C-VIRUS BY THE NUMBERS #2

THE SECOND OF TWO POSTS LOOKING AT THE STATISTICS WHICH INDICATE HOW VIRULENT AND HOW SERIOUS THE COVID-19 REALLY IS. [NOTE THAT THERE ARE OTHER POSTS IN THIS SERIES BY Dr. BRIGGS].

Coronavirus Update IV — Take A Deep Breath — If You Still Can

by BriggsPosted on March 10, 2020

Apologies for the duplicate email! I hit the wrong button yesterday and published the incomplete update meant for today.
All the good stuff, caveats, and explanations are linked, some in Update III, and the most important in Update II, so go there first before complaining. Or skip to the bottom for the latest model.
Personal update: I haven’t seen any panic in NYC. Toilet paper still on shelves. On a flight to Florida on the weekend was one passenger wearing surgical gloves, and a mother insisting on wiping down everything her kids would come into contact with.

Condoms are selling out, because why? Because people are putting them on their fingers to avoid coronavirus. And this.
Panicked yet?
“Don’t joke, Briggs. You don’t understand. It’s much worse than they’re saying.”
That so? How do you know?
“Because the numbers they’re reporting are wrong, faked, too low.”
No kidding? How do you know?
“Because it’s much worse than they’re saying.’
That so? How do you know?…
Iterate ad nauseum.

Yes, because anything other than instantly reporting numbers on iffy tests in rambunctious medical circumstances points to a conspiracy. I’ve worked with medical data for twenty years, and the best you can say about it is it’s a mess. Look at our own data. It’s not like the entire world has got together to decide to release 100% accurate counts at 8 PM Eastern Savings Time. Numbers come in from all over, staggered and rough. We must account for this in our minds when wondering whether how much to trust the model.
Last Friday I did some numbers, which unfortunately I cannot update, because my number source stopped carrying totals for individual Chinese cities. A real pain in the kiester. Nevertheless, here’s what I did then. The idea is still sound:

Diamond Princess carried 2,670 and 1,100 crew, and had 696 coronavirus cases [still 696], or 18%. 6 dead [it’s now 7, but I’ll leave this as it is], which is 0.8% among cases, or 0.16% in toto.
This ship makes nice upper estimates: consider the tight quarters and mandatory mingling and isolation.
Then look at Shagnhai (close to Wuhan), which had Monday about 337 cases and 3 deaths—months after the outbreak. Shaghai has 24.24 million souls.
Thus: 0.14% case rate, 1% in-case death rate, 0.00001% death rate in toto.
A nice lower estimate.
A little too low, though. Applying Shanghai to world [7.7 billion] gives ~110,000 total cases, ~1,000 deaths.
We now have ~100,000 cases, ~3,400 deaths. But near the secondary peak.
Princess to world: ~142 million cases, ~12.3 million deaths. With no indication data trending that way.

China’s numbers have long since slowed, and almost stopped (not of flu, year by year!)—the rate of increase has slowed, I mean. The totals necessarily can only increase. The Wu Flu began in December, and it’s not growing worse at the hot zone, or really anywhere in China.
Hubei province, Google tells me, has 58.5 million people. China (Monday morning, EST) had 80,735 reported cases, which are spread all over the country of one billion souls. Even if all cases were in Hubei, the population case rate is 0.14%. China deaths (also Monday morning) 3,119. This is a 3.8% in-case death rate, or 0.005% death rate for the whole population. Tuesday morning update: 80,754 cases, 3,136 deaths, almost no change.
And the numbers are slowing fast (get it?) in China. Cities nearby Hubei aren’t “going exponential”—the most favored phrase I read—except in the trivial sense that going from 1 to 2 to 4 cases is exponential, but not especially concerning.
Panicked yet?
Here’s another take:

In case you can’t see it, it reads:

American Hospital Association “Best Guess Epidemiology” for #codiv19 over next 2 months:
96,000,000 infections
4,800,000 hospitalizations
1,900,000 ICU admissions
480,000 deaths
vs flu in 2019:
35,500,000 infections
490,600 hospitalizations
49,000 ICU admissions
34,200 deaths

Those stats are for the USA alone, not the world. Though I did see an ackshually guy say it’s not the whole AHA but just one professor. These kind of numbers are not uncommon from all kinds of sources, however.
Here’s another “As the coronavirus spreads, one study predicts that even the best-case scenario is 15 million dead and a $2.4 trillion hit to global GDP“. If you read the story, this is the “best-case scenario”, too.
On the other hand, some caution: Why Novel Coronavirus Fatality is Likely Overestimated.
CDC on the flu, week ending 29 February (these are always 1-2 week delayed):

CDC estimates that so far this season there have been at least 34 million flu illnesses, 350,000 hospitalizations and 20,000 deaths from flu.

USA deaths from coronachan: 22. Germany, incidentally, which had more than twice the number of USA cases had 0 deaths (so far).
A lot of people on our side of the divide are on Trump for on Monday pointing out last year saw 37,000 flu deaths in the USA. As if him saying it making its wrong or unimportant. Everything is political.
Italy and Iran had many more deaths. Iran might be slowly, Italy nearing its peak, probably.
Now you will remember what happened with SARS (see the links above where I keep repeating this). It was bad at the hot zone, and in a couple of other remote places, like Canada, which had very high, double-digit death rates. But it was almost benign in many other remote places. Similar kind of thing is happening with coronavirus. Whether is remains like this is only a guess. These guesses may be way off and this thing escalates like the AHA says. It hasn’t done so by now in China, but hey, we could have bad luck.
What has apparently (or might have) happened with coronavirus is that there are two strains, the worst in China and perhaps Italy and Iran, and the milder most everywhere else. I haven’t seen any confirmation this is so (about who has what), but it would explain the differences.
Incidentally, the tests people are using for diagnosing coronachan, and there are many, are not perfect. With the heightened publicity, i.e. panic, many more are going to be checked and surely some false positives are finding their way into the case numbers. That’s less likely with deaths, but not impossible. That means the true overall death rate might be higher than we think. But it also much less infectious than we think. We won’t know any of this for sure until long after, when it becomes the interest of obscure scholars.
Here’s another hot take. Barbie said, “Math is hard!”
No, wait. This one. This PhD said (click to see the whole thread):

We’re looking at about 1M US cases by the end of April, 2M by ~May 5, 4M by ~May 11, and so on. Exponentials are hard to grasp, but this is how they go. 4/n

I pointed out:

Exponentials sure are hard to grasp. Logistic curves are even harder.
Infections resemble logistic curves and not exponentials, for the excellent reason that exponentials always predict *everyone* will be infected in time. And this never happens. 1/
Look, even CHINA (a billion souls) does NOT have MILLIONS infected, even after 2-3 months of the outbreak. How is it we’re going to beat their numbers so far from the hot zone? 2/

I point this kind of thing out, and some get it. Some, though, are almost angry, as if any good news about this virus is unwelcome.
So many more headlines! Like Ross Douthat’s “My Sunday column: The Coronavirus is Coming For Trump’s Presidency” in which he among other cringey things wrote the eye-rolling “Obviously the White House isn’t to blame for everything that’s gone wrong with the coronavirus response.” Rod Dreher is taking the Fr James Martin role. Never Trumpers in general are trying to score political points.
The WSJ had a headline I’m too lazy to find that ran something like “How deadly plagues will become more common”, which was redolent of global warming concern.
Finally, a word on cancellations. I said it last time, but it bears emphasis. Many companies and politicians are banning travel, forbidding gatherings and the like. Some of this is surely concern and appropriate. But I’d bet much is fear—-fear of the crowd. Just what would happen to MegaCorp Inc. Ltd. if an employee gets coronavirus on an official business trip when all the other companies have stopped flying?
What would happen to the politician who wasn’t seen spending billions on brother-in-law contracts and sees an outbreak in his constituency? To ask is to answer. All this adds to the panic.

