Against the Corona Panic, Pt. VIII: The coronavirus transmission rate (“R0”) fell long before the Lockdown orders; What caused the decline?

For earlier entries “Against the Corona Panic,” see:
Parts One, Two, Three, Four, Five, Six, Seven,
Eight, Nine, Ten, Eleven, Twelve


The Corona-Panic (or, the Corona Mass Hysteria Event of 2020) continues, more narrative-driven and evidence-detached than ever.

Now that we are as far into it as we are, it’s (past) time to question our assumptions, to re-evaluate. After all, we can now compare theory and assumption with observed reality.

The previous post (Part VII, Sweden’s Vindication) compared the influential Neil Ferguson assumptions (that is, his guesstimates) of millions of deaths from the virus and millions more “swamped hospitals”-related deaths under a Swedish-style No-Lockdown approach, with the observed reality in No-Lockdown Sweden through late April.


The Transmission Rate Curve (“R0”) Revisited

In Part III, section 9, I included a graph which this post will examine in more detail, along with a parallel data-set on mobility, with the goal of trying to find possible causal factors behind the beginning of the decline:

Coronavirus R0 in Germany - March 6 to April 9

This graph is of “R-Naught” (R0), which is the transmission rate (or reproduction rate) of the virus, and was calculated by the Robert Koch Institute (RKI), Germany’s public health agency, in a report published April 23 (see Figure 5 [“Abb. 5”] in the report). (Graph also posted at Swiss Propaganda Research‘s “A Swiss Doctor on COVID19” series about this time.)

Before saying anything else, and if you don’t read any more of this post, notice that the transmission rate declined and fell below 1.0 before the Lockdown order.

The data from other countries look similar. Here is Switzerland’s:

Coronavirus R0 in Switzerland - March 2020

This post will focus on a close analysis of the German case, to see if we can find any proof of whether social-distancing, either personal-choice-based or government-mandated, “worked” in line with our assumptions, which is to say the mantra heard throughout March and April 2020. What kinds of changes in behavior are associated with the decline of the transmission rate?

The higher the line at a given time, the faster a virus is spreading at that time. A number above  3.0 means rapid spread is underway. A rate that falls and stays consistently below 1.0 signals the approaching decline and end of an epidemic, at least the transmission phase. With the “1.0 barrier” itself breached several days before the Lockdown order(s), and the peak predating it by as much as much as two weeks (!) in Germany’s case, questions need answers. What caused the decline?


The Social Distancing Manta

No assumption of Corona-Land was as influential, as central to the victory of the pro-Panic side, than the mantra of “social distancing” and its related sub-mantras and slogans (“flatten the curve;” “stop the spread”), enforced from above, with skeptics publicly shamed and dissidents including expert ones, suppressed.

Namely, the pro-Panic side has long said: “We need(ed) social distancing because it is (was) the ONLY way to cause the rate of transmission of this coronavirus to decline.”

This sounds reasonable.

Is it true? What is the evidence for it? Can we reconstruct evidence from March to corroborate it?

But first a word on what the Social Distancing Mantra implied, a key to the puzzle:

The Assumptions behind the Social Distancing mantra

Implied in the advocacy of social distancing by the pro-Panic side are two things:

  1.  (implied) “The virus is unusually dangerous and so requires special measures like this” (in fact, studies continue to come out concluding that the Wuhan Coronavirus is not unusually dangerous; e.g., the latest study coronavirus randomized population testing in Iran published in late April finds a ca. 0.1% fatality rate in a certain province in Iran, making it one of the latest to find a fatality rate somewhere in or near the 0.05% to 0.15% window, pointing again to Just the Flu‘s vindication);
  2. (implied) “To enforce social distancing and stop this Virus Apocalypse, we need extreme measures, mass shutdowns, mass unemployment if necessary, ruined businesses and bankruptcies if necessary, and ‘Lockdown’ policies.” In other words, the Lockdowns rested on the theory that only social distancing could reduce the spread and “flatten the curve,”and that therefore anything done in the interest of Social Distancing was, ipso facto, a good thing.

I have challenged the first assumption there in other posts, as have many others. All studies of which I am aware that have come out over the past six weeks have discredited the notion that the Wuhan Coronavirus and “COVID19” disease is unusually, alarmingly dangerous. The media-quoted rates of 3% or 5% deaths are consistently shown to be too high by at least 25x, even up to 75x too high, because of the statistical-fiasco (bad-data fiasco) involving the “denominator problem.”

In this post I want to look at the second assumption, but will go further and try to “strike the root” in the Thoreau sense:

Let’s dare to ask if the Social Distancing premise was right. What I mean is, Did the changes in behavior we have called “social distancing,” either voluntary or forced, cause the decline in the transmission rate? That is a basic assumption and ought to be asked, and all to few have asked it.

Next, if we find changes in behavior are associated with the transmission-rate decline, what was the role of government-mandated measures (including the extreme shutdowns, stay-at-home orders, and ‘lockdowns’), vs. voluntary measures?

