Show HN: Time Series of CDC's Covid-19 Vaccine Breakthrough Case Reporting | Hacker News Reader

Show HN: Time Series of CDC's Covid-19 Vaccine Breakthrough Case Reporting

7 pointsnanis8 comments

The CDC have been providing "COVID-19 Vaccine Breakthrough Case Investigation and Reporting"[1] information for points in time at close to weekly intervals. Every update erases the previous information and there doesn't seem to be an easily accessible table of these data. Snapshots of the page can be found on archive.today[2] and I have saved both those and some recent manually downloaded copies from cdc.gov.

Because copying & pasting by hand is error-prone, I wrote some code to extract the bits and pieces.

The repo is `nanis/covid19-breakthrough` on GitHub[3]. Snapshots are in the `snapshots` directory. There is also a CSV containing the time series of reported numbers of non-fatal hospitalizations and deaths from COVID-19 among the fully vaccinated[4].

`out/chart.html` shows the time series of fully vaccinated population in millions, hospitalizations and deaths among the fully vaccinated per 100,000 fully vaccinated individuals. You can view it locally by running a simple local web server[5]. There is a copy online[6].

[1]: https://www.cdc.gov/vaccines/covid-19/health-departments/breakthrough-cases.html

[2]: https://archive.today/https://www.cdc.gov/vaccines/covid-19/health-departments/breakthrough-cases.html

[3]: https://github.com/nanis/covid19-breakthrough

[4]: https://github.com/nanis/covid19-breakthrough/blob/11bb7c7495f7c417504971ab8c65aa1f5921baa1/out/2021-09-10.csv

[5]: https://gist.github.com/willurd/5720255

[6]: https://www.covid2020.icu/vaccine-breakthrough/

Interesting work! So of course, I suggest new work for you. :) It would be interesting to put a line for the general, or even non-vaccinated population, so that the growth rate among the vaccinated population would have something to compare to. Perhaps the graph could be just below the existing one, with the same x-axis. But again, thanks for making this, it is interesting!

Screencaps of the outputs please!

edit: Actually I see you posted on your twitter some screenshots, thanks!

edit2: Care to provide a summary of what you see in the data? I see hosptilizations/deaths are on the rise but is it just in proportion to the number of people vaccinated?

Screenshot of the chart: https://pbs.twimg.com/media/E-86fSrXIAgmddQ?format=png&name=...

Screenshot of Biden's claim of 1/160,000 hospitalization rate among fully vaccinated: https://pbs.twimg.com/media/E-4NQBFWEAMzATQ?format=png&name=...

Current rate of known non-fatal hospitalization from COVID-19 among the fully vaccinated is 5.1/100,000 which is 8 times the rate Biden mentioned. It is also 3 times what it was on 6/1.

Current rate of known deaths from COVID-19 among the fully vaccinated is 1.2/100,000. Biden did not make a claim about that number. However, the fatality rate is 4 times what it was on 6/1.

Therefore, known hospitalizations and deaths from COVID-19 among the fully vaccinated is rising faster than the current number of fully vaccinated individuals.

However, this is hard to interpret because there is a lag between arriving at "fully vaccinated" status and getting infected. Then, there is another lag before one might be hospitalized. Then, there is another lag before one might die.

From the way the rates have been rising, it seems to me we have not arrived at a point where we can deduce a decent guesstimate of real life probability of hospitalization and death among fully vaccinated. It seems we'll be lucky to have the hospitalization rate stabilize around 1/10,000 and death rate stabilize around 3/100,000.

Note the phase3 trials lasted about 5-6 months[1,2] and they did not enroll a lot of people at risk. Now, it seems like, there is consensus that whatever protection the vaccines confer doesn't last more than five or so months past achievement of "fully vaccinated" status.

As for being able to compare with "unvaccinated", we need proper data for that, but there is not much out there.

Statements like "98% of hospitalizations since January 1 were among the unvaccinated" do not mean anything as the composition of the population is not constant lumping everything together removes information needed to properly evaluate what's happening.

[1]: https://www.pfizer.com/news/press-release/press-release-deta...

[2]: https://www.npr.org/sections/health-shots/2021/02/19/9691430...

Data from the UK can help with the decent guesstimate you are looking for. See https://assets.publishing.service.gov.uk/government/uploads/... pages 15--17. (The rest of the report is interesting too.)

The probabilities in the UK are clearly marked as probabilities per unit time, where the unit time appears to be four weeks. In contrast, it appears that the CDC data is cumulative since the Big Bang, which I think is less useful to your purpose.

> Data from the UK can help

Thank you for the link. This is actually very good & sober analysis.

> is cumulative since the Big Bang, which I think is less useful to your purpose.

In a Law of Large Numbers sense, if there is a stable probability, we might converge to it ... except that there may not be enough time for convergence before boosters.

> if there is a stable probability, we might converge to it

Yeah, that's the thing I can't figure out from the literature. For example, people say that vaccine X is 90% effective. This means that they ran two groups for some number of weeks, and observed one tenth of infections in one group vs. the other. But what does this mean in terms of individual probabilities? Assume for simplicity that the vaccine immunity lasts forever without decaying. There are still two extreme possibilities consistent with the data, as well as multiple intermediate options. In one extreme, the vaccine sets an immunity bit in each individual, and the unlucky ones will get infected when exposed. In the other extreme, the vaccine somehow increases everybody's activation energy for infection so that, under normal conditions, the probability that an exposure causes an infection is reduced by a factor of 10. In the former case, the steady state is that 10% of the population gets infected eventually, and that's it. In the latter case, you keep going forever with infections per unit time being 10% of what they used to be.

It seems more like vaccination reduces the amount of time it takes your immune system to react once it sees the infection (presumably because it already knows how to make antibodies and doesn't need to evolve them, just start producing again). Therefore, some people's immune systems will kick in and squash it so fast that they never realize they are infected, whereas others will realize it, and a few will succumb to it.

Still better than NOT having had the vaccine, but from what Israel tells us not as good as having had (and survived unscathed) the actual virus in a previous variant. Which, really, does not seem all that surprising. The vaccine has only one target from the virus for the immune system to evolve antibodies against; the actual virus has many more.

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