Onto the Numbers!

We had the initial peak, then the spread with the expected secondary peak. Will there be third and subsequent peaks? Will the coronavirus be like the flu or the ordinary coronavirus and be with us perennially? Will this really explode like it did in China everywhere? Hey, maybe, maybe not. Nobody knows. Not so likely though, because deadly contagious diseases tend to fade out or only pop up from time to time, like ebola or MERS.
One thing that we cannot do is this, which I see everywhere. Given “I don’t know what’s really going on” we cannot conclude “It’s really bad out there!” This is Talebism. The only thing you can say if you don’t know what’s really going on is that you don’t know what will happen. To say anything else is to take a black swan dive.
Here is the code and the data (see earlier posts for details). All numbers from 8 PM EST, Monday night. You MUST read updates II and III for the code notes if you’re playing along; all the caveats, and there are many, are there.
Here is the naive model applied to the total cases and deaths:

The guess for total cases is ~160,000; total deaths ~6,200. This is higher than last week, but I changed the date of the second peak start to make the totals higher, since it seemed model was catching the top of the secondary peak. That it might be is seen in the next picture.
Here’s the daily cases:

Have we reached the secondary peak? If so, then the model is probably not terrible, though I’d guess it’s an underestimate, as it was during the primary peak. If the same pattern holds, multiply everything by (today) 1.1 to 1.3. That multiplicative adjustments goes to 1 as we approach the secondary peak, naturally.
What if there’s a third peak? Obviously, this naive model can’t see it. But neither can we see it in the data. It’s only a guess one way or another. We have to wait and find out.
Here’s the daily deaths:

Just as we cautioned last week, the daily deaths necessarily had to lag daily cases, for you can’t die until after you get sick. Again, look for the media to tout the deaths and not the cases. But because the deaths haven’t yet reached the secondary peak, the daily forecasts are surely too low. Also, deaths are more than in the primary peak, which is of interest, and suggests there might be a third peak, but smaller.
Looks like we have a couple more weeks of madness ahead of us.
Addendum
The daily data per country is here; see China, for instance. The model can be used on the country data, too, and it would make a great exercise to do so.
I also said this:
People are taking actions to prevent spread of the disease (especially hyper vigilant actions) as absolute evidence of the prevalence of the disease. This is like saying the number of people who buckle up makes a good estimate of number hurt or killed in car crashes.
Many normally sober people with expertise who are making predictions are very scared, it seems, of being on the wrong side. They’re fearful of hearing “You said it wouldn’t be bad, but look how many died!”
But they’re willing to hear “You way over-forecast.”
This is wishcasting and wrong.
The decision people make based on the forecast can be weighted lopsidedly; very willing to suffer false positives, say.
But the best forecast is always the most accurate, regardless of the cost-loss of decisions.
We’re aiming for accuracy here with the most unsophisticated model we can make, taking only into account the “shape” of viral outbreaks (this is also a stats class post). It hasn’t been terrible. It might turn terrible, but then it also might stay un-terrible.
Of course, I have to guard against the opposite, and be careful not to under-forecast because of all the over-forecasts.

C-VIRUS BY THE NUMBERS #2

THE SECOND OF TWO POSTS LOOKING AT THE STATISTICS WHICH INDICATE HOW VIRULENT AND HOW SERIOUS THE COVID-19 REALLY IS. [NOTE THAT THERE ARE OTHER POSTS IN THIS SERIES BY Dr. BRIGGS].

Coronavirus Update IV — Take A Deep Breath — If You Still Can

by BriggsPosted on March 10, 2020

Apologies for the duplicate email! I hit the wrong button yesterday and published the incomplete update meant for today.
All the good stuff, caveats, and explanations are linked, some in Update III, and the most important in Update II, so go there first before complaining. Or skip to the bottom for the latest model.
Personal update: I haven’t seen any panic in NYC. Toilet paper still on shelves. On a flight to Florida on the weekend was one passenger wearing surgical gloves, and a mother insisting on wiping down everything her kids would come into contact with.

Condoms are selling out, because why? Because people are putting them on their fingers to avoid coronavirus. And this.
Panicked yet?
“Don’t joke, Briggs. You don’t understand. It’s much worse than they’re saying.”
That so? How do you know?
“Because the numbers they’re reporting are wrong, faked, too low.”
No kidding? How do you know?
“Because it’s much worse than they’re saying.’
That so? How do you know?…
Iterate ad nauseum.

Yes, because anything other than instantly reporting numbers on iffy tests in rambunctious medical circumstances points to a conspiracy. I’ve worked with medical data for twenty years, and the best you can say about it is it’s a mess. Look at our own data. It’s not like the entire world has got together to decide to release 100% accurate counts at 8 PM Eastern Savings Time. Numbers come in from all over, staggered and rough. We must account for this in our minds when wondering whether how much to trust the model.
Last Friday I did some numbers, which unfortunately I cannot update, because my number source stopped carrying totals for individual Chinese cities. A real pain in the kiester. Nevertheless, here’s what I did then. The idea is still sound:

Diamond Princess carried 2,670 and 1,100 crew, and had 696 coronavirus cases [still 696], or 18%. 6 dead [it’s now 7, but I’ll leave this as it is], which is 0.8% among cases, or 0.16% in toto.
This ship makes nice upper estimates: consider the tight quarters and mandatory mingling and isolation.
Then look at Shagnhai (close to Wuhan), which had Monday about 337 cases and 3 deaths—months after the outbreak. Shaghai has 24.24 million souls.
Thus: 0.14% case rate, 1% in-case death rate, 0.00001% death rate in toto.
A nice lower estimate.
A little too low, though. Applying Shanghai to world [7.7 billion] gives ~110,000 total cases, ~1,000 deaths.
We now have ~100,000 cases, ~3,400 deaths. But near the secondary peak.
Princess to world: ~142 million cases, ~12.3 million deaths. With no indication data trending that way.