We have some intriguing data on all of this and I think we have the outlines of an answer.


Extreme Social Distancing was not effective

The answer is that there is no evidence for the most extreme “lockdown”-type measures taken being in any way useful, as will be demonstrated in the rest of this post but as is readily visible from the reconstructed R0 transmission-rate graphs, such as the two posted above.

As for voluntary measures: There is, surprisingly, no evidence that even these are associated with the “turning of the ride” and the beginning of the decline in the transmission rate, at least in Germany.

We are left with the surprising conclusion that the epidemic appears to have been running through the regular cycle for a flu-virus, beginning to decline “on its own” (as it were) irrespective of government measures imposed (shutdowns) and perhaps even of the major changes in public behavior that predated the shutdown/lockdown orders.

If true, this undermines a very central premise of the pro-Panic side.

The rest of this post will be a close study of the decline in the transmission rate (“R0”) in Germany, specifically, looking at associated changes in behavior and finding the chronological relationship between them.


The multiple “curves” of any flu virus epidemic

At this point it should be specified/reminded that there is a lag-time between each of the various steps in an epidemic:

  • Transmission (i.e., having bodily contact with the virus and it going from one person’s system to another’s);
  • Onset of first symptoms for some number of those who come into contact with the virus (depending on the virus, this can be a very small %);
  • Hospitalization of the minuscule number for whom symptoms are severe;
  • Entering an intensive care unit (ICU) for a portion of those who seek hospital treatment;
  • And, finally, Death for a portion of the weakest and most vulnerable, as in the very aged or sick, generally drawn from those who sought hospital treatment.

Each step is subject to a time lag; the entire process will be up to weeks long for the median case who dies. A very, very large majority will not advance much beyond the first step, either zero symptoms or those too mild to notice, often similar to the light “under the weather” feeling a person might get multiple times a year.

The fact that so few ever have symptoms and few of those with symptoms seek treatment can cause a major under-reporting at the beginning of a peak-flu-event like this. By the time one case is confirmed, there are probably going to be hundreds who have been exposed, and the curve continues its upward movement. That and other technical limitations and delays in testing increased the natural lag even more, and so each step of the way, people, the media, and governments were reacting (and continue to react) to the situation as it existed weeks earlier; even if they privately admit the mistake, other forces have taken over and the pro-Panic side is entrenched and jealously guards its gains.

Each of the lines — transmission, symptoms, hospital visits, hospitalizations, intensive care intakes, and deaths — can be visualized as a curve, similar to the two curves presented in Part VII (“Sweden Vindicated“) which show Sweden’s daily coronavirus-positive deaths and ICU intakes. Note that in the Swedish case, the ICU intake curve precedes the Death curve:

Coronavirus Epidemic Arc in Sweden - May 2 update

The transmission curve, though, will be the first to rise, but we aren’t able to know what the transmission curve looks like until weeks after the fact. It will show a rise, have a peak period, and then a fall. The exact mechanisms behind each stage, the movements in each curve in each specific place, are for specialists to look at (there are many, including weather).

That having been said, we should be interested in dating the peak and the start of the decline in the transmission curve (technical name: “R0”).


When did Germany’s transmission curve peak? Why?

Looking back at the Robert Koch Institute (RKI) graph, we see that the 95%-confidence-estimate has the transmission-rate peaking in Germany at some point within the 72-hour window of late-PM March 8 to late-PM March 11. (This is the date range within the confidence interval for where the peak was and therefore where the decline begins.)

Coronavirus R0 in Germany - March 6 to April 9

An immediate observation is that the large event ban looks to maybe have been beneficial. At least chronologically, the announcement of the policy predates by the peak.

Health Minister Jens Spahn (b.1980; lifetime politician; and 2020s-, 2030s-, or 2040s-era Chancellor-wannabe) announced the ban on large events with over 1,000 people on the afternoon of March 8, effective the next day (March 9). While the order predates the peak, direct contributing causality is debatable; March 9 was a Monday, and it’s unlikely there were many events with over a thousand people scheduled for early that week anyway being a work-week and not a holiday week. The secondary effect of people taking personal precautions, now that the government was announcing such things, is more plausible.

The large-event ban is merely one single data-point, though, and society is highly complex. As we are really interested in what (could have) caused the decline, we need much more data. A reasonable suggestion, given where the media narrative has been, and a common one you’ll hear, is that it is entirely because people began changing their usual lives and “social distancing.”

On the idea that the peak came almost two wees before Germany’s general ‘lockdown’ orders were issued, anti-Panic commenter Kratoklastes suggested:

It’s almost as if human beings, who make decisions about how to live their lives, had made a bunch of risk-mitigation decisions all by their own self

This is a highly reasonable conclusion to draw; there should be some good evidence for it to confirm it. We may also thereby be able to find what changes were effective, on which more momentarily.

