The Claim 37% Of Heat Deaths Are Caused By Global Warming Is Absurd

The media has been reporting that 37% “of warm-season heat-related deaths can be attributed to anthropogenic climate change”.

They gleaned this from the peer-reviewed paper, “The burden of heat-related mortality attributable to recent human-induced climate change”, in Nature Climate Change by Vicedo-Cabrera and a slew of others (opening quote from the Abstract).

The abstract opens with this true statement: “Climate change affects human health”. Every year when winter rolls in, deaths rise, peaking sometime in January in the Northern Hemisphere. Deaths begin falling in spring, falling to a low when the hot summer winds start blowing. Here, for example, are the official CDC all-cause weekly deaths, starting late 2009 and going through May of 2021. Flu and pneumonia and COVID deaths are also plotted.

In Florida and Arizona in winter, the snowbirds arrive from Michigan, Ohio, Canada, and other points north. These people are fleeing the cold weather, seeking out the heat. On purpose. They do this not in anticipation the hotter weather will kill them, but will cure or sustain them.

Yet despite all this, the authors say heat due to global warming is killing people, and killing a lot of people.

Before we get to how the authors came to that “37%,” let’s think about how to best know whether or not deaths were caused by heat, both now and in the absence of any so-called global warming. Then we’ll see how close the authors came to this ideal approach.

To properly measure deaths caused by heat, we’d search death records for those deaths in which heat is mentioned as at least a contributing cause, and the investigate the circumstances. The authors did not do this.

Perhaps it’s difficult to know whether any death was caused by heat, that information not being present in many charts. But we might be able to create a per-person model of heat-caused deaths using inputs like temperature and person characteristics (hypertension, weight, dehydration, etc.). For each person in the death database we’d have a probability that their death was associated with heat.

The authors did not do this.

Neither did they compute, as a comparison, a second per-person probability of death-by-heat for temperatures different than the actual temperatures. Call this a counterfactual temperature, chosen to be that value the temperature might have been absent global warming. And they did not multiply the heat-death probability they did not compute by the different probability that the counterfactual temperature was the correct temperature absent global warming. After all, the counterfactual temperature is only a guess and we have to account for its uncertainty.

Again, the authors did none of this.

The weakest, least convincing, and even wrong approach would be to correlate daily deaths and daily temperatures. Everybody knows (or claims they know) correlation does not equal causation. To imply causation by correlation is therefore wrong. It is wrong because the correlation may be spurious, misleading, and so on.

It is also wrong because we would have the strongest correlation in winter, and we’d conclude cold causes more deaths because of the strong correlation between lower temperatures and higher deaths. Curiously, the authors limited their view to the “warmest four consecutive months in each location” and ignored times when deaths peak.

There is still one more uncertainty to account for, which the authors did not. This is a subtly of the heat-caused death model mentioned earlier. Low and high temperatures kill some people. But the number of direct temperature-caused deaths (e.g. frostbite, sunstroke) are low. At best, then, we’re dealing with temperature being an indirect cause.

That means there is uncertainty in how strong a cause, in the long causal chains, of actual deaths temperature is. In order to make such a strong claim that 37% of heat-related deaths are attributable to global warming, the authors must have hit upon an irreproachable set of data and methods to identify these myriad causes.

Or they made an enormous mistake.

I’m next going to explain their approach using a minimal amount of detail: the full explanation is maddening (feel free to look it up and check me).

They went with the weakest and wrong, correlation-is-causation, approach. They did not use the actual daily temperatures and daily death counts (from either all-causes, or only all non-external causes, freely mixing the two codes). Instead, they substituted a model of daily temperatures (“historical climate simulations”), using the actual temperatures to sometimes modify this model for “bias”. They did not account for the uncertainty inherent in the temperature substitution. This means, even if everything else is right, their results will be too certain.

For the counterfactual temperatures, they also used a model. They did not account for the uncertainty this counterfactual model was right. Again, their results would be too certain.

To correlate (something like) deaths with the two models, they used a third model (“a quasi-Poisson regression” which has certain parameters). The model was not just for today’s modeled temperature and today’s death, but they allowed for “a predefined lag period” in the two.