China’s numbers have long since slowed, and almost stopped (not of flu, year by year!)—the rate of increase has slowed, I mean. The totals necessarily can only increase. The Wu Flu began in December, and it’s not growing worse at the hot zone, or really anywhere in China.
Hubei province, Google tells me, has 58.5 million people. China (Monday morning, EST) had 80,735 reported cases, which are spread all over the country of one billion souls. Even if all cases were in Hubei, the population case rate is 0.14%. China deaths (also Monday morning) 3,119. This is a 3.8% in-case death rate, or 0.005% death rate for the whole population. Tuesday morning update: 80,754 cases, 3,136 deaths, almost no change.
And the numbers are slowing fast (get it?) in China. Cities nearby Hubei aren’t “going exponential”—the most favored phrase I read—except in the trivial sense that going from 1 to 2 to 4 cases is exponential, but not especially concerning.
Panicked yet?
Here’s another take:

In case you can’t see it, it reads:

American Hospital Association “Best Guess Epidemiology” for #codiv19 over next 2 months:
96,000,000 infections
4,800,000 hospitalizations
1,900,000 ICU admissions
480,000 deaths
vs flu in 2019:
35,500,000 infections
490,600 hospitalizations
49,000 ICU admissions
34,200 deaths

Those stats are for the USA alone, not the world. Though I did see an ackshually guy say it’s not the whole AHA but just one professor. These kind of numbers are not uncommon from all kinds of sources, however.
Here’s another “As the coronavirus spreads, one study predicts that even the best-case scenario is 15 million dead and a $2.4 trillion hit to global GDP“. If you read the story, this is the “best-case scenario”, too.
On the other hand, some caution: Why Novel Coronavirus Fatality is Likely Overestimated.
CDC on the flu, week ending 29 February (these are always 1-2 week delayed):

CDC estimates that so far this season there have been at least 34 million flu illnesses, 350,000 hospitalizations and 20,000 deaths from flu.

USA deaths from coronachan: 22. Germany, incidentally, which had more than twice the number of USA cases had 0 deaths (so far).
A lot of people on our side of the divide are on Trump for on Monday pointing out last year saw 37,000 flu deaths in the USA. As if him saying it making its wrong or unimportant. Everything is political.
Italy and Iran had many more deaths. Iran might be slowly, Italy nearing its peak, probably.
Now you will remember what happened with SARS (see the links above where I keep repeating this). It was bad at the hot zone, and in a couple of other remote places, like Canada, which had very high, double-digit death rates. But it was almost benign in many other remote places. Similar kind of thing is happening with coronavirus. Whether is remains like this is only a guess. These guesses may be way off and this thing escalates like the AHA says. It hasn’t done so by now in China, but hey, we could have bad luck.
What has apparently (or might have) happened with coronavirus is that there are two strains, the worst in China and perhaps Italy and Iran, and the milder most everywhere else. I haven’t seen any confirmation this is so (about who has what), but it would explain the differences.
Incidentally, the tests people are using for diagnosing coronachan, and there are many, are not perfect. With the heightened publicity, i.e. panic, many more are going to be checked and surely some false positives are finding their way into the case numbers. That’s less likely with deaths, but not impossible. That means the true overall death rate might be higher than we think. But it also much less infectious than we think. We won’t know any of this for sure until long after, when it becomes the interest of obscure scholars.
Here’s another hot take. Barbie said, “Math is hard!”
No, wait. This one. This PhD said (click to see the whole thread):

We’re looking at about 1M US cases by the end of April, 2M by ~May 5, 4M by ~May 11, and so on. Exponentials are hard to grasp, but this is how they go. 4/n

I pointed out:

Exponentials sure are hard to grasp. Logistic curves are even harder.
Infections resemble logistic curves and not exponentials, for the excellent reason that exponentials always predict *everyone* will be infected in time. And this never happens. 1/
Look, even CHINA (a billion souls) does NOT have MILLIONS infected, even after 2-3 months of the outbreak. How is it we’re going to beat their numbers so far from the hot zone? 2/

I point this kind of thing out, and some get it. Some, though, are almost angry, as if any good news about this virus is unwelcome.
So many more headlines! Like Ross Douthat’s “My Sunday column: The Coronavirus is Coming For Trump’s Presidency” in which he among other cringey things wrote the eye-rolling “Obviously the White House isn’t to blame for everything that’s gone wrong with the coronavirus response.” Rod Dreher is taking the Fr James Martin role. Never Trumpers in general are trying to score political points.
The WSJ had a headline I’m too lazy to find that ran something like “How deadly plagues will become more common”, which was redolent of global warming concern.
Finally, a word on cancellations. I said it last time, but it bears emphasis. Many companies and politicians are banning travel, forbidding gatherings and the like. Some of this is surely concern and appropriate. But I’d bet much is fear—-fear of the crowd. Just what would happen to MegaCorp Inc. Ltd. if an employee gets coronavirus on an official business trip when all the other companies have stopped flying?
What would happen to the politician who wasn’t seen spending billions on brother-in-law contracts and sees an outbreak in his constituency? To ask is to answer. All this adds to the panic.

Onto the Numbers!

We had the initial peak, then the spread with the expected secondary peak. Will there be third and subsequent peaks? Will the coronavirus be like the flu or the ordinary coronavirus and be with us perennially? Will this really explode like it did in China everywhere? Hey, maybe, maybe not. Nobody knows. Not so likely though, because deadly contagious diseases tend to fade out or only pop up from time to time, like ebola or MERS.
One thing that we cannot do is this, which I see everywhere. Given “I don’t know what’s really going on” we cannot conclude “It’s really bad out there!” This is Talebism. The only thing you can say if you don’t know what’s really going on is that you don’t know what will happen. To say anything else is to take a black swan dive.
Here is the code and the data (see earlier posts for details). All numbers from 8 PM EST, Monday night. You MUST read updates II and III for the code notes if you’re playing along; all the caveats, and there are many, are there.
Here is the naive model applied to the total cases and deaths:

The guess for total cases is ~160,000; total deaths ~6,200. This is higher than last week, but I changed the date of the second peak start to make the totals higher, since it seemed model was catching the top of the secondary peak. That it might be is seen in the next picture.
Here’s the daily cases:

Have we reached the secondary peak? If so, then the model is probably not terrible, though I’d guess it’s an underestimate, as it was during the primary peak. If the same pattern holds, multiply everything by (today) 1.1 to 1.3. That multiplicative adjustments goes to 1 as we approach the secondary peak, naturally.
What if there’s a third peak? Obviously, this naive model can’t see it. But neither can we see it in the data. It’s only a guess one way or another. We have to wait and find out.
Here’s the daily deaths:

