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GoatXi t1_j2ovudr wrote

Makes sense. A body that fights off an infection faster has less time to transmit it to others.

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Don_Ford t1_j2s6vm4 wrote

I mean, yes, but when you read the inclusions for the study you can see how they set it up to get the desired results.

We identified 1,226 index cases over the study period based on the
inclusion criteria of having a positive SARS-CoV-2 diagnostic test
(without a prior positive test in the preceding 90 days), continuous
incarceration beginning before 1 April 2020 (to ensure reliable
reporting of prior SARS-CoV-2 infection) and a valid close contact in a
shared, closed-door cell (Figs. 1 and 2 and Supplementary Fig. 1).
We defined close contacts of the index case as residents who shared a
cell with an index case for at least one night while the index case was
infectious (assuming a 5-day infectious period after a positive test22);
we required the close contact to have a negative SARS-CoV-2 test within
2 days of first exposure as well as follow-up testing data within
14 days after last exposure (64% of close contacts met both criteria).
Each index case was assigned a single close contact at random if
multiple contacts were identified (<0.1% of cases). Further
description of inclusion and exclusion criteria that were needed to
address concerns for confounding and misclassification is available in
the Methods.

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littleike0 t1_j2s783l wrote

Sorry…how exactly would this be selection bias?

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d_rookr t1_j2p1ywl wrote

Nature is maybe the most reputable scientific journal, so I trust the science.

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pony_trekker t1_j2rbm13 wrote

Lord between this and the Bills player last night, Dunning Kruger has run wild today.

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HamanitaMuscaria t1_j2qnsw1 wrote

"we estimate that unvaccinated Omicron cases had a 36% (95% confidence interval (CI): 31–42%) risk of transmitting infection to close contacts, as compared to a 28% (25–31%) risk among vaccinated cases"

um

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AusCan531 t1_j2qxwcl wrote

A 22% reduction is a long way from perfect, but very helpful in a contagion.

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Tricky-Potato-851 t1_j2robbu wrote

In theory. In the wild, graphing cases, it doesn't matter at all. In the wild all that determines case count, which is why the cases count charts like a stock market traded financial instrument, is the innate points at which humans see risk and actually run from that risk. Having been boosted simply increases the number of boosted entering the contagion pool until the exact same point of risk occurs.

This is why year over year, omicron vs delta was a bug that was roughly 10x as promiscuous with a severity rate 1/10th previous year... overall view of risk is the same.

And so it will continue until you reach near ubiquity of the virus and near harmlessness.

This stuff ain't even a medical problem, it's a human psychology problem, hence the total failure of the medical establishment. Policy did near zero even short term with shut downs and vaccines. Look at the charts and try to guess when policy happened vs simple geometric expansion and contractions at the same points you'd expect if covid was a hot or falling stock in your IRA. I forget the details, having abandoned covid as a pursuit, but the periodicity is between 100 and 120 days, like most things related to people(seasons are innate, not a human invention) and the ball just bounces a certain amplitude based on perceived risk from the reported severity on tv/ observed severity among peers. The rest is not even significant in swaying that progression. Ie, you can determine future covid numbers as a function of hospitalization rates, but NOT vaccine numbers(a fact in the wild and a philosophical challenge as to why that is if you disagree with my premise).

−4

DuckQueue t1_j2s3u5g wrote

> In the wild, graphing cases, it doesn't matter at all

This is wholly incorrect.

If you have a single case of a disease with an r0 of 2, after 20 generations of transmission you've got 2^20 - or just over 1 million cases.

If you reduce r0 by 22%, after that same 20 generations you have 1.56^20 - about 7000 - cases.

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SnooPuppers1978 t1_j2txo5x wrote

R doesn't stay high like that throughout generations, it will proportionately go down the more recently infected/immune people there are.

The calculations must be more nuanced than that.

After each generation you should adapt the number of potential vulnerable candidates compared to what initial R had.

It would flatten the curve though and in total there would be around 24% fewer cases, based on that model. But this model is of course still to basic to exactly match real world. So here you can see for instance, that max cases amount to 187k per generation vs 86k per gen in terms of flattening the curve (good for hospitals).

