I double-cruxed this article because my “voice of caution” objected to it.
I eventually realized the issue was that part of my decision-making process when I do something weird, potentially risky, or expensive, is to consult with friends and family. Yet I feel that the feedback I would get from them would be so thoughtless, negative, frustrating, and potentially damaging, that it’s not worthwhile. And I don’t want to ignore this “consult someone first” rule, because it seems like a generally good rule that loses its force if ignored.
However, I do know some specific people who might be good to talk it over with. They’re warm, open-minded, very smart, scientifically literate, unconventional, have my best interests in mind, trustworthy, and willing to discuss this kind of stuff at length. My next move is probably not to read the paper, but rather to discuss it with them.
I think what you have done here is re-invented the actual helpful version of a practice whose authoritarian bureaucratic cargo-culted version is called “anonymous peer review”.
It is easy (and maybe dangerously wrong) to come to the straightforward conclusion that peer review in general is simply evil bullshit… until one finds the place from which a benevolent truth-oriented human (like oneself) finds a reason to consult with an actual “epistemic peer” as a prudent and socially-embedded response to one’s own uncertainty about things one cares about.
I talked this out with a consultant friend who got his BS in biology. Here’s what we came up with.
A conceptual solution would have the following variables, labeled for clarity.
Cost of vaccine = C
C = (Cost of manufacturing RacVac) ÷ (Doses you’ll administer) + (Dollar value to represent cost of unconventionality of the project)
Probably that vaccine provides value = P
P = (Chance that RadVac works at all) x (Effectiveness if it does work) x (Chance you’ll catch COVID before getting vaccinated) x (Chance you’ll fail in your execution)
Value that could be provided per person = V
V = [ (Dollar value of your life) x (Chance you’ll die if you catch COVID) + (Dollar value of avoiding a day on a ventilator) x (Chance of serious case of COVID) x (About 14 days on a ventilator) + (Dollar value of avoiding a day of fatigue/anosia) x (Chance of long-term fatigue/anosia) x (Expected length of long-term fatigue) + (Expected number of days out of work) x (Cost of lost work) + (Expected out-of-pocket cost of medical care if you caught COVID)]
P’ = 1 - (Chance you’ll transmit it to a particular other person if you catch it) x (Chance they’d have caught it anyway)
V’ = Calculation of V but for another specific person in your life who’d be at risk of COVID if you caught it
If C < P[V + ΣP’V’], it would be worth taking RadVac.
Potential sources for some of these estimates:
(Chance that RadVac works at all) = (Number of vaccines major pharma companies send to preclinical trials) / (Number of vaccines they put in clinical trials) x 33.4%
(Effectiveness if it does work) = (Average effectiveness of mRNA vaccines that have been released so far)
(Chance you’ll catch COVID before getting vaccinated), (Chance you’ll transmit it to a particular other person if you catch it), (Chance they’d have caught it anyway) = Calculated by adding up your own and other people’s activities using the microCOVID risk calculator.
(Dollar value of a life) = (Dollar value placed on a citizen’s life by their federal government)
However, you’d first want to consider if there are other interventions that are even more cost-effective for the same risk factor. For example, if you’re still shopping at the grocery store, consider having your groceries delivered for the next six months.
I made a little different, simplified take on the matter:
For Radvac to be net useful, it needs that following is true:
p(RV prevents Covid)*p(user gets Covid [is exposed to Covid such that it would lead to infection])*p(Covid causes long term harm) > p(RV causes long term harm)
p(RV harm) is currently from the RV paper likely less than 1/10000, cited example is Pandemrix that caused long term harm of narcolepsy with 1/16000 if you had Swedish or Finnish genome.
p(Covid harm) is high in old people, where you can die with up to 25% probability, but for most of young people around here long Covid would seem to dominate and that seems to be maybe 1%. Long Covid probability seems to be not well found, and this seems a likely direction for improving decision with better data.
with these presets we get:
p(RV prevents Covid)*p(user gets Covid) > p(RV harm)/p(Covid harm) ⇔
p(RV prevents Covid)*p(get Covid) > 0,0001⁄0,01 = 0,01
from this, we get 3 inequalities as boundary conditions:
(presume scenario where getting Covid is max, that is 100% ⇒ prevention needs to be > 0,01; vice versa)
p(RV prevents Covid) > 0,01
p(get Covid) > 0,01
p(RV prevents Covid)*p(get Covid) > 0,01
so with current boundary conditions the key thing to find out with Radvac is how likely it is to cure Covid. This needs to be shown likely to be over 1% or it should not be used unless other boundary conditions can be shown to differ.
An aside: this same calculation applies to all other vaccines, which is why the effort has been put into making sure p(harm from vaccine) is ascertained to be much less than 1/10000. This making sure the vaccine harms the least is about necessary condition for mass vaccinations to be net useful for the participants themselves. This is why we have used 1 year+ for safety testing, which gives us way better and lower prior for vaccine harm than 1/10000. If you get no long term harm from N trial persons, then per succession rule your naive prior is that p(harm) < 1/(N+2).
A friend offered that page 7 of white paper could maybe be used to deduce that Radvac would prevent Covid with ~40%.
This would mean the decision boundaries would get to
p(Covid)*40% > 0.01 ⇔
p(Covid) > 0.01/0.40 ⇔
p(Covid) > 0.025
so then you would need your chance to get Covid to be over 2.5% for the use to be net beneficial.
If we also presume a 80+ year old person who has 25% probability of death given Covid, then it becomes
so for them the chance to get Covid before official vaccination would need to be over 0.001 for it to be net beneficial with these boundary conditions.
I double-cruxed this article because my “voice of caution” objected to it.
