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Reading the graph posted, you may think we stopped tracking the flu. However, it's not clear yet whether that is the case, and the charts from 2019 show that.
Here are the charts for 2019 and 2020 in the US*:
(Note the axes are on different time scales unfortunately).
They are very similar with two major exceptions.
1. Week 13, about March 23rd, there is a dip lower, presumably due to the lock downs.
2. There was no activity throughout this spring and summer, but that's typically the case as the 2019 chart shows. 2020 is even lower (virtually no cases). While this could be due to lack of reporting, it could also be due to social distancing and masking.
We are currently in Week 44 of 2020. During week 44 of 2019 cases began to uptick slightly and then increased parabolically into the winter. We should expect the same in 2020. And this will be how we really know if flu testing is suppressed. Anyone claiming anything otherwise is speculating.
Anecdotally, my sister caught a bug recently that tested negative for COVID, and the physician suspected the flu. However, he couldn't test for flu since there was no capacity for flu testing.
Source:
https://apps.who.int/flumart/Default?ReportNo=7
Note the different horizontal axes been the graphs. The top one goes back up after week 43/44 which is about where the bottom one ends.
I know your text describes this but it's easy to look at the graphs and miss!
I just updated my comment to clarify too. Unfortunately, the WHO only plots data for weeks that have occurred, so there's no way to extend match the two axes.
I was about to post the same but _both_ horizontal and vertical axes are different scales.
In short: it is too earlier for 2020 (week 43 is almost nothing in 2019)
The 2019 graph shows nicely that the 2019/2020 flu seasons saw a lot of Influenza B cases, which was not as much present in 2018/2019. AFAIK Influenza B has always been the more severe and deadly type of the flu and to skeptics like myself this underlines even more the suspicion that we have falsly attributed a lot of deaths in our last Winter to COVID when it might have been the flu in many cases. Previous studies have already proven that when a patient had tested positive for the flu and COVID that all these cases have been only counted as COVID deaths. Things like this make it problematic to build trust in the wider population and ask people to follow silly rules when there is so much ground for mistrust in the severity of COVID.
There were virtually no deaths attributed to COVID last winter - everything started in March, past the influenza peak.
This winter the number of deaths from COVID will be an order of magnitude higher than the deaths from flu on an average tear. So even if we attributed every sobgle death from flu to covid, it wouldn’t change the overall picture on Covid really.
Testing didn't really start until March, so you can't possibly know the answer to that.
We're already back to average death levels (maybe even below average if the recent provisional numbers hold up):
https://www.cdc.gov/nchs/nvss/vsrr/covid19/index.htm
Click "percent of expected deaths" column to see.
We thought Covid was an order of magnitude deadlier than the flu, but it's looking more and more like that's not the case. Covid may have hit a large population of vulnerable people with weak immune systems at once, and is currently becoming less deadly as it spreads among younger, healthier populations.
Covid had the element of surprise in the spring, for both immune systems and healthcare systems. Going forward, unless it mutates into some hellish form, it's not likely to continue.
I'd be a little careful with that chart. I was working with the raw data provided on this page:
https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm
, and the CDC warns that even the data going back into August may be incomplete. I'd assume this data comes with the same caveat, so we may well see these numbers increase the reporting comes in.
Edit: from the asterisk on the page you linked:
"*Data during this period are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death."
I hope you are right.
But from your link : is important to note that it can take several weeks for death records to be submitted to National Center for Health Statistics (NCHS), processed, coded, and tabulated. Therefore, the data shown on this page may be incomplete, and will likely not include all deaths that occurred during a given time period, especially for the more recent time periods.
why do you say "silly rules"?
I grant that there is, in principle, a possibility that health authorities are wrong and that these rules are not necessary because the problem has been inflated as you said.
Also, there is the possibility that, in principle, the rules themselves are ineffective.
However, if the rules are wrong, that's even more so a problem of COVID is a real problem.
If COVID has been overinflated, then the problem is not that the rules are silly but that they are not necessary (and thus their negative sideffects are worse than the benefits).
Colouring the rules themselves as "silly" only reveals a bias in your argument and probably will reduce the effectiveness in communicating your point to those in a different echo chamber.