Needless to say, if we go with “people did it on their own,” it means at the least that the moderate measures of ca. March 10-15 period were an adequate response, and that the escalation-spiral of increasingly strict measures up to ‘Lockdown’ were not necessary at all.


On Herd Immunity

There are always other factors always at play that could affect this curve. The most fundamental mechanism that drives a decline of transmission rate in any flu-strain’s spread, causing it to “peak and decline on its own” in a given place, is herd immunity. When enough people start getting exposed to a new flu-virus strain, there are fewer people available who have not yet been exposed and the rate is expected to fall. This is not hard to understand.

This is to say that the natural flu-virus-cycle always looks something like that RKI graph, at some scale at some time in some place. Throw a dart at a calendar. Whatever date you hit, odds are that some virus in your region is doing something that looks like what is seen in the RKI’s calculated Wuhan Coronavirus transmission rate (R0, R-Naught) in Germany graph. Some virus of some kind will be following that arc: Emerging, rising, peaking, declining. All unbeknownst to us, all emerging and declining for one reason or another, a series of superspreading events, weather, whatever. Most are very minor; occasionally some are moderately more serious and trigger “peak flu events” which become visible in total-mortality data, usually in December, January, or February but spikes that begin in March are not necessarily surprising.

All flu viruses do this. This is what led Knut Wittkowski to recently say,

As we have learned now, over and over again, this flu is a flu.”

Most of us don’t bother paying attention to such things (why would we?) but specialists know the pattern at work.

The interesting thing in 2020 is how many caved in to the alarmists and disregarded this long-established knowledge…


Germany falls to pro-Panic forces

As mentioned above, the (announcement of the) ban on large events is chronologically associated with the peak and the start of the decline in the transmission curve. The problem with even this reasonable large-event-ban order, is that, in retrospect, and in this case, even that kind of order may have been a mistake in that it was probably a contributing factor to the Panic atmosphere (the Corona-Panic). To that extent, it may have been a net negative (and, in any case, it’s likely most/all such large events would have been postponed or cancelled anyway).

Why did Germany cave in to the Panic?

It may be lost in the flux of events since then, but Germany was actually one of the holdouts against the most extreme measures, and its government leaned towards a Swedish approach until it, too, caved in. This was after the UK and US folded to the pro-Panic wave (following the evil deed by Doctor Frankensson who released his “imaginary horror scenario” guesstimate of millions of deaths March 16).

As I see it, one must analyze this thing in terms of both calculations like R-Naught and social-political factors that contributed to the vortex of Panic that caused so much unnecessary damage. And after all, the one influences the other.


Measuring how/when people changed their behavior: The Google Mobility data

In response to a discussion on the decline of the coronavirus transmission rate in Germany, “J A A” wrote:

If you look at the google community mobility report for Germany here, it suggests a correlation between the decline in the rate of transmission and the decline in the mobility of people in Germany. While lockdown was ordered on March 23 [actually evening March 22], German authorities were already suggesting it before. For example, Merkel had an address to the nation on March 18 where she said Germans should stay at home.

I recognize this is just a correlation between two sets of data and might not be significant, but it might indicate the effectiveness of staying at home.

Before looking at the Google mobility dataset in detail, here is the transmission-rate graph again for reference:

Coronavirus R0 in Germany - March 6 to April 9

Recall now that R0 in Germany peaked at some point within the 72-hour window of late-PM March 8 to late-PM March 11.

The transmission rate (“R0”) declined as follows:

  • (The peak occurs between late-PM March 8 and late-PM March 11)
  • R0 was below 3.0 already as of the morning of March 12;
  • It hit 2.0 by about late in the day on March 14;
  • It further declined below 1.5 as of the morning of March 17;
  • It fell below 1.0 about the morning of March 20;
  • (The severe Lockdown, banning all meetings between more than two people and closing all businesses, was ordered early evening March 22, effective March 23).

I would suggest the general period of interest is the twelve days between March 8 to 19, which is when we see the substantial decline; the more specific window to look for possible causal factors driving the decline in the transmission rate, I would suggest, is March 11 to March 16, when it dropped from ca. 3.0 to already the cusp of 1.5. Any contributing measures taken by either the government, or by people independently, or by some other (natural) mechanism, that reduced the rate of transmission will have to be found within that window.

Here is the Google Mobility data for Germany:

Google Mobility data during COVID19 - Germany - March to mid-April 2020

What do we see about changes of behavior in the Google mobility data?

Here is what I see:

  • Use of mass transit begins to majorly decline beginning on the weekend of March 14-15, with the down-trend more likely beginning Sunday March 15 than Saturday March 14 (this is close chronologically to the large fall-off in British public transit ridership, which was at 80% the usual rate on the same weekend, but down to <30% by the next weekend, according to one study; Ferguson’s release of his doomsday-fantasy-scenario on Monday March 16 is associated with the British fall-off);
  • Workplace visits start to steadily go down starting Monday March 16, and were down by 40% the usual rate by Friday March 20;
  • It looks like visits to “retail and recreation” start to drastically fall also about March 16, reaching ca.70% below normal by Friday evening March 20 through Sunday March 22, with the latter date being when the general Lockdown was ordered, meaning therefore that changes in behavior all predated the Lockdown.