Just as we cautioned last week, the daily deaths necessarily had to lag daily cases, for you can’t die until after you get sick. Again, look for the media to tout the deaths and not the cases. But because the deaths haven’t yet reached the secondary peak, the daily forecasts are surely too low. Also, deaths are more than in the primary peak, which is of interest, and suggests there might be a third peak, but smaller.
Looks like we have a couple more weeks of madness ahead of us.
Addendum
The daily data per country is here; see China, for instance. The model can be used on the country data, too, and it would make a great exercise to do so.
I also said this:
People are taking actions to prevent spread of the disease (especially hyper vigilant actions) as absolute evidence of the prevalence of the disease. This is like saying the number of people who buckle up makes a good estimate of number hurt or killed in car crashes.
Many normally sober people with expertise who are making predictions are very scared, it seems, of being on the wrong side. They’re fearful of hearing “You said it wouldn’t be bad, but look how many died!”
But they’re willing to hear “You way over-forecast.”
This is wishcasting and wrong.
The decision people make based on the forecast can be weighted lopsidedly; very willing to suffer false positives, say.
But the best forecast is always the most accurate, regardless of the cost-loss of decisions.
We’re aiming for accuracy here with the most unsophisticated model we can make, taking only into account the “shape” of viral outbreaks (this is also a stats class post). It hasn’t been terrible. It might turn terrible, but then it also might stay un-terrible.
Of course, I have to guard against the opposite, and be careful not to under-forecast because of all the over-forecasts.

C-VIRUS BY THE NUMBERS #1

STATISTICS PLAY A VITAL PART IN DETERMINING HOW DANGEROUS AND HOW VIRULENT COVID-19 ACTUALLY IS.

THIS IS THE FIRST OF TWO POSTS LOOKING AT THE NUMBERS TO DATE.

Email

March 9, 2020

Coronavirus Codswallop -- By the Numbers

By Brian C. Joondeph

"Codswallop" is one of those interesting words that might have been used by Supreme Court justice Anton Scalia in a dissenting opinion, or by conservative intellectual William F. Buckley in describing some liberal policy.
It's a British expression that refers to words or ideas that are foolish or untrue — in other words, nonsense.
While codswallop is a good description of the entire Democrat agenda, today I will restrict its use to the hysteria surrounding the coronavirus outbreak, media fear-mongering, and resulting public panic.
Big media are all about ratings, view, and clicks, hence their axiom, "If it bleeds, it leads."  A viral outbreak is the perfect story, on par with a missing Malaysian airliner or a celebrity football player named OJ on trial for murder.
The added bonus is that any negative news can be laid at the feet of a president loathed by the media, who just so happens to be running for re-election.  The media are in full campaign mode, trying desperately to drag the carcass of one of their corpselike candidates across the presidential finish line.
Stoking fear over quarantines and supply chain disruptions has sent the stock market on a downward roller coaster ride.  One of President Trump's major achievements is the roaring economy.  Taking the stock market down 25% or more may help the Democrats.  But by the numbers, the economy is still roaring, bolstered by the February jobs report of 273,000 added jobs, more than expected, and record-low 3.5% unemployment.
Despite the hair-on-fire reporting of coronavirus news, let's look at some actual numbers, rather than the codswallop from CNN or MSNBC.  Statistics from the Centers for Disease Control and the Johns Hopkins Coronavirus Dashboard are illustrative.
At the time of this writing, there are 107,352 cases worldwide, 3,646 deaths, and 60,558 recoveries.  Fifteen of those deaths occurred in the U.S.  The odds of recovering are far higher than the odds of dying.
Cases in mainland China have peaked, with few added cases over the past week.  Cases elsewhere are on the rise, following the same pattern as China in early February.  Recoveries are rising at an even faster rate.
Granted that China may be better equipped to institute mandatory quarantines and travel restrictions under their command and control government, the pattern is similar to the disease course for other viral epidemics.
Anthony Fauci, M.D., of the National Institutes of Health and a member of the Trump administration's task force, gave some perspective in a New England Journal of Medicine editorial:

The median age of the patients was 59 years, with higher morbidity and mortality among the elderly and among those with coexisting conditions (similar to the situation with influenza).
The overall clinical consequences of Covid-19 may ultimately be more akin to those of a severe seasonal influenza.

In other words, the coronavirus may be a nastier version of the seasonal flu, potentially fatal for the elderly and infirm.  How many Americans die from the flu each day?  Let's ask the CDC.
Influenza and pneumonia caused 55,672 deaths in the U.S. in 2017, or 153 persons per day.  As a reminder, only 15 have died from the coronavirus to date, the number dying in any four-hour period from the flu.
Over the past decade, influenza has affected between 9.3 and 45 million persons each year, depending on the flu severity.  Hospitalizations for the flu have ranged from 140,000 to 800,000 persons per year, and deaths varied between 12,000 and 61,000 each year.
These numbers, in America only, far eclipse the number of coronavirus fatalities worldwide, about 3,600 thus far.  This could and will likely change, but are the numbers worthy of the hair-on-fire reaction from cable news anchors and Democrat politicians?
Remember the coronavirus mortality rate of 3.4% pushed by the World Health Organization, the global Deep State's health mouthpiece?  President Trump said that number was too high and was excoriated by the liberal media, eagerly willing to trade a bunch of dead Americans for a Trump defeat in November.
It turns out the president was correct.  Health and Human Services assistant secretary Admiral Brett Giroir declared, "The best estimates now of the overall mortality rate for COVID-19 is somewhere between 0.1% and 1%."
For comparison, the fatality rate for the seasonal flu is 0.1%.  The coronavirus fatality rate is likely similar to the 0.1–1% figure based on confirmed cases.  How many individuals have a normal cold, when in reality they have the coronavirus, and recover after a week?  That would mean that far more are infected but are unreported, as their infection is a nonevent, making the fatality rate lower than reported.
Look also at past viral illnesses, far more lethal than the coronavirus.  The fatality rate for MERS and SARS was 34.4 and 9.5% respectively.  Neither illness generated as much media hysteria as coronavirus.
Swine flu, also known as H1N1, happened on Obama's watch.  With over 60 million cases in the U.S., and over 12,000 deaths, where was the vitriol hurled at Obama, compared to what we are seeing directed toward Trump?
Another number ignored by the media is the number of cases of coronavirus per capita.  The U.S. rate is obviously far lower than China, South Korea, and Japan, but also lower than Italy, France, Germany, and Spain.
President Trump's decisive actions, again contrary to media reporting, are responsible for keeping U.S. numbers down due to his travel ban.
For additional perspective, heart disease kills 1,774 persons a day, cancer 1,641, accidents 466, and strokes 401 per day.  A recent tornado in Tennessee claimed 24 lives, almost twice the number of Americans who died from the coronavirus thus far.
Some other numbers offer perspective. Americans die each year from unusual causes. One hundred sixty die each year from autoerotic asphyxiation, 67 are victims of serial killers, 986 are killed by police, 75 from lawnmowers, 31 struck by lightning, and one American dies each year being trampled on Black Friday.
I haven't heard any media angst over lawnmowers or auto-erotica.  Medical errors are also far more dangerous than any viral epidemic.  From 250,000 to 400,000 Americans die each year from medical errors, the third most common cause of death in the U.S.  What would happen if Bernie Sanders got his wish and government were in charge of all of health care?
Numbers are inconvenient to the media — particularly the math-challenged like MSNBC's Brian Williams and NY Times editor Mara Gay discussing Bloomberg's campaign spending, being off by a factor of a million.  How can we trust these people reporting on coronavirus numbers?
President Franklin D. Roosevelt once said, "The only thing we have to fear is fear itself."  If you watch the evening news or read the daily newspaper, you will be inundated with fear.  Take the constant barrage of coronavirus codswallop with a grain of salt, and keep things in perspective.
Brian C Joondeph, M.D. is a Denver-based physician and freelance writer whose pieces have appeared in American Thinker, Daily Caller, Rasmussen Reports, and other publications. 