> Is COVID a real problem?
Not to the vast majority in every age category.
I personally had COVID and it was less severe than the last time I had the flu, so why should I treat COVID different than the flu or care at all?
> Are the current rules effective?
Not in liberal democracies, that's what the data shows. If you live in an authoritarian regime where people are willing to completely give up their lives then it is effective, but at that point you might argue are they still living or just existing like zombies? In all Western nations it didn't matter if one took more stringent or more lenient actions, everyone had a first wave, everyone has a second wave. Nobody invented a testing regime, a track and trace regime which allows us to live normally, so what's the point in taking those measures when they didn't prevent a second wave for anyone?
> Colouring the rules themselves as "silly" only reveals a bias in your argument
Fair point. Young generations have been taught for many decades now that we are not in this world together. Nobody pays off your debt. Nobody else will look after your health if you don't do it yourself. Nobody will come and provide you shelter when you become homeless. Look at the most woke state in the USA - California - every woke person walks past homeless people and couldn't are less. People who claim we are in this or in anything else together are selfish afraid human beings who want to control the population out of their own fear. The notion that we are in this together is wrong and that is the education that young people have been given for many years now. This is how it was in the last economic crisis, this is how it will be in this one too. So as far as I'm concerned COVID was nothing to me and my wife and it is not a threat to our family, so why should we care any longer about this? Other people's problems is not our problem. Just like every woke Californian walks past homeless people and doesn't care, I walk past the COVID death statistics and equally don't care. Why am I the villain now?
Everyone with the 'I've got mine' mentality is the villain. I expect that reasoning from my 3 year old son, but my 5 yo daughter has already moved passed it. That an entire nation basis it's philosophy on that of a toddler is... Disturbing.
I appreciate that you elaborated on your opinion and I believe many of your points are valid. COVID is not a big threat to you and your family (based on my assumptions about you which could very well be wrong). Neither is it a big threat to me, 30 year old, healthy, single male living in Germany.
However, some of your assertions are not true. The COVID waves were vastly different in different countries across Europe, and despite Germany having elevated cases again and a second "Lockdown" the situation is nowhere near what it was in May. No constant Sirens from Ambulances (where I live), no overcrowded ICUs (some exceptions). Similarly, the lockdown proposed now is more lenient than a couple of months ago.
There is a definite talking point to be made about which rules are more effective than others and I personally would be more lenient than what my government proposes, but all in all we fared fairly well in comparison with our neighboring countries.
One point you made about a generation only caring about itself I can falsify immediately: The only reason why I am missing a basketball game with friends tonight is because I had an encounter with a positive covid case (my cousin). While I'm >99% sure I'm COVID free, I opted to argue on the internet tonight as some of my basketball peers are in a risk group (>60).
You're not the villain. I don't know you.
> Young generations have been taught for many decades now that we are not in this world together. Nobody pays off your debt. Nobody else will look after your health if you don't do it yourself. Nobody will come and provide you shelter when you become homeless
You picked some extreme examples. We are in this world together. It's called a society. It's unfair, it's cruel,
it's skewed, but to imply everybody is completely on their own is disillusioned. Humans cooperate. Not always willingly, but effectively. This is how we prospered for millennia and occupied every corner of the globe. You're sharing your thoughts now thanks to cooperative work by countless people who built the information age.
Thinking you can lift yourself up from your bootstraps and only think for yourself is ignoring how interconnected the society where you live is.
Pointing out extreme cases where people put a limit to their compassion doesn't change the fact that you do owe your successes in your life also to the effort of others you have never met.
The title is very catchy and misleading. The WHO's virus circulation graph and the text did NOT describe it as "Completely Disappeared in 2020." It did reporting having seen very minuscule amount of flu virus detected, instead.
https://www.who.int/influenza/gisrs_laboratory/updates/flune...
Edit: now the title has been updated, it's more accurate
I mean, it certainly looks lower, but if you look at the same time in 2019, it was very low then as well. If it still looks this low in 10 weeks, I'll be impressed.