Note that these are not sudden fall offs, but trends, mainly driven in Germany’s case by the sum of people’s individual choices.

But here is the interesting part:

Each one of these declines in observed activity post-dates the 95%-confidence interval for when the R0 peak was hit and began its decline, which was, at latest, the late evening of March 11 (a Wednesday) or as early as late-evening March 8 (a Sunday). In other words, the transmission-rate decline was underway before the changes in behavior (social distancing), as measured in the Google Mobility data.

This may indeed be good evidence, in and of itself, for herd immunity theory in practice. Herd Immunity may at times be misunderstood to be an all-at-once phenomenon, but in practice follows an arc, much like so much else in life if graphed in aggregate, driving down the transmission-rate curve.


Other reports of people’s activities can be reconstructed from media reports. I will leave this to others, but will suggest one more and briefly look at it:


During an early part of the Corona Panic in the US, there was a focus on churches.

An early and high-profile report out of the US (March 9) of a coronavirus-positive pastor at an Episcopal church in Georgetown, Washington DC, who was thought to have “infected several parishioners,” led to the kneejerk decision by the Episcopal diocese of Washington to suspend all services at all its churches for three weeks (a decision effectively expanded to several months as the Panic escalation-spiral swirled ever upward, and bans on church services were imposed after pro-Panic forces seized control of governments).

A look at what churches, and congregants, were doing during the critical period in Germany may therefore be of interest. A few very specific dates are relevant: The evening of Wednesday February 26th (Ash Wednesday); the Sunday mornings of March 1st, 8th, and 15th. These are by far the busiest times for churches near the period of interest.

It appears there were no disruptions at all to services in Germany through Sunday March 1. Transmission was high by this time but it was not yet known. The Panic had yet to begin.

We might expect slightly lower attendance for Sunday March 8, given the early stages of the Panic cycle, promoted by the media there as everywhere else, but services were held as usual.

It appears that most church services in Germany were held as usual through Sunday March 15 (the Protestant churches reportedly held services usual on March 15 with increased safety measures, though some had already cancelled services). The largest churches/cathedrals had suspended services in accordance with the ban on large events and some local/regional government decisions. It appears that the churches that hadn’t suspended services by March 16 were heavily leaned on to do so by the government starting that day (the Catholics announced a suspension of services with the last diocese confirming the suspension March 18. Government “guidelines” recommending the suspension of services at all houses of worship were issued March 16), and very few, if any, services were held as usual on Sunday March 22, just ahead of the general Lockdown order (after which no congregation was allowed to meet at all; unprecedented in peacetime).

This is a lot of detail on churches in Germany, but the salient fact is: While the overall transmission-rate decline starts not later than late-PM March 11 (Wednesday), the church-related attendance falloff dates only in part to Sunday March 15, and is in full only from Sunday March 22. Leading up to Sunday morning services on Sunday March 15, the transmission decline was underway for at least 3.5 days and as many as 6.5 days.

The bulk of the changes in church attendance and therefore of close contact at churches, related to suspensions of services, post-date the beginning of the start of the transmission-rate decline.

The later Lockdown order that closed all churches was so late that R0 was already below 1.0 before Sunday March 22.

Church attendance may not be high in Germany, but this is a close look at yet another place where changes in behavior post-date the decline in the transmission rate.


Summary and Conclusions

We can also conclude a few surprising things about the decline of coronavirus transmissions in Germany in March 2020, which deserve to be better known:

  1. The peak of the transmission rate was between late-PM March 8 and late-PM March 11 (the RKI appears to give only a 2.5% chance the peak was after 12:01am March 12),
  2. After the peak, a decline began which turned into sustained decline, creating a familiar bell-like curve in the transmission rate;
  3. Given that the transmission rate had sunk below 1.0 some days earlier, the Lockdown order which was announced March 22 (effective March 23) was unnecessary and needlessly economically and socially damaging ;
  4. The major changes in the behavior of the public, surprisingly, all post-date the start of the transmission-rate decline;
  5. There should be no doubt that people’s changed behaviors contributed to the lowering of the transmission rate, visualizable within the graph by” keeping downward pressure on the curve” starting about March 16 (a Monday), and to a limited extent the immediately preceding weekend based on the clear changes in behavior seen in the Google data;
  6. While personal-choice social distancing may have helped with “downward pressure” on the transmission-rate curve, it did not itself trigger the start of the decline, which may have peaked on its own in accordance with the beginning stages of herd immunity in some parts of Germany (a well-underway process that was disrupted/delayed by the Lockdown);
  7. The same conclusions will apply anywhere else the epidemic curve had reached the stage it had in Germany by early March.