Edit: as an example R2 vs R1.56 with 100 starting infected and a a population of 1,000,000 could be something like that:

R2 Cases R1.56 Cases Total R2 Cases Total R1.56 Cases
100 100 100 100
200 156 300 256
400 243 700 499
799 379 1499 878
1596 591 3095 1469
3182 921 6277 2390
6324 1433 12601 3823
12489 2227 25090 6050
24351 3453 49441 9503
46294 5335 95735 14838
83724 8199 179459 23037
137398 12496 316857 35533
187725 18801 504582 54334
186005 27736 690587 82070
115105 39717 805692 121787
44732 54413 850424 176200
13382 69928 863806 246128
3645 82238 867451 328366
966 86165 868417 414531
254 78697 868671 493228
67 62215 868738 555443
18 43147 868756 598590
5 27019 868761 625609
1 15780 868762 641389
0 8828 868762 650217
0 4817 868762 655034
0 2592 868762 657626
0 1384 868762 659010
0 736 868762 659746
0 391 868762 660137
0 207 868762 660344
0 110 868762 660454
0 58 868762 660512
0 31 868762 660543
0 16 868762 660559
0 8 868762 660567
0 4 868762 660571
0 2 868762 660573​

With a slightly more accurate script and simulation I got the following:

R0 Gens before < 10 infections Total Cases Max Cases in a Gen
0.78 10 428 78
1 2152 45472 100
1.28 63 403244 25961
1.64 35 662799 87996
2.1 24 822088 168399
2.68 18 913575 254938
3.44 14 963671 322040
4.4 12 987001 373786
5.63 10 996338 457475
7.21 8 999257 586940
9.22 7 999901 455211
11.81 7 999993 691460
15.11 6 1000000 684507
19.34 6 1000000 487709
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DuckQueue t1_j2wnm2i wrote

> After each generation you should adapt the number of potential vulnerable candidates compared to what initial R had.

In the abstract your point isn't wrong, but in the real world population sizes are much larger, resistance is imperfect to begin with, mutation occurs, and we're talking about a disease where previous infection doesn't confer a high degree of resistance that persists over the long-term - like COVID - so that isn't going to have nearly as large an impact as you're suggesting with your example.

1

SnooPuppers1978 t1_j2woh6q wrote

> In the abstract your point isn't wrong, but in the real world population sizes are much larger, resistance is imperfect to begin with, mutation occurs, and we're talking about a disease where previous infection doesn't confer a high degree of resistance that persists over the long-term - like COVID - so that isn't going to have nearly as large an impact as you're suggesting with your example.

Yes, all of this can be adapted to the model, but eventual result will still be a wave like graph, where difference of 22% would get lower the higher the R0 is and the end results in terms of magnitudes would be very similar to what I showed above.

Whether the population is 1,000,000 here or 1,000,000,000 doesn't make that much of a difference though. It's just few generations more.

We could create a model that incorporates waning immunity based on the studies we've seen. And also run a vaccine like intervention to see how results would differ. We could try to use 8 billion people and try to roll out vaccine to all of them within certain timeframe. I might do it during the weekend if I have time.

The results with 1 billion population here - you can see that it's just few more gens, magnitude wise, proportionally not that much difference:

R0 Gens before < 10 infections Total Cases Max Cases in a Gen
0.78 10 428 78
1 2153540 45454565 100
1.28 117 403004862 25885890
1.64 60 662734374 88055684
2.1 40 822064894 170459771
2.68 30 913564065 254590943
3.44 23 963666407 343953730
4.4 19 986999921 429451582
5.63 16 996336642 456685926
7.21 13 999256872 437456355
9.22 12 999900871 527835860
11.81 10 999992570 696393878
15.11 9 999999726 623729861
19.34 8 999999996 744938203
1

DuckQueue t1_j2wpnl4 wrote

> It's just few generations more.

Like... twice as many. Yes, not multiple orders of magnitude but still enough to make a huge difference, especially when you account for the other factors I mentioned.