This appears to be 10 days before any death. To account for this lag, they used two more models (two splines, one for seasonality). Naturally, they did not account for the uncertainties in these two models, nor of the arbitrary, and what seems awfully long, 10-day period. The longer the time period, the more “associated” deaths they would identify.

All of these models have parameters, also called coefficients. Ordinarily, we’d be interested in the observables, and not the unobservable innards (coefficients) of any model. See this for why. The gist is that certainty in the coefficients is always greater than certainty in the observables. Meaning any results which speak of observables (heat deaths) but which report what happened to coefficients are over-certain.

Anyway, the coefficients from this first stage of models were then input into regressions along with “country-level gross domestic product, location-specific average temperature and interquartile range and indicators of climatic classification”.

Gross domestic product is causative of heat deaths?

You’ll be tired of hearing it, but the uncertainty in the observables due to these regressions was not accounted for.

Finally, the actual deaths were substituted for modeled deaths: “For each location-scenario-model-day combination, we computed the number of heat-related deaths on the basis of the corresponding modelled temperature series, daily baseline mortality and the estimated heat-mortality association represented by the location-specific [coefficient estimates]”.

By this point, we have models of models (built with other models) predicting models of models. It’s models all the way down. They did compute, for the final stage only, confidence intervals of the model coefficients, for the locations and scenarios.

This allowed them to say such things as, for Akron, OH, “Heat-related mortality in ‘Natural forcings only’ scenario” was -0.04% of all deaths. This is not a typo. They also said for Akron that “Annual average heat-related number of deaths attributed to human-induced climate change” was -1. Again, no typo. Lastly they also said “Proportion of heat-related mortality attributed to human-induced climate change” at Akron was 52.9%. Big jump, that.

Akron was far from the only city to have negative heat-related deaths. Daytona Beach, Florida had -3 (negative 3) annual deaths due to global warming. And so on.

I haven’t the slightest idea what the authors could mean by these numbers (found in supplementary tables). They appear to be the result of bad models, like how in regressions negative test scores can be produced, because normal distributions shouldn’t have been used. Or they could have meant the extra heat caused by global warming saves 3 people are year in not-so-cold Daytona Beach.

Did they authors not notice their own results?

I didn’t show the confidence intervals, because they are the wrong ones. They apply only the final-final-final model stage and incorporate none of the uncertainties I mentioned above.

So, did the authors make that one final mistake of calling correlation causation? Even though every scientist is taught from birth not to commit this blunder?

Yes, sir, they did: “our findings demonstrate that a substantial proportion of total and heat related deaths during our study period can be attributed to human-induced climate change”. That is causal language no matter how you cut it.

Now that I have shown you the authors have made many errors, I am allowed to speculate on why they made them. One is hubris: “we applied cutting-edge time-series regression techniques”. They mention far down in the notes it was they that invented these methods. The desire to do something, even the wrong thing, just to show that it can be done is strong in many scientists.

The most important reason, however, is faith. It is clear the authors began with the belief that global warming is causing heat deaths (and not lowering cold deaths). With this faith, they would be unable to see how the data could prove them wrong.

BONUS! This paper falls into the, unfortunately growing, climate attribution genre, of which I provide a full critique of the methods and mistakes of this not-to-be-trusted analytic technique.

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Categories: Statistics

22 replies »

  1. Need a parallel study on deaths due to Biden Presidency. Or deaths due to MSM hysteria, etc.

  2. I am curious, how many authors were on this study? “The greater the number of contributing authors on a paper, the poorer the quality of said paper.”

  3. Michael: I so agree.

    So where on the paper is a comparison to the Dust Bowl and the 1800’s heat waves?????

    “To properly measure deaths caused by heat, we’d search death records for those deaths in which heat is mentioned as at least a contributing cause, and the investigate the circumstances. The authors did not do this.”
    How about they checked historical temperature records to see how hot it has to be to kill? Oh, no time for that either.

    Models are way easier than data–the models say what you want them to. Data you have to surgically remove all that pesky data that doesn’t fit.