As for the question posed at the start of this post, on whether Social Distancing was necessary and important: Inconclusive.

It appears Social Distancing is yet another way within “Corona” that the data does not quite align with the narrative.


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40 Responses to Against the Corona Panic, Pt. VIII: The coronavirus transmission rate (“R0”) fell long before the Lockdown orders; What caused the decline?

  1. Allen says:

    Another excellent piece which uses data that completely refutes the swindle that is upon us.

    Have you seen this piece- very concise:

    • Hail says:

      Thanks, Allen.

      And that’s a good essay by Orlov. After covering a lot of ground, he says:

      [T]he first step is to free your own mind

      (By metaphor,) the Pro-Panic side staged a coup d’etat, dictated terms, set up a new religion and got most to buy into it. But on point after point, they are wrong. Others have described the Corona-Panic as a “mind virus.” The cure is the light of day. Open inquiry on neutral terrain causes the Corona mind-virus to wither and die.

      Almost any angle of investigation reveals serious narrative weakenesses, even where it seems strongest, as I think applies to the case of Social Distancing and the main point(s) of this post.

  2. Bo says:

    Thanks for this. So it was in decline either by people’s own action or by a natural process.

    Do they have the graph for Sweden? US?

    • Hail says:

      The US, not that I’m aware of. I haven’t seen it for Sweden, either, but I would expect Sweden might be more likely publish it.

  3. Federalist says:

    Excellent post as usual, Hail.

    It’s surprising that the German (R0) data comes from a German government agency. I wonder if there is public discussion in Germany about the fact that the government’s own data suggest that the extreme measures were useless. Presumably not, if Germany is anything like the U.S. with its apparently unlimited capacity to promote the narrative despite all evidence to the contrary.

    • Hail says:

      I agree, the fact that it’s from a government agency is notable (I would less expect to see this readily from the US CDC anytime soon).

      What’s also notable: It’s observed/actual data reconstructed retroactively (the R0 number is impossible to calculate in real time). These are not somebody’s future projections.

      It’s now early May, two months into the start of the Panic, and we now have a lot of observed-data “in hand,” and no longer need to rely on somebody’s models or projections. The Swedish deaths curve’s sustained down-trend (in Part VII here, Sweden Vindicated) is another case of observed-data to analyze.

  4. Bill says:

    Germany is a terrible example because their population is in the heart of Europe, at or near the site of two original breakouts. Plus they waited too long to close down and their population is 8 times that of Sweden. Compare on the other hand Israel, which is about the same size of Sweden, acted rather quickly and decisively and has so far only 200 deaths to Sweden’s 2.5k.

    • Hail says:

      I’m not sure what the relevance of Germany’s location is to its transmission rate (reproduction number, R0) and when/why it began to decline and sustained a decline.

      Maybe you are referring to their overall corona situation in Germany. It has seen almost no excess deaths, but has failed to sufficiently move towards herd immunity so it is doing itself no favors with continued economic disruption.

    • Hail says:

      The problem may be more the media than the government. Any government that tries the path of easing restrictions risks being demagogued by the media and political opponents.

      In Germany’s case, the ruling party in Germany (CDU) is already at its of lowest ebb in history and probably is worried about this.

  5. Allen says:

    Some interesting data on the value of shares of Big Pharma before and after “pandemic.” Make of it what you will.

    Percentage drop and increase in share price in February-April of the top 10 pharmaceutical companies (value in dollars):


    ROCHE HOLDING 19/2/20 – 351,1 12/3/20 – 247,4 % – 29
    JOHSON&JOHNSON 21/2/20 – 149,8 12/3/20 – 110,6 % – 26,3
    GILEAD 20/2/20 – 67 12/3/20 – 68 % – 1,4
    AMGEN 13/2/20 – 223 12/3/20 – 182 % – 18,3
    GLAXO 10/2/20 – 1657 12/3/20 – 1404 % – 15,2
    NOVARTIS 12/2/20 – 95 12/3/20 – 83,9 % – 11,6
    MERCK 13/2/20 – 122,7 12/3/20 – 89,5 % – 27
    SANOFI 18/2/20 – 93,7 12/3/20 – 73,4 % – 21,6
    ABBVIE 13/2/20 – 64,5 12/3/20 – 74,2 % + 15
    PFIZER 11/2/20 – 38,09 12/3/20 – 30,1 % – 21,2


    ROCHE HOLDING 12/3/20 – 274,4 28/4/20 – 352,7 % +28,5
    JOHSON&JOHNSON 12/3/20 – 110,6 24/4/20 – 154,86 % +40
    GILEAD 12/3/20 – 68 29/4/20 – 83,14 % +22,2
    AMGEN 12/3/20 – 182 27/4/20 – 242 % +32,9
    GLAXO 12/3/20 – 1404 30/4/20 – 1698 % +20,9
    NOVARTIS 12/3/20 – 83,9 27/4/20 – 88,03 % +5,8
    MERCK 12/3/20 – 88,5 30/4/20 – 108,55 % +22,6
    SANOFI 12/3/20 – 73,4 27/4/20 – 93,4 % +27,2
    ABBVIE 12/3/20 – 74,2 29/4/20 – 83,76 % +12,8
    PFIZER 12/3/20 – 30,1 29/4/20 – 38,12 % +26,7

    • Hail says:

      In any revolution, some will come out ahead.