And that still wouldn't account for how diseases actually spread in real populations, where not everyone has an equal chance of being exposed to any given other person. There's a reason actual models of the spread of disease are much more complex than the model you're providing. And a reason why observational estimates of the R0 for COVID haven't been appreciably declining over time.

1

SnooPuppers1978 t1_j2wqqe5 wrote

Yes, but there's also factors to the other side. As the OP above mentioned people will adapt their behaviour depending on how they perceive the risk for themselves. If people have vaccinated and perceive the risk as lower, they will be more likely to go out. If there's a huge wave currently ongoing, people will be less likely to go out. If there's little threat, people will go out more likely, making the likelihood of new wave to start higher. Risk behaviour will be another balancing factor that will make the wave smooth out whether you have the intervention or not. If people see death around them, they get scared and start to avoid, if people see no danger, they will increase their risk behaviour. Behaviour will influence the R0 so much. Imagine being in contact with 50% fewer people than you were previously. That would be halving the R.

So in the end with all those factors together, unless the efficacy is enough to create herd immunity it's going to be waves with not much differing total amount of cases. Efficacy has to be enough for herd immunity or very close to that, otherwise yeah, it would just be something like that.

Main effect will be for risk groups for whom the risk of the disease will be much lower in terms of hospitalisations and death thanks to their immune systems being prepared from the vaccine. And in addition less overload on hospitals due to flattening the curve, but in the end total amount of infections are not going to be magnitudes away due to inherent characteristics of this virus.

1

DuckQueue t1_j2ws3t1 wrote

> So in the end with all those factors together, unless the efficacy is enough to create herd immunity it's going to be waves with not much differing total amount of cases.

You seem to be assuming that the disease will exhaust itself and run out of people to infect, but as the real world shows, that isn't generally how infectious diseases - especially ones this effective at escaping the immune system - work.

It's only meaningful to talk about the total number of cases up to a given point in time - if you're trying to talk about the total where the number of new infections permamently drops to 0 you're talking about circumstances that might apply to some newly-arising zoonotic diseases but decidedly does not apply to the disease we're talking about.

1

SnooPuppers1978 t1_j2wsv97 wrote

> You seem to be assuming that the disease will exhaust itself and run out of people to infect

For certain amount of time, hence the waves. There will be smaller amount of population still having the virus, until the virus mutates or immunity wanes enough after which it will start all over again.

After certain amount of time like a year or two years, the total cases amount would be similar in terms of magnitude. They won't be 10x based on 22% efficacy.

Because you were suggesting 7k vs 1 million which is different in magnitudes.

I'm suggesting that difference would probably be less than 2x after 2 years for example. And if I had to guess it would probably be something like 25% difference similarly, if we tried to make our model more comprehensive.

1

Immoralist86 t1_j2rnslb wrote

But also:

“Index cases with a history of prior SARS-CoV-2 infection (that is, reinfection) had a lower risk of transmitting to close contacts (23% (19–27%)) than index cases with no history of prior infection (33% (30–37%)”

“Prior SARS-CoV-2 infection was similarly associated with a 23% reduction (3–39%) in risk of transmission from the index case. Having both prior vaccination and SARS-CoV-2 infection was associated with a 40% (20–55%) reduction in risk of transmission by the index case, based on a linear combination of regression coefficients.”

“for every five additional weeks since last vaccine dose, SARS-CoV-2 breakthrough infections were 6% (2–11%) more likely to transmit infection to close contacts. We did not observe a statistically significant relationship between time since last SARS-CoV-2 infection and risk of transmission”

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[deleted] t1_j2s2x3r wrote

I’m thinking an about face to our national approach towards coronavirus is necessary. While prior infection or vaccination may reduce transmission, a healthy immune system in general is the real key. Avoiding processed food and all added sugars cannot be stressed enough.

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1

TTigerLilyx t1_j2t9nah wrote

Well that was an awkwardly long sentence.

