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Comment by timr | Hacker News Reader

There has been a lot of (IMHO unsupported) speculation that the almost complete eradication of influenza in 2020 was due to competitive inhibition from SARS-CoV2. However, data I've seen suggests that rhinovirus is still circulating at its usual rate [1].

If it's true that rhinovirus is such a potent inhibitor of SARS-CoV2, at the very least, the interplay between SARS-CoV2 and other respiratory viruses is non-trivial, and doesn't explain the complete suppression of influenza. Any simple hypothesis involving "competitive inhibition" is likely to be wrong.

The fact that rhinovirus continues to circulate so widely should also make people at least question the dominant narrative concerning masks and respiratory viruses. But I digress...

[1] https://syndromictrends.com/metric/panel/rp/percent_positivi...

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If I'm reading that chart right, it is the percentage of sicknesses caused by each virus type, not the rate of sickness in the population. So we don't have information in this chart on the absolute prevalence. The change in relative rates may suggest which measures are relatively more effective on different viruses, but doesn't help us analyze the effectiveness of the current narrative.

On the research presented in the original article, what predicted implications would this research have had for March 2020? I thought 2020 seemed like a fairly average year for colds up until March, when COVID spiked. Is that suggesting this benefit/effect weaker in a population than the test measures in a individual, or just that March could have been much worse across the world? (for example, was hypothetically Italy having a very low rate of colds at the time?)

> If I'm reading that chart right, it is the percentage of sicknesses caused by each virus type, not the rate of sickness in the population. So we don't have information in this chart on the absolute prevalence. The change in relative rates may suggest which measures are relatively more effective on different viruses, but doesn't help us analyze the effectiveness of the current narrative.

That's exactly correct, and instead the poster is continuously misinterpreting a rate as a fixed quantity.

> the poster is continuously misinterpreting a rate as a fixed quantity.

I am not. It is a measurement of the percentage of samples in a surveillance network, positive for each pathogen. Here is the methods paper:

https://publichealth.jmir.org/2018/3/e59/

Here is the relevant section:

> To calculate the pathogen detection rate (as displayed in Figure 2 [second data view] and on the Trend website), we compute the rate for each organism at each institution as a centered 3-week moving average. To adjust for the capacity differences between sites, a national aggregate is calculated as the unweighted average of individual site rates. Only data from sites contributing more than 30 tests per week is included to avoid noise from small numbers of tests. Because the calculation of pathogen detection rate includes results from patients with multiple detections, the detection rate for all organisms can, in theory, add up to greater than one. In practice, this does not occur.

The data says exactly what I described: influenza prevalence has declined to nearly zero. Rhinovirus has continued to circulate at normal levels.

I think this will be my final reply on this topic. I appreciate you posting links to support your view, but I don't believe you're taking time to reflect on what I'm saying.

> The fact that rhinovirus continues to circulate so widely

This statement cannot be made from the link you posted. This is a rate. A frequency rate among sampled data. However it does not track the number of samples occurring. No amount of averaging can cover that. As a result, a person cannot make a conclusion to support the above statement on frequency of circulation of rhinovirus.

> Rhinovirus has continued to circulate at normal levels.

This statement is not supported by the data you list. The description you provide above even supports my argument. They are adjusting for capacity differences, but are still reporting a rate.

This is the key statement they make supporting my point:

> To adjust for the capacity differences between sites, a national aggregate is calculated as the unweighted average of individual site rates.

They are averaging rates of infection. You cannot use that to make the statement that you're making that "Rhinovirus has continued to circulate at normal levels."

This is all very well understood stats. The only thing I can suggest at this point is to do some background reading on statistics, sampling and statistical inference.

I'm trying to both be cordial about it, as you have been cordial in your tone and appear to have an earnest interest in this topic - but also trying to make clear that you are unintentionally spreading false information.

You are doing something that statistics 101 makes clear is invalid to do. I'm not certain how else to put it. My only request is that you refrain from repeatedly posting. It is incorrect information, and it turns out it isn't just an invalid conclusion, it's actually the opposite of what is occurring.

Keep the enthusiasm, but just understand the math/stats a bit more.

> This statement cannot be made from the link you posted. This is a rate. A frequency rate among sampled data. However it does not track the number of samples occurring.

It does. Click the link [1]. Figure 2 [2] shows the number of samples. They explain it clearly:

> The FilmArray RP test utilization rate (TUR) metric is defined as the non-normalized number of RP patient test results generated each week across the Trend sites (computed as a centered 3-week moving average).

