Canada2017 said:

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Horrible that ANYONE is keeping a political scorecard about people's suffering in the middle of a pandemic.

People have lost all sense .

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Only dudes like you who don't want to find out what we need to do to stop this from killing more ppl and do it

Wallace said:

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Canada2017 said:

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Horrible that ANYONE is keeping a political scorecard about people's suffering in the middle of a pandemic.

People have lost all sense .

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Only dudes like you who don't want to find out what we need to do to stop this from killing more ppl and do it

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This is a POLITICAL scorecard .

LOL. I needed a good belly laugh.

midgett said:

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Booray said:

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I have seen several comments about Red v Blue results, usually referring to death totals or deaths per capita. Was wondering how to measure a state's performance. No perfect method really, but in my mind population density is the real driver of corona risk. The more spread out you are, the easier it is to control the risk. So I measured how each state's per capita death toll ranked v. its population density rank. If a state ranked 10th in population density but 15th in per capita death toll it was 5 spots better than expected; the reverse being true if it was 5th in per capita death toll.

Here is how the states have performed to date against expectations, with states characterized as red or blue based on the affiliation of their governor (we have 25 Democrat and 25 Republican governors) Congrats to Hawaii and condolences to New Mexico.

HI +37 Blue
TN +19 Red
FL +17 Red
CA +17 Blue
NC +16 Blue
WV +15 Red
TX +13 Red
KY +11 Blue
OH +10 Red
SC +9 Red
VA +8 Blue
VT +8 Red
OR +7 Blue
WI +6 Blue
MD +4 Red
DE +4 Blue
ME +4 Blue
RI +3 Blue
UT +3 Red
PA +1 Blue
MA +1 Red
WA +1 Blue
AR +1 Red
NJ -- Blue
OK -- Red
ID --Red
MT --Blue
GA -1 Red
CT -1 Blue
WY -2 Red
AK -2 Red
MO -3 Red
AL -4 Red
IL -4 Blue
NY -5 Blue
IA -6 Red
KS -6 Blue
MI -11 Blue
SD -12 Red
ND -12 Red
IN -12 Red
NE -13 Red
MN -13 Blue
AZ -14 Red
NV -17 Blue
LA -18 Blue
MS -19 Red
CO -23 Blue
NM -25 Blue

Of the 27 states that met or bettered expectations, 15 of them had blue governors and 2 of the reds (Ohio and Maryland) imposed pretty stringent measures. On the other hand, my method does not take into account margin of victory or loss, I suspect that NY and NJ actually performed worse than the stats show. Hawaii had the natural advantage of being an island; many of the Northern Plains states suffered from meat plant outbreaks in otherwise sparsely populated areas. California and Florida took wildly different routes and ended up in the same place.

My rough take is that what the scientists have said all along is true: the virus has no respect for politics.It looks to me to be a pretty even scorecard. Of course we are not near finished yet.

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With all due respect, okay with a little respect, that's a faulty analysis.

One you are using a % and then combining with an ordinal number.

NY City/Jersey City and Newark are all considered one metro area. One area of density. It's the largest by far in the US with 19+ million people. That accounts for much of the population of the TWO states with the two highest death counts. It also includes a bit of PA.

Texas has a population of over 27 million people. DFW and Houston areas account for nearly 15 million and Austin and San Antonio areas account for nearly 5 million more. The population density is still higher in NY/NJ but 75% of the Texas population are in those 4 areas alone. The rest include bunches in El Paso, Waco, Amarillo, Elm Mott, Lubbock, Corpus, Laredo, etc. The population density of most of Texas is very low. It's like you are comparing Albany, NY with Big Bend Monument.

We can go down your list and do similar exercises for Tennessee (Knoxville, Memphis, Nashville, Chattanooga), North Carolina (Triangle, Charlotte, Winston Salem, Asheville), etc.

Your analysis is very faulty.

---

It wasn't intended as a dissertation or a peer-reviewed published paper. And the major "flaw" you mention regarding the population density around NYC is something I alluded to in explaining why the model was far from perfect.

But it is instructive. It is a rough gauge of how well governors have handled thinks adjusted for what I view as the primary differentiator for the spread of the virus. Greg Abbott is governor of all of Texas, the densely and sparsely populated parts. His focus needs to be keeping the virus contained in the densely populated areas, something until two weeks ago he had done very well. That is why the ranking gives him credit.

Rough gage may be a fair description.