1

FTBagginz t1_j3asuuk wrote

That’s wild when the reports came out and the cdc admitted knowing the vaccines weren’t going to stop the spread

0

mightcommentsometime t1_j3bm99r wrote

Only if you don't understand the bare bones basics of epidemiology.

No vaccine directly stops spread. Large groups of vaccinated people do because vaccines lower your susceptibility.

1

compaqdeskpro t1_j2rau3j wrote

"Helped to limit"? I'm extremely impressed. My whole life everyone told me its impossible to make a cold vaccine because of how much it mutates. Flu vaccines work but not 100%, as there are several strains you could have, so only the elderly were compelled. Covid was a flu that mutated more than usual, possibly because it was bioengineered, so common sense would tell you the vaccines don't work very well. The media even had to admit that previous vaccines don't work on the newest mutation. That common sense still seems to hold up, and the hysteria fell flat on its face.

−11

DuckQueue t1_j2s4rpe wrote

  1. Colds and flu have been around infecting humans for centuries or more, which means there is a huge amount of genetic variation to start with. That makes it a lot harder to create a vaccine which is highly effective against all their already-existing variations, which makes it easier for a variant to arise which escapes immune protection.

  2. COVID isn't an influenzavirus at all. FFS, influenza is a segmented negative-sense RNA virus while coronavirus is a positive-sense, non-segmented RNA virus.

  3. Not all viruses are equivalent in terms of genetic diversity and mutation rates.

  4. COVID wasn't bioengineered

  5. The original COVID vaccines are less effective against the newest strains, not ineffective.

Basically, almost everything you said was completely wrong.

8

[deleted] t1_j2opky9 wrote

[removed]

−49

Jazzlike-Drop23 t1_j2poshu wrote

Did you read the article? I thought not.

It also states that prior infection reduces transmission by a very similar amount.

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H1tm4n t1_j2pt91f wrote

So benefit for the vaccinated is what now?

−23

Jazzlike-Drop23 t1_j2pudf6 wrote

For healthy people, not a lot I believe.

For older and vulnerable people, a reduced chance of severe illness or death.

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Bearpoints t1_j2qaozd wrote

Vaccination has always been about slowing the spread over the general population. The more people vaccinated, the slower the spread, and the less strain on the health system. This allows the health system to be better equipped to treat those who are the moat vulnerable. This is exactly why the season flu vaccination is encouraged.

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thezander8 t1_j2qchu5 wrote

uhhh that you get the about the same benefit as prior infection (according to this study) without having to live through the worst flu of your life while unvaccinated against it? (IF you live.)

Getting protection against COVID without actually getting COVID is a pretty clear benefit.

10

SlowerThanLightSpeed t1_j2q0oss wrote

Though you may find that this analogy isn't an equivalence (that's how words that aren't synonyms work)... Think of it this way:

The goal is to avoid getting pregnant.

One way to do that is to get pregnant (during which time you can no longer conceive). Ha ha! While pregnant you can't get pregnant!

The other way is to take the pill.

8

redruggles5 t1_j2rc6pe wrote

You could get Guillan-Barré Syndrome and be paralyzed for life if you’re lucky! Bring on the sheep votes.

−8

Thekilldevilhill t1_j2rd1t3 wrote

You can also get it from the virus itself, or influenza, campylobacter or pretty much anything that triggers your immune system. Also, pretty much everyone recovers and fatal cases or complete paralysis is rare.

But don't let these facts get in the way of your agenda.

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LA_Lions t1_j2pojad wrote

The sheer amount of misinformation that is widely spread is what causes them to feel like they have to keep proving the obvious to everyone. Showing evidence backed information is the only (non-violent) way to combat misinformation, conspiracy theories, and lies about vaccines and boosters.

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Jazzlike-Drop23 t1_j2ppg5c wrote

Doesn't work though. The conspiracy lot think the science is just made up.

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LA_Lions t1_j2pq0zl wrote

I agree. The researchers and scientists don’t seem to have an answer for what we are to do if a third of the population are beyond help.

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calcifornication t1_j2qa2vu wrote

Yes I agree that it is very strange that the science sub posts currently relevant research papers published in major journals.

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