      I can see the suggestions now:

      “The unemployed can work in Big Pharma factories, mask-producing plants, and creating homemade hand sanitizer like those prisoners in New York.”

      In other “Corona New Normal” news, almost too surreal to imagine is real, Sports will not be allowed indefinitely. This by diktat of Count Fauci, Head of the Corona Committee for Public Safety. (He has reportedly proposed a total professional sports ban through the end of the year unless teams play to empty stadiums and all players observe self-quarantine between games…). Unemployment will be the norm, but some are doing well.

      Maybe unemployed pro sports players can work doing PSA ads for Big Pharma during the ongoing shutdown?

  6. Mr, Hail: Again, thanks for the yeoman’s work on these posts! (wish I knew what a yeoman was to begin with.) Since we’ve been occasionally discussing the reason for the “Kung Flu Gap”, or the reason people go pro-panic or anti-panic, let me add something I’ve been thinking about. This is besides the obvious (to me, at least) factor of how much individuals stay in front of the idiot plate or their small screens.

    It’s a matter of perspective too. Let’s say, you don’t remember, because you are just that kind of person, or you are too young to remember, the SARS, the H1N1, the “Bird Flu” of the 00s-10s, or especially the Swine Flu of the mid-1970’s (for the latter, it’s perfectly understandable). Maybe people who don’t keep memories of events, other than in their own lives, just are buying the narrative that this COVID-one-niner is just a world-changing, never-seen-anything-like-it! type event. To them, it IS a science fiction movie come to life.

    Of course, without the continual media infotainment, it’d be hard to get this perspective. Many who may still watch the TV and read incessantly off the internet (guilty as charged on the 2nd charge), if they have some PERSPECTIVE, will understand that, NO, this is not (well SHOULD have not been) a world-changing event.

    Age would have to be a factor, with the older people, I imagine only up to the age in which this is really life-threatening to one’s self, having more perspective in general. It’s time for an Audacious Epigone bar graph, in my opinion.

    I’ll have do more posting on Peak Stupidity this evening. I am trying to not focus solely on this Corona-crap. Even though I have a different perspective than iSteve*, it’s probably still tiresome for some readers. I’ve got thoughts on China coming out tonight that are not related much to the Kung Flu.

    * You’d think, though, of all people, he WOULD have that perspective, ruining my theory(?)

    • oops, couple of errors there. The attempted run-on sentence starting with “Age..” should have ended with “… having more perspective, can see this as just the same-old-same-old and notice that Big-Media and Governments have gone completely overboard this particular time”

      Also, in the prior paragraph, “can’t get this perspective” is confusing. I should say, that those who don’t follow the infotainment so much will not get that ridiculous *erroneous* perspective of the idiots on TV. They’ll keep their actual true PERSPECTIVE on what this COVID-19 is, which, as you say, is just another flu. (I maintain it is s nastier version, but that’s not a big difference. I also question whether it is really that particularly SPECTACULARLY more contagious – I have a post coming on that – I mean, if it really stayed on door knobs, cloth, car upholstery, etc, etc, for days, were I worried about it more, I’d say we are all truly f___d!)

    • Federalist says:

      Steve Sailer is great on just about everything else. On the CoronaPanic he’s been terrible. To me, his posts on Corona have gotten to be just about unreadable. Basically, he picked a side and that side was wrong. I don’t know why he wasn’t skeptical and objective like he usually is. For a while now, he’s been sticking his head in the sand. He won’t write a post saying, “What if everything they told us about Covid 19 is wrong?” because he bought into it completely.

      Steve is writing some mildly critical posts now but it’s things like wanting the government of California to be a little more lenient on letting people go to the beach. Never does Steve even contemplate the kind of ideas that Hail blogs about. If Steve thinks that people like Hail are wrong, then he should explain why and debate them. Instead, he just obsesses about fine tuning the lockdown.

    • Hail says:

      I share your interest on the origins of the pro-Panic vs. anti-Panic split, which for lack of a better name I have sometimes called the Corona Political Cross-Cut. It has not energized one portion or another of existing coalitions, but has created two largely new ones, completely splitting the old coalitions. (See also a related comment I wrote yesterday and the reply by an Anon.)

      I remember really starting to notice this phenomenon about March 15 (a Sunday). but especially in the seven days thereafter. I wrote to this effect on March 26 in the anti-Panic essay you published.

      I’ve made notes on possible sources of division, as I’ve noticed them, or as I’ve heard good/plausible ones proposed by others. The list is now long and I’ve been thinking to do a post on it. I always get distracted with the latest way the data doesn’t align with the narrative, though. Seeing few others pointing it out, I spend time on such posts.