  4. Let’s take a step back from papers and look at events. My sister-in-law got married during the huge global heat wave 25 years ago, which I will never forget because we had to wait outside for about half an hour for the church to open and it was incredibly hot. Remember it? Thousands of elderly people in France died because of their SCHEDULES — French people have a lot of time off and take long vacations out of the country, so many young and middle-aged people were gone during the heat wave and elderly people who had no fans or air conditioning died when when their relatives weren’t around to check on them. According to this crowd, the heat waves should be worse now, right? It’s 25 years later, which to them should have caused a huge acceleration (rather than being a tiny blip in natural variations that should be difficult to measure unless there was a HUGE variation). So tired of this.

  5. Gail

    Are you talking 1994?

    I remember reading the International Herald Tribune reporting the highest temperatures in 400 years!


    If this paper includes 2020/2021 deaths, IHME counters their figures with excess deaths attributed to Covid
    World deaths currently just under 7 Million
    US deaths just under 1 million
    Your paper is countered by the IHME

  6. Cold kills way more than heat.

    Some day the idiots in charge of this rock are going to put into motion some stupid plan to “cool the earth” (by pumping some chemical into the air, or erecting a giant sun shade in orbit) and they’ll trigger another ice age and kill billions.

  7. Dear Granting Agency:

    This request for $2,718,281.82 [ain’t excel grand?] dollars to support [my tenure app] further research at my University’s Climate Catastrophe Center is supported by the following key documents:

    1 – our pledge of allegiance to wokism, BLM, and the democratic [fascist] national agenda;
    2 – a copy of my previously published work proving the reality of climate change [all b.s, of course, but Fully funded]
    3 – a contractual commitment to producing work to be reported under the abstract below:

    The coming heat death of the proletariat

    Our results [stuff we will make up] are based on detailed statistical comparisons between [wild ass guesses] concensus estimates about the heat tolerance of food grains to [other wild ass guesses] and cell wall radi in Nebraska native grasses. Analysis of 5,772.15 samples suggest (p=0.01) [lol] a nanometer correlation to each tenth of a degree [kelvin] of temperature change [huh? hey, they’re arts grads]. We conclude that the global climate emergency we’re currently experiencing will reduce world food production by 25% [it came up heads] over the next ten [heads again] years.

  8. Now now, we all know that what the scientists of THE SCIENCE ™ were really trying to do was to help the government find an excuse to lock us all up inside during summer in order to save lives and prevent hospitals from being overrun during both warm and cold weather.

  9. some stupid plan to “cool the earth” …and they’ll trigger another ice age

    cf Fallen Angels, by L.Niven, J.Pournelle, and M.Flynn

  10. People will only sit up and take notice when the climanistas’ switch off the power.
    Don’t believe it just wait, the whole movement is filled with useful idiots led by a eugenics
    movement that been around since Galt, Malthus, and propagandist in chief Holy Man
    Darwin. The world is just not quite enough for the 1% who get a really big kick out of
    watching bugman squirm. He’s like a deer in the headlights with the gay queer
    trans racist pedophile tropes they concoct, symptoms of a diseased mind.


  11. All,

    I miscounted the number of authors. It’s not 4 dozen. It’s 70.

    A lot of people wanted to get in on the signaling.

  12. Distributed Lag Non-Linear Model (DLNM) regression, correct? I used such in my master’s thesis, but now I know better…

  13. So 70 people proudly put their names on this bastardized junk science? Not a single one detected the horrendous mistakes? They all wanted “credit” as if they were real scientists?

    The Hoax runs deep. Integrity is a rare and endangered commodity. The lemmings are on the run over the cliff. It’s mass intellectual suicide. Jim Jones Koolaid University. Sacrifice yourself on the Altar of Gross Stupidity today!

  14. “Finally, the actual deaths were substituted for modeled deaths…”

    Is the English language different where the author lives? This looks exactly backwards to me. Reasonable, in context, would be:

    “Finally, modeled deaths were substituted for actual deaths…”

    or perhaps

    “Finally, actual deaths were replaced by modeled deaths”.

    Granted, even the Oxford English Dictionary seems to nod at this, saying:

    n noun
    1 a person or thing acting or serving in place of another.
    2 a sports player nominated as eligible to replace another after a match has begun.
    3 Scots Law a deputy.
    n verb
    1 (usually substitute something for) use, add, or serve in place of. Ø(usually substitute something with) replace with another. ØChemistry replace (an atom or group in a molecule) with another.
    2 replace (a sports player) with a substitute during a match.

    substitutability noun
    substitutable adjective
    substitutive adjective

    Middle English (denoting a deputy or delegate): from Latin substitut-, substituere ‘put in place of’.