C-VIRUS BY THE NUMBERS #1

STATISTICS PLAY A VITAL PART IN DETERMINING HOW DANGEROUS AND HOW VIRULENT COVID-19 ACTUALLY IS.

THIS IS THE FIRST OF TWO POSTS LOOKING AT THE NUMBERS TO DATE.

Email

March 9, 2020

Coronavirus Codswallop -- By the Numbers

By Brian C. Joondeph

"Codswallop" is one of those interesting words that might have been used by Supreme Court justice Anton Scalia in a dissenting opinion, or by conservative intellectual William F. Buckley in describing some liberal policy.
It's a British expression that refers to words or ideas that are foolish or untrue — in other words, nonsense.
While codswallop is a good description of the entire Democrat agenda, today I will restrict its use to the hysteria surrounding the coronavirus outbreak, media fear-mongering, and resulting public panic.
Big media are all about ratings, view, and clicks, hence their axiom, "If it bleeds, it leads."  A viral outbreak is the perfect story, on par with a missing Malaysian airliner or a celebrity football player named OJ on trial for murder.
The added bonus is that any negative news can be laid at the feet of a president loathed by the media, who just so happens to be running for re-election.  The media are in full campaign mode, trying desperately to drag the carcass of one of their corpselike candidates across the presidential finish line.
Stoking fear over quarantines and supply chain disruptions has sent the stock market on a downward roller coaster ride.  One of President Trump's major achievements is the roaring economy.  Taking the stock market down 25% or more may help the Democrats.  But by the numbers, the economy is still roaring, bolstered by the February jobs report of 273,000 added jobs, more than expected, and record-low 3.5% unemployment.
Despite the hair-on-fire reporting of coronavirus news, let's look at some actual numbers, rather than the codswallop from CNN or MSNBC.  Statistics from the Centers for Disease Control and the Johns Hopkins Coronavirus Dashboard are illustrative.
At the time of this writing, there are 107,352 cases worldwide, 3,646 deaths, and 60,558 recoveries.  Fifteen of those deaths occurred in the U.S.  The odds of recovering are far higher than the odds of dying.
Cases in mainland China have peaked, with few added cases over the past week.  Cases elsewhere are on the rise, following the same pattern as China in early February.  Recoveries are rising at an even faster rate.
Granted that China may be better equipped to institute mandatory quarantines and travel restrictions under their command and control government, the pattern is similar to the disease course for other viral epidemics.
Anthony Fauci, M.D., of the National Institutes of Health and a member of the Trump administration's task force, gave some perspective in a New England Journal of Medicine editorial:

The median age of the patients was 59 years, with higher morbidity and mortality among the elderly and among those with coexisting conditions (similar to the situation with influenza).
The overall clinical consequences of Covid-19 may ultimately be more akin to those of a severe seasonal influenza.

In other words, the coronavirus may be a nastier version of the seasonal flu, potentially fatal for the elderly and infirm.  How many Americans die from the flu each day?  Let's ask the CDC.
Influenza and pneumonia caused 55,672 deaths in the U.S. in 2017, or 153 persons per day.  As a reminder, only 15 have died from the coronavirus to date, the number dying in any four-hour period from the flu.
Over the past decade, influenza has affected between 9.3 and 45 million persons each year, depending on the flu severity.  Hospitalizations for the flu have ranged from 140,000 to 800,000 persons per year, and deaths varied between 12,000 and 61,000 each year.
These numbers, in America only, far eclipse the number of coronavirus fatalities worldwide, about 3,600 thus far.  This could and will likely change, but are the numbers worthy of the hair-on-fire reaction from cable news anchors and Democrat politicians?
Remember the coronavirus mortality rate of 3.4% pushed by the World Health Organization, the global Deep State's health mouthpiece?  President Trump said that number was too high and was excoriated by the liberal media, eagerly willing to trade a bunch of dead Americans for a Trump defeat in November.
It turns out the president was correct.  Health and Human Services assistant secretary Admiral Brett Giroir declared, "The best estimates now of the overall mortality rate for COVID-19 is somewhere between 0.1% and 1%."
For comparison, the fatality rate for the seasonal flu is 0.1%.  The coronavirus fatality rate is likely similar to the 0.1–1% figure based on confirmed cases.  How many individuals have a normal cold, when in reality they have the coronavirus, and recover after a week?  That would mean that far more are infected but are unreported, as their infection is a nonevent, making the fatality rate lower than reported.
Look also at past viral illnesses, far more lethal than the coronavirus.  The fatality rate for MERS and SARS was 34.4 and 9.5% respectively.  Neither illness generated as much media hysteria as coronavirus.
Swine flu, also known as H1N1, happened on Obama's watch.  With over 60 million cases in the U.S., and over 12,000 deaths, where was the vitriol hurled at Obama, compared to what we are seeing directed toward Trump?
Another number ignored by the media is the number of cases of coronavirus per capita.  The U.S. rate is obviously far lower than China, South Korea, and Japan, but also lower than Italy, France, Germany, and Spain.
President Trump's decisive actions, again contrary to media reporting, are responsible for keeping U.S. numbers down due to his travel ban.
For additional perspective, heart disease kills 1,774 persons a day, cancer 1,641, accidents 466, and strokes 401 per day.  A recent tornado in Tennessee claimed 24 lives, almost twice the number of Americans who died from the coronavirus thus far.
Some other numbers offer perspective. Americans die each year from unusual causes. One hundred sixty die each year from autoerotic asphyxiation, 67 are victims of serial killers, 986 are killed by police, 75 from lawnmowers, 31 struck by lightning, and one American dies each year being trampled on Black Friday.
I haven't heard any media angst over lawnmowers or auto-erotica.  Medical errors are also far more dangerous than any viral epidemic.  From 250,000 to 400,000 Americans die each year from medical errors, the third most common cause of death in the U.S.  What would happen if Bernie Sanders got his wish and government were in charge of all of health care?
Numbers are inconvenient to the media — particularly the math-challenged like MSNBC's Brian Williams and NY Times editor Mara Gay discussing Bloomberg's campaign spending, being off by a factor of a million.  How can we trust these people reporting on coronavirus numbers?
President Franklin D. Roosevelt once said, "The only thing we have to fear is fear itself."  If you watch the evening news or read the daily newspaper, you will be inundated with fear.  Take the constant barrage of coronavirus codswallop with a grain of salt, and keep things in perspective.
Brian C Joondeph, M.D. is a Denver-based physician and freelance writer whose pieces have appeared in American Thinker, Daily Caller, Rasmussen Reports, and other publications. 