The actual WHO Influenza update [1] rightfully adds a disclaimer:
The current influenza surveillance data should be interpreted with caution as the ongoing COVID-19 pandemic have influenced to varying extents health seeking behaviours, staffing/routines in sentinel sites, as well as testing priorities and capacities in Member States. The various hygiene and physical distancing measures implemented by Member States to reduce SARS-CoV-2 virus transmission have likely played a role in reducing influenza virus transmission.
But also:
Globally, despite continued or even increased testing for influenza in some countries influenza activity remained at lower levels than expected for this time of the year.
[1]:
https://www.who.int/influenza/surveillance_monitoring/update...
I can say that for march to may in France everybody that died with COVID like symptoms was counted as a COVID fatality since we didn't have enough tests.
So it could very well be that many people died of the flu but were counted as COVID, we'll never know.
But this article is using flu-tests to test for specimens of the flu.
Why would a lack of COVID tests mess up the flu-tests that they're using?
He’s saying the published stats could be off because of a bias toward diagnosing flu deaths as COVID deaths without testing for COVID. That is, the suggestion seems to me to be that the sampling methodology may underrepresent flu. I don’t know that I agree, but I suppose it’s possible.
The idea that 172 different strains of the Flu virus can be accurately detected and tracked, but suddenly adding a 173rd virus (COVID19) to the mix would mess up their survey seems a bit ridiculous to me.
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These flu-surveys are extremely important for designing next year's flu vaccine. There are hundreds, if not thousands, of flu strains, since that virus is constantly evolving. But the flu vaccine can only protect against 5ish strains.
Some strains (in particular: Flu TypeA) are known to spread much faster than others (ie: Flu TypeC). So even if TypeC is more common, maybe Flu TypeA is prioritized because of the risk of it becoming a pandemic a year out.
They didn't perform flu tests on all "covid" deaths.
But the vast majority of samples are coming from people who will ultimately survive, but who have respiratory illness. Anyhow, scientists have considered testing bias.
https://www.cdc.gov/mmwr/volumes/69/wr/pdfs/mm6937a6-H.pdf
“Initially, declines in influenza virus activity were attributed to decreased testing, because persons with respiratory symptoms were often preferentially referred for SARS-CoV-2 assessment and testing. However, renewed efforts by public health officials and clinicians to test samples for influenza resulted in adequate numbers tested and detection of little to no influenza virus.”
Most people don't die from flu, so that means it might be underrepresented by 0.1%.
If anything, there's less testing for flu because of covid. But nonetheless, this is sampling, not testing, the WHO performs consistent randomized sampling over time to keep the data meaningful. If they just were based on testing of reported flu cases the data would be heavily biased and basically useless in tracking the disease.
While testing for flu in the global sample is indeed down 21% compared to last year, positive cases are (currently) down 97%.
From their fortnightly report of 28 October 2019:
"data to FluNet for the time period from 30 September 2019 to 13 October 2019. The WHO GISRS laboratories tested more than 102881 specimens during that time period. 5005 were positive for influenza viruses"
And of 26 October 2020:
"...from 28 September 2020 to 11 October 2020. The WHO GISRS laboratories tested more than 81257 specimens during that time period. A total of 172 specimens were positive for influenza viruses"
This is completely irrelevant to the linked data.
how dare you :-)
Well, not _completely_:
"A total of 172 specimens were positive for influenza viruses, of which 108 (62.8%) were typed as influenza A and 64 (37.2%) as influenza B."
If you consult the previous years, the graph is the same.
The conclusion is not accurate.
About a month ago, I came down with an upper respiratory illness that felt like a severe flu. Covid nasal swab test was taken 24 hours after first symptoms appeared, and came back negative. Therefore I assumed it was flu.
However given the supposedly very low base rate of flu during the current season, is it more likely from a Bayesian perspective that the Covid test was a false negative?
The statement is not true at all.
On what do you base that?
This feels like a sensible conclusion. With borders closed and human to human contact relegated to only your closest family the whole annual mechanism for spreading flu (often season and triggered by air travel) goes to zero.
The title on HN is probably invented by the submitter, which is misleading and doesn‘t match the HN policy.
The title on the page: “Influenza: FluNet Summary 26 October 2020
Source: Laboratory confirmed data from the Global Influenza Surveillance and Response System (GISRS).”