I eventually realized the issue was that part of my decision-making process when I do something weird, potentially risky, or expensive, is to consult with friends and family. Yet I feel that the feedback I would get from them would be so thoughtless, negative, frustrating, and potentially damaging, that it’s not worthwhile. And I don’t want to ignore this “consult someone first” rule, because it seems like a generally good rule that loses its force if ignored.
However, I do know some specific people who might be good to talk it over with. They’re warm, open-minded, very smart, scientifically literate, unconventional, have my best interests in mind, trustworthy, and willing to discuss this kind of stuff at length. My next move is probably not to read the paper, but rather to discuss it with them.
I think what you have done here is re-invented the actual helpful version of a practice whose authoritarian bureaucratic cargo-culted version is called “anonymous peer review”.
It is easy (and maybe dangerously wrong) to come to the straightforward conclusion that peer review in general is simply evil bullshit… until one finds the place from which a benevolent truth-oriented human (like oneself) finds a reason to consult with an actual “epistemic peer” as a prudent and socially-embedded response to one’s own uncertainty about things one cares about.
I talked this out with a consultant friend who got his BS in biology. Here’s what we came up with.
A conceptual solution would have the following variables, labeled for clarity.
Cost of vaccine = C
C = (Cost of manufacturing RacVac) ÷ (Doses you’ll administer) + (Dollar value to represent cost of unconventionality of the project)
Probably that vaccine provides value = P
P = (Chance that RadVac works at all) x (Effectiveness if it does work) x (Chance you’ll catch COVID before getting vaccinated) x (Chance you’ll fail in your execution)
Value that could be provided per person = V
V = [ (Dollar value of your life) x (Chance you’ll die if you catch COVID) + (Dollar value of avoiding a day on a ventilator) x (Chance of serious case of COVID) x (About 14 days on a ventilator) + (Dollar value of avoiding a day of fatigue/anosia) x (Chance of long-term fatigue/anosia) x (Expected length of long-term fatigue) + (Expected number of days out of work) x (Cost of lost work) + (Expected out-of-pocket cost of medical care if you caught COVID)]
P’ = 1 - (Chance you’ll transmit it to a particular other person if you catch it) x (Chance they’d have caught it anyway)
V’ = Calculation of V but for another specific person in your life who’d be at risk of COVID if you caught it
If C < P[V + ΣP’V’], it would be worth taking RadVac.
Potential sources for some of these estimates:
(Chance that RadVac works at all) = (Number of vaccines major pharma companies send to preclinical trials) / (Number of vaccines they put in clinical trials) x 33.4%
(Effectiveness if it does work) = (Average effectiveness of mRNA vaccines that have been released so far)
(Chance you’ll catch COVID before getting vaccinated), (Chance you’ll transmit it to a particular other person if you catch it), (Chance they’d have caught it anyway) = Calculated by adding up your own and other people’s activities using the microCOVID risk calculator.
(Dollar value of a life) = (Dollar value placed on a citizen’s life by their federal government)
(Chance they’ll die if you catch COVID) = Hospitalization and death rates by age
(Chance of lingering effects of COVID) = 52.3%
However, you’d first want to consider if there are other interventions that are even more cost-effective for the same risk factor. For example, if you’re still shopping at the grocery store, consider having your groceries delivered for the next six months.
I made a little different, simplified take on the matter:
For Radvac to be net useful, it needs that following is true: p(RV prevents Covid)*p(user gets Covid [is exposed to Covid such that it would lead to infection])*p(Covid causes long term harm) > p(RV causes long term harm)
p(RV harm) is currently from the RV paper likely less than 1/10000, cited example is Pandemrix that caused long term harm of narcolepsy with 1/16000 if you had Swedish or Finnish genome. p(Covid harm) is high in old people, where you can die with up to 25% probability, but for most of young people around here long Covid would seem to dominate and that seems to be maybe 1%. Long Covid probability seems to be not well found, and this seems a likely direction for improving decision with better data.
with these presets we get: p(RV prevents Covid)*p(user gets Covid) > p(RV harm)/p(Covid harm) ⇔ p(RV prevents Covid)*p(get Covid) > 0,0001⁄0,01 = 0,01
from this, we get 3 inequalities as boundary conditions: (presume scenario where getting Covid is max, that is 100% ⇒ prevention needs to be > 0,01; vice versa)
p(RV prevents Covid) > 0,01
p(get Covid) > 0,01
p(RV prevents Covid)*p(get Covid) > 0,01
so with current boundary conditions the key thing to find out with Radvac is how likely it is to cure Covid. This needs to be shown likely to be over 1% or it should not be used unless other boundary conditions can be shown to differ.
An aside: this same calculation applies to all other vaccines, which is why the effort has been put into making sure p(harm from vaccine) is ascertained to be much less than 1/10000. This making sure the vaccine harms the least is about necessary condition for mass vaccinations to be net useful for the participants themselves. This is why we have used 1 year+ for safety testing, which gives us way better and lower prior for vaccine harm than 1/10000. If you get no long term harm from N trial persons, then per succession rule your naive prior is that p(harm) < 1/(N+2).
A friend offered that page 7 of white paper could maybe be used to deduce that Radvac would prevent Covid with ~40%.
This would mean the decision boundaries would get to p(Covid)*40% > 0.01 ⇔ p(Covid) > 0.01/0.40 ⇔ p(Covid) > 0.025 so then you would need your chance to get Covid to be over 2.5% for the use to be net beneficial.
If we also presume a 80+ year old person who has 25% probability of death given Covid, then it becomes
p(RV works)*p(get Covid)*p(Covid harm) > p(RV harm) ⇔ p(Covid)*40%25% > 1/10000 ⇔ p(Covid) > 0.0001/(0.40.25) = 0.001
so for them the chance to get Covid before official vaccination would need to be over 0.001 for it to be net beneficial with these boundary conditions.