"Non-normalized number of RP patient test results" => count of samples

They calculate positive rates for each pathogen, using the the number of samples as the denominator.

> They are averaging rates of infection.

They are not. They are computing an unweighted average rate across sites. Look at figure 2. Read the text again.

This surveillance data is showing you that the rate of samples positive for rhinovirus in their network is ~unchanged. The rate of influenza has disproportionately declined. There is nothing wrong with the data.

> Keep the enthusiasm, but just understand the math/stats a bit more.

Thanks for the advice.

[1] https://publichealth.jmir.org/2018/3/e59/

[2] https://publichealth.jmir.org/2018/3/e59/#figure2

Your statements seem mostly correct to me, but may be read in a misleading manner to imply the prevalence of colds is similar this year to past years. That data also does exist somewhere (since it was used to compute the plot in your first link), it just isn’t shown in that particular plot. From comparison to the paper, we seem to only have plot 1 for 2020, and not plot 2. Plot 1 (rates) showed the relative effects, but we need a link for plot 2 (counts) for 2020 before we can make statements about the absolute effects.

Hope that helps clear up the misunderstanding. And if you have a link to the counts data also, do share!

If that's exactly correct why doesn't it always add up to 100%?

I’ve only spent a couple minutes looking at the plot, but it appears they don’t know why half the patients are showing symptoms in a normal year. This year, something new that they didn’t add to their test aggregation—I assume COVID—increased the “other” category and decreased the “flu” category. But note that means ~80% of the data is categorized as missing last year, so extrapolate this observation at your own risk.

> doesn't explain the complete suppression of influenza

Influenza isn’t infective enough to spread during the summer months anyway (i.e. it is completely suppressed), unlike rhinoviruses, so it’s easily most plausible that a few additional hygiene measures have suppressed influenza further.

The data I linked to covers the winter -- the same "hygiene measures" were in place in the winter, and clearly affecting both viruses differently.

If you're saying that rhinoviruses are more contagious than the flu because they're less seasonal...there's really no evidence to support that. They're more-or-less the same [1]. It's possible that influenza is more sensitive to heat, light, etc.

My point is, the story isn't likely to be simple or reductionist.

[1] https://www.medrxiv.org/content/10.1101/2020.02.04.20020404v...

This covers the bases. There isn't a huge mystery here, although there are some unknowns that need more research.

https://www.nature.com/articles/d41586-020-03519-3

R0 rates are just an indicative estimates. They don't account for different modes or vectors of transmission.

So it's not a given that mask wearing, social distancing, temperature, UV, humidity, and hand washing would necessarily all have identical effects on Covid, flu, and the various virus families that cause colds.

That Nature story is a great example of the speculation I was talking about in my first post: a sample of "experts", chosen by reporters, repeating opinions.

There's a pretty decent coverage of the level of uncertainty involved, but the reporter still can't resist the urge of "crafting a narrative" that bypasses the uncertainty. For example:

> In May...when some of the strictest lockdowns were in place, health workers noted an abrupt and early halt to the 2019–20 flu season in the Northern Hemisphere. That might partly have been an artefact caused by fewer people coming to a clinic for testing, experts say, but it was also attributable to the effectiveness of policies such as social distancing.

Pretty definitive statement, there. But not even two paragraphs later:

> “Some South American countries haven’t done such a good job controlling COVID, but even there flu is low,” says virologist Richard Webby at St Jude’s hospital in Memphis, Tennessee. “I don’t think we can put it all down to mask wearing and social distancing.” He suspects that the dearth of international travel played a part.

So...yeah. We don't know the answer. The article makes it sound like we do. The headline and photo captions really makes it sound like we know.

Reporters are constantly putting their thumb on the scale by crafting editorially convenient narratives. Richard Webby's opinion doesn't properly emphasize the impact of of social distancing? Bury it under a vaguely definitive-sounding lede, and quote some other "expert" who does agree.

</rant>

You haven't mentioned social behavioral change in your speculation about the decimated 2020-2021 flu season. I'd wager that has a very large part in why the flu hasn't spread: everyone is socially distanced, remote, masked, extra hygienic, and extra aware of illness.

I didn't mention it because it's not addressed by this article, which is specifically about competitive inhibition.

That said, if you're going to claim that all of these things we have done have eliminated the flu, you should take at least a few moments to reflect on the fact that they have done ~nothing to rhinovirus.

Flu has an R0 of about 1.3, Rhinovirus has an R0 of around 2.7, and Covid is estimated to have an R0 of 2.7 or higher. So it makes sense that the measures we have taken have stopped the flu but not stopped covid or rhinovirus.