    • Hail says:

      The funny thing about thinking about the pro-Panic/anti-Panic split is that whichever parameter you “zero in” on, there are immediate counter examples, as you say yourself in your reasonable comments on perspective.

      An example of what you say is the commenter Buzz Mohawk, who I think is b.1950s. He is one of the many regulars over there who is strongly anti-Panic, and has several times said specifically that the 1968-69 pandemic flu being no big deal. That is in his memory/experience of having gotten that it, the so-called Hong Kong Flu. Yet others who remember 1968, who therefore also have that perspective, are definitely on the pro-Panic side.

      There are no easy answers, but through multiple avenues of approach we can theoretically get a rough outline of what happened.

      More lines of possible division are to be had in people’s reactions to the efforts such as the humble ones here at Hail To You — pointing to observations like “Germany’s R0 was way downbefore the Lockdown order,” and daring to ask critical questions such as “Why did Germany’s R0 decline when it did.”

  7. Pingback: Against the Corona Panic, Pt. VII: Sweden’s vindication is complete; Graphing the actual coronavirus epidemic in Sweden against the pro-Panic side’s wild projections | Hail To You

  8. Mehen says:

    Hail, regarding my previous request, I just came across this analysis which may be of interest to you.

    • Hail says:

      There is no empirical evidence for these lockdowns
      Comparing US states shows there is no relationship between lockdowns and lower Covid-19 deaths.
      WILFRED REILLY (published April 22)

      The author was right to point to Sweden, as it is the best example of the kind of analysis he is doing. By mid-April, and definitely by late April, it was clear from observed data that there were not going to some gigantic number of deaths in Sweden in the hundreds of thousands, as the Lockdown-fanatics and their fuzzy-moedellers had it. Iceland long followed similar policies to Sweden (no lockdown) and also had a mild epidemic.

      Some commenters at that article point out that comparing US states is less than ideal because flu activity never starts everywhere at the same time and in any case rural and interior areas are going to tend to be last anyway. If he wrote on April 16 (as suggested in the article based on the day/time he reports collecting the data), it would be better to do May 16 and better still July 16, by which time it will be (one can hope) “academic.” The criticisms are valid, but the general point is still right, Lockdown orders didn’t help.

      I would propose the changes in the transmission rate (R0) vs. response measures could be the best way to judge the usefulness of response measures, which is what I’ve tried to do here.

  9. Hail says:

    Commenter Mark, writing in another thread here, cites a new Robert Koch Institute study published May 3:

    [T]here is absolutely nothing in the [May 3] graph to indicate the national lockdown [in Germany] had any effect at all, beyond perhaps maintaining steady an already downward trend.

    It doesn’t appear that they have an updated R0 graph in their newest reports. They refer back to the April 23 report on the R0 Question. I take this to mean they still have confidence in their R0 calculations made at that time, which were analyzed so closely in this post.

    (Another tidbit from the RKI report: Two-thirds of coronavirus-positive deaths in Germany as of May 3 are over age 80; 1% are below age 50; this looks like an older age-profile than even regular flu.)

  10. Dwayne says:


    What are your thoughts on the possibility of seeing a sharp dip below the average number of deaths after the sharp spike we have seen? I notice on the Euromomo site that both the Netherlands and France are starting to journey well below what would be normal for this time of year. Perhaps this correction will be due to the number of elders who passed suddenly due to this virus, but would have perished naturally over a longer period this year.

    • Hail says:

      Dwayne: Yes, definitely.

      What you describe happens after every flu epidemic, because a flu epidemic will take a portion of those “closest to death,” who otherwise would have died in 1 , 2 , 3, maybe 4 months’ time instead dying with the peak-flu-event, i.e., the deaths behind the “spikes” we see.

      If you look at the EuroMOMO data for the other peak-flu-event spikes, aggregate or country-specific, you’ll tend to always see a period of below-average deaths after a spike.

      This is why it is best to view a full-year period, including long periods before and after the epidemic tails off. Winter 2019-20 was a mild season in most places, and year-to-date deaths only “caught up” well into the Wuhan Coronavirus peak-flu-event epidemic cycle.

      I discussed this more in the comment section of Part VII: See here and a follow-up expansion on the point here. I found that the long period Week 31 to Week 17 (last August through late April of this year) for the EuroMOMO reporting countries showed only a very marginal increase in deaths for 2019-20.

      I proposed that that the modest 2019-20 increase would be sapped, and possibly even all-but disappear entirely in many places, if we review the full-12-month data at the end of August (i.e., all-cause deaths for the full 52-week period 2019 Week 31 to 2020 Week 30, vs. the same periods in previous years).