The problem with combining % and ordinal is the potential gaps between places. There won't be a equal % difference between places yet you are using a % to rank. What if the difference between 6th and 18th is really tight while the difference between 18th and 19th is larger than the difference between 6th and 18th? If you account for that, then we're talking.

midgett said:

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Rough gage may be a fair description.

The problem with combining % and ordinal is the potential gaps between places. There won't be a equal % difference between places yet you are using a % to rank. What if the difference between 6th and 18th is really tight while the difference between 18th and 19th is larger than the difference between 6th and 18th? If you account for that, then we're talking.

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You are correct, but I have to work also.

quash said:

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RD2WINAGNBEAR86 said:

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The only thing gonna kill this Coronavirus Armageddon is the election on November 3rd. If Americans can feed their families and survive til then, we will be fine. God Bless America. My heart goes out to all Americans that have had their lives and careers destroyed by the coronavirus response. Just hang on! Better times ahead.

---

Delusional in the extreme.

I keep seeing this stated as though it means something. The only possible explanation is that Covid19 is a hoax.

That's TDS. And wrong.

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What would Ron Paul say? Isn't ole Ron not only a physician but an icon of the Libertarian Party?

whiterock said:

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quash said:

---

RD2WINAGNBEAR86 said:

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The only thing gonna kill this Coronavirus Armageddon is the election on November 3rd. If Americans can feed their families and survive til then, we will be fine. God Bless America. My heart goes out to all Americans that have had their lives and careers destroyed by the coronavirus response. Just hang on! Better times ahead.

---

Delusional in the extreme.

I keep seeing this stated as though it means something. The only possible explanation is that Covid19 is a hoax.

That's TDS. And wrong.

---

CV is not a hoax.
The histrionic reaction to it is.

---

And you think the reaction stops cold on election day?

Why is death rate (deaths/cases) by state not a more effective measure of performance?

ATL Bear said:

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Why is death rate (deaths/cases) by state not a more effective measure of performance?

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Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

Booray said:

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ATL Bear said:

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Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

Booray said:

---

ATL Bear said:

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Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Both are taken into account because both are part of the equation, and at the end of the day the survival outcome is really all that matters at far as performance.

Osodecentx said:

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Booray said:

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ATL Bear said:

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Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Are you mocking me? J/k.

ATL Bear said:

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Booray said:

---

ATL Bear said:

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Both are taken into account because both are part of the equation, and at the end of the day the survival outcome is really all that matters at far as performance.

---

I must be missing something in your question.

I assume you feel that the lower the death rate the better? If so, assume two identical states each with a population of 100.

State A has one case and that patient dies for a death rate of 100%.

State B has 50 cases and 25 die for a death rate of 50%.

Would you rather live in the state with the better death rate of 50%.

Booray said:

---

ATL Bear said:

---

Booray said:

---

ATL Bear said:

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Both are taken into account because both are part of the equation, and at the end of the day the survival outcome is really all that matters at far as performance.

---

I must be missing something in your question.

I assume you feel that the lower the death rate the better? If so, assume two identical states each with a population of 100.

State A has one case and that patient dies for a death rate of 100%.

State B has 50 cases and 25 die for a death rate of 50%.

Would you rather live in the state with the better death rate of 50%.

---

No one would draw any conclusions with such a small subset of data, so your example is moot. You start with an assumption about how much land area a state has matters relative to virus performance, when populations within states always have concentrated densities. Sort of a random evaluation factor. To put it in perspective, if Rhode Island would have lost the same number of people to Covid as NY, they would have finished ahead of NY on your rankings despite those deaths equaling 3% of their entire state population.

EDIT: if you asked me, not that you are, a performance factor could be cases per capita plus the death rate (cases/deaths). That would evaluate infection spread/prevention and treatment/outcome.

ATL Bear said:

---

Osodecentx said:

---

Booray said:

---

ATL Bear said:

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Are you mocking me? J/k.

---

Great minds & such

ATL Bear said:

---

Booray said:

---

ATL Bear said:

---

Booray said:

---

ATL Bear said:

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Both are taken into account because both are part of the equation, and at the end of the day the survival outcome is really all that matters at far as performance.

---

I must be missing something in your question.

I assume you feel that the lower the death rate the better? If so, assume two identical states each with a population of 100.

State A has one case and that patient dies for a death rate of 100%.

State B has 50 cases and 25 die for a death rate of 50%.

Would you rather live in the state with the better death rate of 50%.

---

No one would draw any conclusions with such a small subset of data, so your example is moot. You start with an assumption about how much land area a state has matters relative to virus performance, when populations within states always have concentrated densities. Sort of a random evaluation factor. To put it in perspective, if Rhode Island would have lost the same number of people to Covid as NY, they would have finished ahead of NY on your rankings despite those deaths equaling 3% of their entire state population.