It‘s also possible that those who would normally participate in the Global Influenza Surveillance and Response System just weren‘t able to do what was normally done in a non-pandemics year. The page doesn’t present any explanation.
Apologies, I re-phrased the title to be accurate.
A lot of people aren’t going to doctor’s offices right now. I personally know of 3 people with flu like symptoms who refused to go to the doctor for a variety of reasons, but one mentioned being a outcast for possibly having COVID 19.
Not sure why you are getting flagged. People not seeking medical assistance could be a reason why the sampling isn’t collecting any flu case.
Because they're not reported cases, but sampled cases, so whether reported goes up or down doesn't really matter as the sampling is consistent.
Saying that they are sampled cases doesn't mean anything about whether that number can be effected by other variables. Fewer tests would result in lower total positive results. So would people with flu symptoms actively avoiding being tested. Whether that's happening is an entirely valid question.
Check this link and have a blast[0]
This year, for example in the North America region, there have been 26,000 samples for weeks 35 and 36. Around 40 positives.
Last year, 27,000 in the same period. Around 1,000 positives.
As I said in multiple posts already, the WHO tries to keep consistent sampling to keep the data meaningful. It's literally their job.
[0]
https://apps.who.int/flumart/Default?ReportNo=12
But what the parent is saying is that lots of people who have fever may be self-isolating and not seeking medical assistance thinking it is Covid (as many of the symptoms are identical), whereas they may have seen a doctor a year before. In this case, the population that doctors see that have flu-like symptoms (as opposed to other symptoms) may be less. So it doesn't matter how many samples you take in that population, you would get less flu patients.
All speculation. But just a plausible explanation.
Again, they're independent variables.
WHO sites keep consistent testing for patients with respiratory symptoms. The same way that some flu cases may be "hidden" because people stay at home, likewise some flus that wouldn't be tested otherwise will because the patient thinks it's covid.
In any case if some hide because there's a pandemic or WW3, it doesn't matter because other patients will be part of the sample. If there's flu it will be seen, pandemic ongoing or not.
You may be interested in reading the Global Influenza Surveillance Manual[0]. Relevant info is in chapter 6, regarding sampling, in particular 6.2, in which it recommends against testing all and only those that seek medical assistance.
> Ad hoc or convenience sampling
> Sampling schemes that do not adhere to a pre-determined system are the easiest and least costly to implement but are also the most subject to bias. Differences in the health- seeking behavior of different groups and preconceived ideas about the risk of health- care providers can introduce unpredictable biases, consequently yielding patterns in the data that do not represent reality. While this approach may still yield data sufficient to identify transmission seasonality, and provide specimens for virological surveillance, it will not provide a reliable picture of the epidemiological characteristics of influenza or burden and should not be used if these are the objectives of the system.
In 6.4 it describes the systematic sampling strategies recommended, which remove the bias of the point you (and the other commenter) raised.
As described in 6.3, random sampling would be best, but also too expensive for tracking, and is only to be done by WHO sites performing some research where it would be needed.
https://www.who.int/influenza/resources/documents/INFSURVMAN...
Hoping for more deadly viruses to spread.
Which means there's a huge flu season in our future.
Classic sample bias; the hospitals were _closed_ in anticipation of everyone's weird fantasy of tens of thousands of people hooked up to breathing machines, so very little flu testing was actually done. All the indications were that it was set to be a terrible flu season[0]. Of course it could be that Corona-chan was circulating before it was broadly recognized, but that would be public health nitwits admitting their mistakes: something that doesn't seem to happen, ever.
[0]
https://time.com/5758953/flu-season-2019-2020/
81k is kind of a shitty sample size to make a sweeping worldwide judgement for 7+billion.
Next part, since the focus of 2020 was Covid testing, I'm pretty sure flu testing resources were lessened in the process, if not borderline ignored.
At what point was it okay to judge a population on 0.0000001157142% sample size?
While I'm not a fan of the WHO anymore, to be fair to them, where the hell do they say the flu disappeared? This title is disingenuous.
This is a common misunderstanding of the statistics. The sample size is more a function of the target variance and the confidence level, not as much on the overall population. 81k, if picked properly, would be sufficient for their purpose.
Properly selected, 1k is a sufficient sample size for any population.