CLIMATE CONUNDRUM

What Is Earth’s Temperature, Now or Then?

Date: March 10, 2020Author: Nwo Report 0 Comments

Source: Jonathon Moseley

Is Planet Earth warming, cooling, or staying the same?  I often challenge advocates for climate alarmism: what is the temperature of the planet today?  Or we can use any specific day in recent years for which data are available. We cannot know the temperature of the planet thousands or millions of years ago if we cannot even measure it today.
Yes, the question is one single temperature of the entire planet.  Not the temperature in Nome, Alaska or Dallas, Texas, or Sydney, Australia or in your home town.  One single temperature reading for the entire globe.  To put it that way immediately sounds strange.
But if we don’t have a single temperature reading for the entire planet for today, how can we say if the planet is getting warmer or cooler or not changing at all?  We cannot talk about the temperature in, say, Geneva or London or New York City only.  The question is whether the entire planet is getting warmer, not isolated cities.
Some of us have forgotten basic statistics. Some avoided it in school.  But most of us are vaguely familiar with the random sampling process used in public opinion surveys.  We see opinion polls in the news all the time.  If we want to know how the USA’s estimated 153 million registered voters are going to vote on Election Day, but we don’t want to actually ask all 153 million of them, we have to follow (not violate) strict statistical methodologies for taking samples that are smaller than the entire “universe” or total population.
So if we ask 1,000 people — the same 1,000 people every year — whom they are planning to vote for, the results will be meaningless hogwash.  To be statistically valid, the sample must be random.  Each time.  Not a random sample one time that is repeated year after year.  Each sample subset must be truly, honestly random.  No games.  No phony adjustments.  Every time.  (It might be interesting to follow a subset over time to investigate why people decide whom to vote for.  But that cannot be used to predict the entire population.)
We also know that when people actually vote, the survey predictions are almost always wrong.  For one thing, when we survey people, we are not measuring how they are going to vote.  We are sampling what they are telling us, which is not the same thing.
The Earth is 196.9 million square miles of surface area.  It is a sphere 24,901 miles in circumference.  The vast majority of the Earth is ocean, and in particular vast, mostly untraveled waters like the Pacific and Southern Atlantic and the Arctic Sea.  The Earth is just unimaginably, stupendously big.  Most of planet Earth never sees any human presence, much less a weather station.
Another fatal flaw in climate alarmism is the failure to understand that air moves.  Air is made of gases, which by definition are not fixed in place or shape, but flow freely.  Alarmists try to evoke the image of carbon dioxide as like a blanket.  But carbon dioxide is not nailed in place.  It is free to move.  When warmed, all gases move upward towards outer space.  Convection transports heat from the surface up to the thin air, where jet airplanes cruise.  Heat is radiated from there out into space.
Air masses travel horizontally across the Earth.  Remember the polar vortex?  Extremely cold air sitting over the Arctic Circle is sometimes dislodged by air currents and moved south into Canada or even the northern United States.  The weather gets extremely cold.
But the Earth did not change.  Very cold air simply moved from one place to another.  The Earth is still the same temperature.  The Arctic got warmer, while North America got colder.  The air moved.  But overall, the Earth did not change.
Probably all of us have experienced, as this author has watched, the temperature drop 10 to 20 degrees within hours as a strong cold front moves in.  Even in the Bahamas, I have watched the temperature drop from the 90s to the 70s in only three or four hours.  For some reason, cold fronts when arriving are typically more violent and abrupt than a return to warmer weather.
Because the air is in constant motion, even a truly random sample of Earth’s 196.9 million square miles of surface area would have to be taken on the same day at the same time of day.  Note that even in one location, the swing from daytime temperatures to overnight temperatures can be a 20- to 40-degree swing on the same day.
So why can’t we just measure certain cities and average their changes?  Because we are measuring weather, not climate.  Unless we measure the entire Earth we are just measuring air masses moving around, changing temperatures.
We are told scientists have adjusted for these concerns (in some mysterious magic way).  But actual rocket scientists accidentally crashed a lander into the planet Mars due to a mathematics mistake.  So forgive us if we would just like to look over their math.
The reader can find attempts to measure the Earth’s one single temperature.  For example, Carbon Brief’s “Explainer: How do scientists measure global temperature?” offers mental gymnastics.  The hand is quicker than the eye.  One with a science education, not indoctrinated, will blow a gasket at the house of cards.
To measure the Earth’s surface area of 196.9 million square miles, there are about 10,000 weather stations on the planet, plus about 2,000 ships, airplanes, and ocean buoys.  Remember: Those stations were designed to measure local weather, not the planet.
The alarmists explain: “The temperature at each land and ocean station is compared daily to what is ‘normal’ for that location and time, typically the long-term average over a 30-year period.”  But there is no normal.  Local anomalies are driven by weather patterns, such as El Niño and the Polar Vortex.  Many weather stations are at airports for good reason.  But aviation has changed over time from occasional propeller planes to jet airplanes every few minutes.  The expansion of cities causes the heat island effect to artificially raise temperatures at airports no longer out in the countryside.
So “[d]aily anomalies are averaged together over a whole month.  These are, in turn, used to work out temperature anomalies from season-to-season and year-to-year.”  This is nonsense.  Then: “After working out the annual temperature anomalies for each land or ocean station, the next job for scientists is to divide the earth up into grid boxes.”
NASA, they say, divides the world up into boxes of 2 degrees longitude by 2 degrees latitude.  That is a gigantic area — over 19,000 square miles — with enormous temperature variations within that box.  The other measurement schemes are 5 degrees by 5 degrees or over 119,000 square miles each.  There is vastly different weather occurring within each 119,000-square-mile box.  Again, there are only 12,000 weather stations, including part-time ones on mobile craft for the entire planet, unevenly focused too much on the “First World.”
From the time the thermometer was invented with a scientifically valid scale comparable from one thermometer to another around 1850, other than use as a novelty or hobbyist’s toy, and meticulous records started (every day, the same time of day), measurements were concentrated in Northwestern Europe and the Northeastern United States.  Gradually, decade by decade, driven largely by the rise of air strips in World War I, the locations, geographic diversity, quantity, and quality of weather stations changed over time.  So even the temperature records we have are not comparable across decades.
In short, you can claim to be able to measure the world’s temperature.  But if you want to really do it — good luck.

https://nworeport.me/2020/03/10/what-is-earths-temperature-now-or-then/

CLIMATE CONUNDRUM

What Is Earth’s Temperature, Now or Then?