EDIT: if you asked me, not that you are, a performance factor could be cases per capita plus the death rate (cases/deaths). That would evaluate infection spread/prevention and treatment/outcome.

---

The example isn't moot. If it was you would not have suggested an alternate to measure the prevention of spread, which is what the example illustrated. I could change the example by adding 5 zeros to the end of each number and 10 more states with different fractions. It would no longer be a small data set and it would show exactly the same thing.

Your suggestion is a good one but it also has two flaws. First, I was looking for one number as a metric not multiple. To get a ranking out of your suggestion one would have to decide the relative importance of the two factors.

Second, and to the point of my OP, there is a degree of difficulty factor. People argued against a nationwide lock down--correctly in my view--that "Montana is not like New York." What did they mean by that? They meant that because Montana was not as densely populated as New York, the risk of community spread was much lower. In judging the relative performances of Steve Bullock and Andrew Cuomo it is disingenuous to ignore that difference.

Just using cases per capita ignores that degree of difficulty factor on the prevention of spread component.

I understand that the method I used is imperfect. If my 100 person states are set up so that one has two towns of 10 and 90 people and one has 50 towns of 2 people but each state has the same land mass, the states have the same density but the risk of spread across all 100 people is much greater in the first.

But my computation at least attempts to account for all three factors: deaths per capita inherently includes spread and the efficacy of treatment, then adjusted for density.

Booray said:

---

ATL Bear said:

---

Booray said:

---

ATL Bear said:

---

Booray said:

---

ATL Bear said:

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Both are taken into account because both are part of the equation, and at the end of the day the survival outcome is really all that matters at far as performance.

---

I must be missing something in your question.

I assume you feel that the lower the death rate the better? If so, assume two identical states each with a population of 100.

State A has one case and that patient dies for a death rate of 100%.

State B has 50 cases and 25 die for a death rate of 50%.

Would you rather live in the state with the better death rate of 50%.

---

No one would draw any conclusions with such a small subset of data, so your example is moot. You start with an assumption about how much land area a state has matters relative to virus performance, when populations within states always have concentrated densities. Sort of a random evaluation factor. To put it in perspective, if Rhode Island would have lost the same number of people to Covid as NY, they would have finished ahead of NY on your rankings despite those deaths equaling 3% of their entire state population.

EDIT: if you asked me, not that you are, a performance factor could be cases per capita plus the death rate (cases/deaths). That would evaluate infection spread/prevention and treatment/outcome.

---

The example isn't moot. If it was you would not have suggested an alternate to measure the prevention of spread, which is what the example illustrated. I could change the example by adding 5 zeros to the end of each number and 10 more states with different fractions. It would no longer be a small data set and it would show exactly the same thing.

Your suggestion is a good one but it also has two flaws. First, I was looking for one number as a metric no multiple. To get a ranking out of it, one would have to decide the relevant importance of the two factors.

Second, and to the point of my OP, there is a degree of difficulty factor. People argued against a nationwide lockdowncorrectly in my viewthat "Montana is not like New York." What did they mean by that? They meant that because Montana was not as densely populated as New York, the risk of community spread was much lower. In judging the relative performances of Steve Bullock and Andrew Cuomo it is disingenuous to ignore that difference.

Just using cases per capita ignores that degree of difficulty factor on the prevention of spread component.

I understand that the method I used is imperfect. If my 100 person states are set up so that one has two towns of 10 and 90 people and one has 50 towns of 2 people but each has the same land mass, they have the same density but the risk of spread across all 100 people is much greater in the first.

But my computation at least attempts to account for all three factors: deaths per capita inherently includes spread and the efficacy of treatment, then adjusted for density.

---

It wasn't "Montana is different from New York" because of land size or density, it's because they didn't have a raging outbreak. They could just as easily have an outbreak in Bozeman or Missoula or Helena and it would require action. The same was for Texas. They weren't having an outbreak at the time, so that is the motivation for the different treatment. It would have been reflected had an outbreak started, and the smaller numbers would have had an exponential impact compared to other population bases. It almost sounds if you're trying to build an excuse for populated metropolitans, but ratio stats are intended to cut through that.

Regarding your example, if you added multiple zeroes to your sample set, that makes a huge difference because even if you kept the same outcomes you would have a location where 100% of the patients are dying and 50% in the other, so of course you'd say the latter is doing better. 100% of a thousand is much worse than 100% of 1.