    Traditionally, the verb substitute is followed by for and means ‘put (someone or something) in place of another’, as in she substituted the fake vase for the real one. More recently it has also been used with with or by to mean ‘replace (something) with something else’, as in she substituted the real vase with the fake one. Though still disapproved of by traditionalists, this use is now generally regarded as part of standard English”.

    But is it wise to use exactly the same phrase to be used to mean two exactly opposite things?


    I moved to Texas from West Virginia (don’t ask) and I’ve been telling everyone within earshot that the heat is going to kill me. NOW I KNOW.


    Thanks to Yeonmi Park and Jordan Peterson for telling her courageous story. None of this is surprising to me, because of my strong education and my life experiences on six continents.

    Most people do not yet realize that the North Korean model or the Chinese Communist Party (CCP) model is what western elitists like Trudeau and Biden etc want for Canada, the USA and the rest of the Western democracies – the end of freedom and the adoption of the brutal, corrupt CCP model – a few princes at the top, looking down on all the poor peasants.

    MY SITUATION ASSESSMENT – published circa November 2020

    It’s ALL a leftist scam – false enviro-hysteria including the Climate and Green-Energy frauds, the full lockdown for Covid-19, the illogical linking of these frauds (“to solve Covid we have to solve Climate Change”), paid-and-planned terrorism by Antifa and BLM, and the mail-in ballot USA election scam – it’s all false and fraudulent.

    The Climate-and-Covid scares are false crises, concocted by wolves to stampede the sheep.

    The tactics used by the global warming propagandists are straight out of Lenin’s playbook. The Climategate emails provided further evidence of the warmists’ deceit – they don’t debate, they shout down dissent and seek to harm those who disagree with them – straight out of Lenin.

    The purported “science” of global warming catastrophism has been disproved numerous ways over the decades. Every one of the warmists’ very-scary predictions, some 80 or so since 1970, have failed to happen. The most objective measure of scientific competence is the ability to correctly predict – and the climate fraudsters have been 100% wrong to date.

    There is a powerful logic that says that no rational person can be this wrong, this deliberately obtuse, for this long – that they must have a covert agenda. I made this point circa 2009, and that agenda is now fully exposed – it is the Marxist totalitarian “Great Reset” – “You will own nothing, and you’ll be happy!”

    The wolves, proponents of both the very-scary Global Warming / Climate Change scam and the Covid-19 Lockdown scam, know they are lying. Note also how many global “leaders” quickly linked the two scams, stating ”to solve Covid we have to solve Climate Change” – utter nonsense, not even plausible enough to be specious.

    Regarding the sheep, especially those who inhabit our universities and governments:
    The sheep are well-described by Nassim Nicholas Taleb, author of the landmark text “The Black Swan”, as “Intellectual-Yet-Idiot” or IYI – IYI’s hold the warmist views as absolute truths, without ever having spent sufficient effort to investigate them. The false warmist narrative fitted their negative worldview, and they never seriously questioned it by examining the contrary evidence.

    More, for those who can and do read and think:

    A Climate, Energy and Covid Primer for Politicians and Media
    By Allan M.R. MacRae, Published May 8, 2021 UPDATE 1e
    Download the WORD file

  17. It’s hard to believe that anyone would actually want credit for authoring such an obvious piece of drek.

  18. Most of these “scholarly” and “peer-reviewed” articles are overseen by people for whom English is not their first language. They are gas-lighting efforts by Communist Chinese, who’ve infested our universities and media.

    Last winter, we saw what happened when Texas’ independent power grid went down during an ice storm. People froze to death, even in their beds.

    Meanwhile, a Communist Chinese mega-billionaire former general, (the same guy who owns the land where China is persecuting Muslims) now owns 200 sq mi of Texas, including a wind farm, on the Mexican border; the Communist Chinese are building a major runway ten miles from Air force base, tapped into the Texas power grid. Gov. Abbott, you okay with this?

  19. I believe 55.6723% of deaths due to exposure to cold are caused by climate change!! All the scientists I have discussed this with totally agree with me.

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