Date: March 10, 2020Author: Nwo Report 0 Comments

Source: Jonathon Moseley

Is Planet Earth warming, cooling, or staying the same?  I often challenge advocates for climate alarmism: what is the temperature of the planet today?  Or we can use any specific day in recent years for which data are available. We cannot know the temperature of the planet thousands or millions of years ago if we cannot even measure it today.
Yes, the question is one single temperature of the entire planet.  Not the temperature in Nome, Alaska or Dallas, Texas, or Sydney, Australia or in your home town.  One single temperature reading for the entire globe.  To put it that way immediately sounds strange.
But if we don’t have a single temperature reading for the entire planet for today, how can we say if the planet is getting warmer or cooler or not changing at all?  We cannot talk about the temperature in, say, Geneva or London or New York City only.  The question is whether the entire planet is getting warmer, not isolated cities.
Some of us have forgotten basic statistics. Some avoided it in school.  But most of us are vaguely familiar with the random sampling process used in public opinion surveys.  We see opinion polls in the news all the time.  If we want to know how the USA’s estimated 153 million registered voters are going to vote on Election Day, but we don’t want to actually ask all 153 million of them, we have to follow (not violate) strict statistical methodologies for taking samples that are smaller than the entire “universe” or total population.
So if we ask 1,000 people — the same 1,000 people every year — whom they are planning to vote for, the results will be meaningless hogwash.  To be statistically valid, the sample must be random.  Each time.  Not a random sample one time that is repeated year after year.  Each sample subset must be truly, honestly random.  No games.  No phony adjustments.  Every time.  (It might be interesting to follow a subset over time to investigate why people decide whom to vote for.  But that cannot be used to predict the entire population.)
We also know that when people actually vote, the survey predictions are almost always wrong.  For one thing, when we survey people, we are not measuring how they are going to vote.  We are sampling what they are telling us, which is not the same thing.
The Earth is 196.9 million square miles of surface area.  It is a sphere 24,901 miles in circumference.  The vast majority of the Earth is ocean, and in particular vast, mostly untraveled waters like the Pacific and Southern Atlantic and the Arctic Sea.  The Earth is just unimaginably, stupendously big.  Most of planet Earth never sees any human presence, much less a weather station.
Another fatal flaw in climate alarmism is the failure to understand that air moves.  Air is made of gases, which by definition are not fixed in place or shape, but flow freely.  Alarmists try to evoke the image of carbon dioxide as like a blanket.  But carbon dioxide is not nailed in place.  It is free to move.  When warmed, all gases move upward towards outer space.  Convection transports heat from the surface up to the thin air, where jet airplanes cruise.  Heat is radiated from there out into space.
Air masses travel horizontally across the Earth.  Remember the polar vortex?  Extremely cold air sitting over the Arctic Circle is sometimes dislodged by air currents and moved south into Canada or even the northern United States.  The weather gets extremely cold.
But the Earth did not change.  Very cold air simply moved from one place to another.  The Earth is still the same temperature.  The Arctic got warmer, while North America got colder.  The air moved.  But overall, the Earth did not change.
Probably all of us have experienced, as this author has watched, the temperature drop 10 to 20 degrees within hours as a strong cold front moves in.  Even in the Bahamas, I have watched the temperature drop from the 90s to the 70s in only three or four hours.  For some reason, cold fronts when arriving are typically more violent and abrupt than a return to warmer weather.
Because the air is in constant motion, even a truly random sample of Earth’s 196.9 million square miles of surface area would have to be taken on the same day at the same time of day.  Note that even in one location, the swing from daytime temperatures to overnight temperatures can be a 20- to 40-degree swing on the same day.
So why can’t we just measure certain cities and average their changes?  Because we are measuring weather, not climate.  Unless we measure the entire Earth we are just measuring air masses moving around, changing temperatures.
We are told scientists have adjusted for these concerns (in some mysterious magic way).  But actual rocket scientists accidentally crashed a lander into the planet Mars due to a mathematics mistake.  So forgive us if we would just like to look over their math.
The reader can find attempts to measure the Earth’s one single temperature.  For example, Carbon Brief’s “Explainer: How do scientists measure global temperature?” offers mental gymnastics.  The hand is quicker than the eye.  One with a science education, not indoctrinated, will blow a gasket at the house of cards.
To measure the Earth’s surface area of 196.9 million square miles, there are about 10,000 weather stations on the planet, plus about 2,000 ships, airplanes, and ocean buoys.  Remember: Those stations were designed to measure local weather, not the planet.
The alarmists explain: “The temperature at each land and ocean station is compared daily to what is ‘normal’ for that location and time, typically the long-term average over a 30-year period.”  But there is no normal.  Local anomalies are driven by weather patterns, such as El Niño and the Polar Vortex.  Many weather stations are at airports for good reason.  But aviation has changed over time from occasional propeller planes to jet airplanes every few minutes.  The expansion of cities causes the heat island effect to artificially raise temperatures at airports no longer out in the countryside.
So “[d]aily anomalies are averaged together over a whole month.  These are, in turn, used to work out temperature anomalies from season-to-season and year-to-year.”  This is nonsense.  Then: “After working out the annual temperature anomalies for each land or ocean station, the next job for scientists is to divide the earth up into grid boxes.”
NASA, they say, divides the world up into boxes of 2 degrees longitude by 2 degrees latitude.  That is a gigantic area — over 19,000 square miles — with enormous temperature variations within that box.  The other measurement schemes are 5 degrees by 5 degrees or over 119,000 square miles each.  There is vastly different weather occurring within each 119,000-square-mile box.  Again, there are only 12,000 weather stations, including part-time ones on mobile craft for the entire planet, unevenly focused too much on the “First World.”
From the time the thermometer was invented with a scientifically valid scale comparable from one thermometer to another around 1850, other than use as a novelty or hobbyist’s toy, and meticulous records started (every day, the same time of day), measurements were concentrated in Northwestern Europe and the Northeastern United States.  Gradually, decade by decade, driven largely by the rise of air strips in World War I, the locations, geographic diversity, quantity, and quality of weather stations changed over time.  So even the temperature records we have are not comparable across decades.
In short, you can claim to be able to measure the world’s temperature.  But if you want to really do it — good luck.

https://nworeport.me/2020/03/10/what-is-earths-temperature-now-or-then/

GREEKS SPRAY INVADERS WITH PIGS' ***** AND MORE THAT MSM WON'T SHOW

GREEKS SPRAY INVADERS WITH PIGS' ***** AND MORE THAT MSM WON'T SHOW

NEED WE PANIC?

Verified by Psychology Today

Samuel Paul Veissière Ph.D.

Culture, Mind, and Brain

The Coronavirus Is Much Worse Than You Think

How COVID-19 is infecting our minds, not our lungs.

