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Comment by nmca | Hacker News Reader

Could you elaborate?

>Overall, our findings indicate that a large proportion of COVID-19 infections were undocumented prior to the implementation of travel restrictions and other heightened control measures in China on 23 January, and that a large proportion of the total force of infection was mediated through these undocumented infections (Table 1). This high proportion of undocumented infections, many of whom were likely not severely symptomatic, appears to have facilitated the rapid spread of the virus throughout China. Indeed, suppression of the infectiousness of these undocumented cases in model simulations reduces the total number of documented cases and the overall spread of SARS-CoV2

This paper is about undetected carriers spreading SARS-CoV2 across China prior to the Jan 23 lockdown. It does not imply that 86% of all total infections that we see currently are undocumented, it only reflects the relatively narrow testing that was happening prior to Jan 23 (likely only the severe cases).

After Jan 23, China expanded its testing much more broadly, and other countries (such as South Korea) have done so as well. You should not take this paper to mean that the actual number of cases for these countries is larger by a factor of 1/(1-0.86).

Thank you, in parallel to this response I looked at the paper in more detail and updated the original comment. A shame, I was briefly optimistic about the news.

There is a strong desire by many (particularly on HN) to find any sort of evidence to support the contrarian notion that "Hey, it's not that big of a deal, everybody else is just overreacting!"

We should be conscious of this desire, and be careful assessing new evidence that comports with this notion.

This is a pretty insane take. Asking exploratory questions is not contrarian, it's scientific. Beyond that, HN has been oscillating between doomsdaying about CoV19 and calling it no big deal for weeks now.

But this isn't a bad thing -- having strong opinions and questioning the veracity of data is key to having informed, strong opinions.

Nothing scientific about misreading a scientific paper and drawing conclusions that aren't there. HN has a well-known contrarian bias that tends to manifest as a "we know better than the so-called experts" hivemind.

To misread a scientific paper you have to actually read it. Data analysis is a difficult field, and there are a number of studies where the data presented tells a completely different story than the scientists presenting it. Science is political and scientists are fallible. Confirmation bias isn't a plebian problem. Reading for your own understanding and asking questions is a necessary part of both scientific accountability and personal growth!

And, hearteningly, we see that OP has edited his comment to reflect the knowledge you passed along and has a better understanding of the situation. Inquiry at work.

Great. This is then one success story among many stories of failure to understand the scientific literature. Even now there is another story on the front page of HN where armchair epidemiologists are proclaiming in the comment section that this is no worse than H1N1. This shit is exhausting.

Could someone explain the difference between SARS-CoV2 and COVID-19? Is the former the virus and the latter the infection?

Correct.

There was a presentation that was posted here today which explains this nicely.

https://drive.google.com/file/d/1DqfSnlaW6N3GBc5YKyBOCGPfdqO...

If South Korea and the UK, with fairly significant testing, have both found ~3% positives, then even if you assume the people tested were 100x more likely than the general population to have the disease, then in South Korea you'd have around 15k cases (about 2x reported) and in the UK around 19k (around 13x reported). If you assume the tested were only 10x more likely to be infected, those numbers scale correspondingly to 150k (20x reported) and 190k (130x reported).

The test only finds active infections, note.

Can you test negative and still be contagious? That would obviously make the potential ratio much larger.

As I understand it, yes. The probability of that, I'm not sure. This is where I found information about the nuanced properties of the test: https://www.youtube.com/watch?v=oGiOi7eV05g It's from there that I realized the test doesn't seem to be intended to be used in the way most people think -- it's supposed to be a "if a patient arrives in hospital with pneumonia, do this to tell if they have covid" tool, not a "if some random person wonders if they have it or not, run this test" tool.

Ah, you imply that the underreporting rate fell over time and the headline number is from before the travel ban.

Precisely

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