Sources: https://www.qps.com/2020/10/05/covid-19-versus-the-seasonal-... https://www.sciencedirect.com/science/article/pii/S246804271... https://www.bmj.com/content/369/bmj.m1891

You are leaning way too hard on point estimates of R0. The way people estimate R0 is noisy, and the error bars on these estimates are significant. It's fairly pointless to take any two papers and compare the values as if they're precise.

This literature review has estimates of R0 for flu running from 1.06-3.4, and rhinovirus running from 1.2-1.83:

https://www.medrxiv.org/content/10.1101/2020.02.04.20020404v...

Given the uncertainties involved, these ranges are effectively identical, with flu maybe being a bit more contagious.

OK I've got a better idea:

In the particular conditions we created in 2020, the Rhinovirus was better able to spread than the Flu. Why?

Because people were on the lookout for fever (and other things like continuous cough etc). Flu causes fever, and anyone who got a fever and was sensibly-minded would self isolate at least for a few days until they got test results or until symptoms abated. Whereas Rhinovirus is much less likely to cause a fever, so people twig that they've 'just got a cold' and carry on going about their day.

Especially for schoolkids - if they've got a fever, they're kept at home. If they've just got a snotty nose then they're likely to still go to school.

So Rhiniovirus was able to fly under the radar whereas Flu wasn't.

Could be. Covid is certainly more flu-like than rhinovirus-like. Kids were also not in school, and kids are historically a big spreader of influenza.

I generally think people look for "fancy" explanations for the trends, when simpler explanations (i.e. people weren't going to the doctor) work just as well.

> That said, if you're going to claim that all of these things we have done have eliminated the flu, you should take at least a few moments to reflect on the fact that they have done ~nothing to rhinovirus.

Why do you keep saying these measures have done nothing to rhinovirus?

The link you've shared does not support that. It shows relative percentages - and you're confusing that for absolute infection counts.

Unless you also believe that 60% of the population has a stomach virus on a daily basis (data from their other chart).

> Why do you keep saying these measures have done nothing to rhinovirus?

Because they haven't.

> The link you've shared does not support that. It shows relative percentages - and you're confusing that for absolute infection counts.

I am not confusing it. It shows you the percentage of samples they test that come up positive for rhinovirus (and other things. They test for all of the things listed, in parallel.)

Influenza A & B, RSV, and some other viruses have been virtually eliminated across their sampled population. The rate has dropped to zero. Rhinovirus has not -- the rate of detection is unchanged.

Again, you're confusing percentages.

To use some simplified numbers to explain it - consider that normally 100,000 people are infected with some form of respiratory virus on a daily, basis and 20% of those are rhinoviruses, then that means there are 20,000 daily rhinovirus infections. And let's also say that strains of influenza are another 20% and 20,000/day.

Now what is happening, is in a covid world, due to masks and distancing, the number of people infected on a daily basis drops from 100,000 to 10,000. Rhinoviruses are sill 20% of that, but they are now down to 2,000. Masks and social distancing has had a drastic affect on them.

Influenza drops down to only 2% so only 200 cases daily. Masks and distancing have an even more drastic effect in influenza.

As a result, we're seeing exactly the graph you've linked.

Rhinovirus is 20% rate, but of a much smaller pie. And you're mistaking that as masks and distancing having little or no effect.

I am not "confusing percentages". You (now) agree with me on what the data says, you just don't like how it fits in with your theory.

> Now what is happening, is in a covid world, due to masks and distancing, the number of people infected on a daily basis drops from 100,000 to 10,000. Rhinoviruses are sill 20% of that, but they are now down to 2,000....Influenza drops down to only 2% so only 200 cases daily. Masks and distancing have an even more drastic effect in influenza.

Yes, I understand your hypothesis: masks make influenza go down to almost 0, but somehow rhinovirus ends up at exactly the same percentage as it was before. In other words: masks work exceptionally well for flu, don't work at all for rhinovirus.

This is a theory. It is...implausible...but if you want to believe it explains the patterns in the data, you're certainly welcome to do so.

everyone is socially distanced, remote, masked, extra hygienic, and extra aware of illness.

Flu has been eradicated by lockdown, but lockdown must continue because COVID has not. That appears to be the policy right now.

question the dominant narrative concerning masks and respiratory viruses

My limited understanding of that narrative is that COVID19/SARS-CoV-2 needs larger droplets to spread, and thus common masks help. But other viruses may be able to spread further as aerosols and last longer on surfaces, thus common/non-fine-particulate-filtering masks may not help.

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