Posted Feb 27, 2020

Ask yourself the following: Would you feel confident taking an over-the-counter medication if you were 98 percent sure it would work safely? Would you dare to gamble all your savings in a one-off scheme in which you had a 98 percent chance of losing it all?
The coronavirus is a similar no-brainer. As a generic member of the human species, you have about the same odds of dying of the coronavirus as winning in the gambling scenario. These are overall rates, meaning that unless you are already in very poor health, are very old, or very young, the odds for you are much lower. Or next to nil.
Why then are so many countries implementing quarantine measures, shutting down their borders, schools, and soccer games for something that is less likely to happen to anyone than drowning in a single year, or even being hit by lightning in one’s lifetime? Why is the stock-market crashing, and why are school and workplace mass emails, news headlines, social media feeds, and face-to-face conversations dominated by stories about what is essentially a new strand of mild to moderate flu?
Our minds like to jump to threatening headlines with big, alarming numbers. As this post was first aired, a total of 80,000 cases of COVID-19 had been reported in 40 countries. To put things in perspective again, this is a mere 0.0001% of the world population. In comparison, seasonal outbreaks of influenza make 3 to 5 million people sick enough to seek treatment worldwide (up to 0.06% of the population) while many more cases go undetected. The seasonal flu results in 290,000 to 650,000 deaths each year — up to 0.008% of the population.
To grasp the full — and very real — power of the coronavirus, we need to enter the rabbit hole of evolved human psychology.
The coronavirus is quite simply, and almost exclusively, a moral panic. This is so in the most literal sense. Human bodies, minds, societies, systems of meaning, norms, and morality have co-evolved with pathogens. Determining who drove whom in this dark scenario is currently unclear.
To understand this strange dynamic, consider people’s blatant inability to make statistically correct inferences about actual risk in the current epidemic of catastrophizing about COVID-19. The human propensity to ignore basic probability, and our mind’s fondness for attending to ‘salient’ information is well-documented. The negativity bias is one of the most potent of such pre-programmed mental heuristics: Any cue that contains information about potential dangers and threats will jump to mind easily, will be easier to remember, and easier to pass on. In the lingo of cultural epidemiologists, we describe danger cues as possessing "high learnability, memorability, and teachability" — or high feed-forward potential in epidemics of ideas. There is a clear evolutionary advantage to this trait: We are better off over-interpreting rather than under-interpreting danger. In most cases, these instant associations work well. Cues that signal the presence of pathogens tend to elicit automatic disgust responses, so as to help us avoid dangers.  Over time, we’ve also evolved the ability to react instantly to a range of visual and auditory cues that convey a high likelihood of pathogen presence. This is why most of us are grossed out by the presence of mice, rats, or bugs, or by the sound of sniffling.
But this mental heuristic is known to glitch in other ways. Racism and xenophobia, for example, also recruit pathogen-detection brain mechanisms. The language and metaphors we routinely use to justify moral outrage and our fear of the other also employ pathogen metaphors. We speak of undesirables as “vermin”; we are “grossed out” by offensive ideas; we worry about our girls being “soiled," and our young people's minds being “infected” by “sick” individuals and groups. Studies have shown that germaphobes and people who score higher in disgust sensitivity tend to be more ideologically and politically rigid.
The plot thickens — or, more to the point, tightens — again. A growing consensus in the social sciences plots the historical rise of societies with 'tighter' social norms and more conservative cultures to the presence of pathogens in the environment. Western cultures tend to be 'looser' than non-Western ones for this reason — northern latitudes do not sustain as many pathogens as tropical zones — and they have become even looser since the advent of improved sanitation and antibiotics. Countries with higher historical pathogen prevalence are also associated with less gender equality and more rigid gender roles than those with cleaner environments.
But it gets weirder again. Deadly viruses like smallpox, the plague, measles, and influenza evolved in conditions of high population density between humans, animals, their detritus, and their excretions. More to the point, zoonotic (animal-borne, contagious to humans) diseases co-evolved under new selective pressures exerted on humans, plants, and animals as they domesticated one another in the Neolithic period, starting 12,000 years ago. By ‘domestication,' I refer to the evolutionary strategy of species who selectively breed and reshape the life histories of other species for their own needs. Over a million years ago, following the domestication of fire, for example, our hominin ancestors were able to burn vast expanses of forest and savannah to reshape animal migration patterns for their hunting needs. Neolithic humans, to be sure, appear to have started the trend of selectively breeding plant species (millet, wheat, rice) and animal species (dogs, camels, pigs, goats, sheep, cows) for their nutritional, survival, and energy-conservation needs. As human and animal population density rose in the Neolithic, multiple waves of uninvited commensals like rats, mice, sparrows, pigeons — and, following those, fleas, lice, ticks, ants, flies, bees, and other insects joined in. Parasites, bacteria and viruses soon followed.  Anthropologist James C. Scott refers to these radical niche transformations as “Late-Neolithic Multi-Species Relocation Settlement Camps."
Recall that evolution is a numbers game: At a population level, species seek to maximize their numbers by exploiting — and bending to their will — the vulnerabilities of other organisms in the niche. From Scott’s perspective, commenting on the backbreaking toil of humans who became tied to their ploughs in the course of a few centuries, it is unclear who domesticated whom in the Neolithic. Judging by the exponential spread and 'success’ of such plant species as wheat, corn, rice, or marijuana, and the radical modes of restructuring of human activities and human bodies following their adoption as mono-crops, one might suggest, as Michael Pollan once did, that these plants colonized us. The abandonment of varied sources of proteins and fibre, as well as the flexible modes of livelihoods and environmental knowledge that sustained hunter-gatherer lifestyles gave rise, in record evolutionary time, to deep physiological changes and damages to the human body. By many accounts, the human species has yet to recover from the shock of the agricultural transition, which, for a while, led to lower statures, tooth decay, and lower bone density from malnutrition; a spike in auto-immune diseases; and increased mortality from new pathogens. On another cynical account — judging this time by the bending of human psychology, norms, social roles, moral codes, and patterns of migration and conflict — the new pathogens clearly won the numbers game.
By this account, COVID-19 is turning out to be a remarkably intelligent evolutionary adversary. By exploiting vulnerabilities in human psychology selectively bred by its pathogen ancestors, it has already shut down many of our schools, crashed our stock market, increased social conflict and xenophobia, reshuffled our migration patterns, and is working to contain us in homogenous spaces where it can keep spreading. We should pause to remark that COVID-19 is extraordinarily successful epidemiologically, precisely because it is not extremely lethal. With its mortality rate of 90%, for example, Ebola is a rather stupid virus: It kills its host — and itself — too quickly to spread far enough to reshape other species’ life-ways to cater to its needs.
The bad news for you is that, if you live in a densely populated area, you are very likely to contract the coronavirus — if not this year, next year, or the year after as it undergoes its seasonal global migration pattern with its zoonotic cousins.
The good news is that you will almost certainly not die from it, and it may not even register that you are slightly more sluggish than usual for a week or two. Much more relevant to the terrible threat caused by our Pathogen Overlords, you can prepare to fight the yearly Corona invasions to come by resisting your own neuroticism, your own prejudice, and your own irrationality. As far as numbers games are concerned, our Pathogen Overlords are much more noble, and much more worthy of our hatred than our fellow human pseudo-enemies in political, religious, and culture wars.
Humans of the world, unite: You have nothing to lose but your bad health.