  11. Pingback: Against the Corona Panic, Part IX: “Corona-Paranoia” and the case of pro-Panic US Congresswoman Haley Stevens, a character study | Hail To You

  12. Pingback: Against the Corona Panic, Part X: The problem of “deaths with” the virus vs. “deaths from” the virus: Evidence that only one-third of corona-positive deaths are “deaths from” | Hail To You

  13. Pingback: Against the Corona Panic, Part XI: Stay-Open Sweden set to lose 0.02% of total population to Coronavirus, in line with usual peak flu years; 2020 may equal 2018 in total mortality; why did we destroy the economy over this? | Hail To You

  14. Pingback: Against the Corona Panic, Pt. VI: Where has the regular flu gone? The CDC reports unprecedented crash in non-COVID flu-positives, raising questions | Hail To You

  15. Pingback: Against the Corona Panic, Pt. V: A Hero of the Hour, Dr. Knut Wittkowski | Hail To You

  16. Pingback: Against the Corona Panic Pt. IV: What about New York City? A Case Study in Hysteria Pandemic vs. Virus Pandemic | Hail To You

  17. Pingback: Against the Corona Panic, Pt. III: “Just the Flu” Vindicated by the Data; Or, Why to End the Shutdowns Now | Hail To You

  18. Pingback: Against the Corona Panic, Pt. II: “Honor the Truth, be Steadfast, Defend the Nation” — Say ‘No’ to jockeying for political advantage on the coattails of Corona Hysteria | Hail To You

  19. Pingback: Against the Corona Panic | Hail To You

  20. Hail says:

    Corona-Skeptic medical expert in the UK, Dr. John Lee, on R0 and problems with it (via quoting Lee in the Daily Mail, “Ministers are pinning everything on the ‘R’ rate but DR JOHN LEE says it’s less reliable than a weather forecast”):

    As a former professor of pathology, and someone who has had a long research career, I am very familiar with critical assessment of data.

    And in the case of R, I can tell you that this is not a strong enough number to bear the burden of any Government policy, let alone a policy with the magnitude of lockdown.

    In fact, the epidemiological models that generate R are probably less reliable than long-range weather forecasts. Let me explain.

    There is a tendency to give models too much respect because they rely on mathematics that few can follow.

    But any model, no matter how complex, is only as good as its data and assumptions.

    Here is one key problem with the forward-looking R0 estimates:

    [N]ew work just published in the prestigious journal Cell shows that coronaviruses causing the common cold give rise to immune cells [T cells] that also react to Sars-Cov-2, the virus responsible for Covid-19.

    These cells were present in 40 to 60 per cent of people who had not been exposed to the new virus. If they confer a degree of immunity to it, as seems likely, they would blow calculations of R out of the water.

    This would also explain another incorrect assumption, that the virus would ‘rip through’ the population, infecting 80 per cent of us, when in fact it seems to be levelling out at about 20 per cent.

    And here is Dr. Lee on the pro-Panic side’s push to depress R0 to below 1.0:’

    The best way to deal with the virus is not lockdown, but to encourage R above one for the fit and healthy.

    If they go out and catch the virus it builds herd immunity, bringing forward the time when R heads back below one and the virus largely peters out.

    In this post (Part VIII), I concluded that the retroactively calculated R0 for Germany showed signs of movement towards herd immunity already by the second week of March before the process was interrupted by the pro-Panic side’s coup d’etat.

  21. Pingback: Against the Corona Panic Part XII: An anthropological study into the “Corona Cult.” Pro-Panic hardliners and the media succeeded in erecting a virus-centered apocalypse cult as state religion and inducing a mass-conversion event to it, in Marc

  22. ganderson9754 says:

    I got scared early on after listening to Greg Cochran and Jim Miller. In retrospect I just can’t understand how two smart guys (and Sailer, too) could be so wrong. Cochran’s about my age, (66, but Miller’s late 40’s early 50’s, so I guess the closer to the danger zone one is the more worried one might be. Since my initial attack of the Heebie Jeebies I’ve been resistant to the narrative- although it can be said that I talk a good game, but am really kind of a pussy. However, assuming we make it out of this panic- which I assume involves gagging Fauci And screwing Trump to the sticking post, I hope someone- Walz, Baker, that witch in Michigan pays a big price.

    Also Hail- thanks for all this! You gave voice to what I was trying to formulate.

  23. Pingback: Against the Corona Panic, Part XIV: Total Mortality data in Europe now confirms the Wuhan-Coronavirus was comparable in magnitude to flu waves of the 2010s; the Panic and lockdowns are fully discredited | Hail To You

  24. Pingback: Against the Corona Panic, Part XIV: Total all-cause mortality data in Europe confirms Wuhan-Coronavirus comparable in magnitude to flu waves of the 2010s; Panic and lockdowns fully discredited | Hail To You

  25. Pingback: Against the Corona-Panic, Part XV: The coronavirus death curves in Stay-Open Sweden and the Stay-Locked-Down USA are remarkably similar over four months, discrediting lockdown-pushers | Hail To You

  26. Pingback: Is Corona a religious cult? An anthropological study | Hail to You

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