I've heard on this thread and elsewhere than many people are back to being presumed COVID positive, but not actually tested. I doubt those presumed positive would make it into statistics.

    When 5 people in my partner's brother's family got sick and two tested positive, they didn't bother testing the other three. Sure, presuming they have COVID as well is a safe bet, but this will mess up statistics.

    (Four were vaxxed, with all three different vaccines among them. The fifth was two years old, and so not eligible for the vax. He is likely Patient Zero.)

    I don't think there's been some huge reduction in testing. Ever since we got enough tests to be able to test everyone who wanted one (so like late spring of last year), my state and city have had their positivity rate vary with actual cases and, especially hospitilizations. If the positivity rate rises a bunch, yeah, they are testing too little, but that hasn't happened outside of places with outbreaks obvious for other reasons. Generally posititvity rates have fluctuated with increased cases and hospitilization, but unlike (a) last spring here, (b) NY/NJ when they were at the worst of it, and (c) some other states who got hit without preparation last fall/winter (I recall when IA's rate was way up), the rate here and outside of a few southern states (that we all can probably identify) the positivity rate seems fine. It's higher than I'd like here vs early summer (bc too few people are vaccinated vs the fact they could be), but I don't think it suggests there are lots of cases being missed.

    I am totally fine (in favor of) policies that require people to be either (a) vaxxed or (b) masked and tested a bunch. I don't see a need to mask or test vaxxed people, especially in places like my office where everyone is vaxxed. (If I had suspicion I had it I'd get an appt or buy an at home test.)
  • Fuzzipeg
    Fuzzipeg Posts: 2,243 Member
    I've had such big hopes for NZ, that you could avoid all that has been going on in the UK and other countries in the last 18 months and more. I hope its possible to locate the more, if there are any, "contact cases". I think the first officially identified case was a person, a seemingly spontaneous one off case, who had no knows possible contact.

    Wishing you all the very best, that this situation can be overcome soon. Take care, Keep Safe.
  • lokihen
    lokihen Posts: 372 Member
    I read that it's up to 7 cases in New Zealand now.
  • SModa61
    SModa61 Posts: 2,090 Member
    I decided to see what additional info the internet had on the NZ situation. I came across an unexpected article. It’s content applies to all of us, not just NZ. https://www.google.com/amp/s/amp.theguardian.com/world/2021/jul/08/new-zealand-children-falling-ill-in-high-numbers-due-to-covid-immunity-debt