Your model tells us nothing other than an attempt to try to affirm your thoughts on population density as some prime factor. While it may have more people to get infected, it's also easier to consolidate resources as well as enforce and role out prevention measures to a maximum amount of people. Population density is measured by people per kilometer or square mile. So you could have the most densely populated city in a large state and it wouldn't be reflected the same as you appear to be arguing. That's why I said land, not people, are the driving factor. I used the RI example as a counter, but there are several others that look very odd, and don't really seem to reflect any logical measure of comparative performance.

My example is to COMBINE both the cases per capita and the death rate for a score you could rank by state. That would address both spread and effective treatment. I still think death rate is the most effective and objective, but by adding the case per capita you increase the understanding of infection management. Since both factors have equal value across the comparison and for each state as a score component you don't really need a value equalizer, unless you're saying deaths matter more than cases, which would bring us back to just using the death rate.

If you wanted to go even more technical you could take the testing ratio and deduct it from the score as a viral "visibility" factor. Those who exceeded national averages would have their score reduced, and those who didn't would have their score increased. The main reason against this factor is testing numbers aren't that reliable for a number of factors.

[img][url=https://ibb.co/f2sfDHm][/url] image upload[/img]

For context, here is what the author of the chart says in explanation

Using "cases" as a headline number, which the media has done lately, gives very little information about how well or poorly those cases are being handled. A better metric is the Case Fatality Rate (CFR), which is deaths divided by confirmed cases. CFR measures the percentage of people in a state who've tested positive for COVID that actually end up dying from it.

A high fatality rate can be caused by several factors.
Failing to protect older populations. States with a high percentage of older residents are at greater risk of deaths. How well a state protects its older population is a key to keeping the death rate down.
Not enough testing. States that don't have enough testing not only reduce the denominator in the Case Fatality Rate calculation, they also leave more people uncertain about whether they are infected. People unknowingly infected may be at a greater risk of infecting at-risk populations like the elderly.

While infinitely better than using "cases" to judge how a state is handling the coronavirus outbreak, CFR is still not a perfect measure.

CFR can be skewed if deaths are undercounted or overcounted. For example, if a death is counted as a COVID death just because the person tested positive for it, despite the fact that the person's primary cause of death was something else, it's not an accurate count. But, since so many elderly patients have comorbidities such as diabetes and hypertension, determining the cause of death can be difficult.

Also, the Case Fatality Rate only counts cases that have been confirmed through testing. A different measure, the Infection Fatality Rate (IFR), calculates the fatality rate based on estimates of the TOTAL number of infected people, not just those who have been tested. Antibody testing has found that the actual number of infected people is as much as ten times higher than the confirmed cases, meaning the IFR may be ten times lower than the CFR numbers listed here.

Still, disparities between states will exist no matter the measure used. Probably the most important factor that has led to disparities in death rates is whether states were able to "flatten the curve" by protecting the vulnerable in the early months of the outbreak. Most of the states with the worst Case Fatality Rates had bad outbreaks among the elderly early on.

States that kept fatalities low during the spring, meanwhile, are benefiting from several factors keeping their fatality rates down. As recent research from JP Morgan says, ".. we do not see cases in southern/western states resulting in mortality rates similar to those observed in the Northeast during March and April. likely due to a larger % of mild and asymptomatic cases, a younger average age, better treatment, and more testing."

While deaths and rates will likely rise in states that have not developed much in the way of herd immunity, the above factors will hopefully keep the CFR significantly lower.

quash said:

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whiterock said:

---

quash said:

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RD2WINAGNBEAR86 said:

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The only thing gonna kill this Coronavirus Armageddon is the election on November 3rd. If Americans can feed their families and survive til then, we will be fine. God Bless America. My heart goes out to all Americans that have had their lives and careers destroyed by the coronavirus response. Just hang on! Better times ahead.

---

Delusional in the extreme.

I keep seeing this stated as though it means something. The only possible explanation is that Covid19 is a hoax.

That's TDS. And wrong.

---

CV is not a hoax.
The histrionic reaction to it is.

---

And you think the reaction stops cold on election day?

---

Won't stop cold, just fade to the back page.

TN cases peaked 6/29, and the 7-day case average peaked 7/5. Time will tell if there is another leg up.

The new hospitalization 7-day average peaked 7/3.

Still in Phase 2 of re-opening

ATL Bear said:

---

Booray said:

---

ATL Bear said:

---

Booray said:

---

ATL Bear said:

---

Booray said:

---

ATL Bear said:

---

Why is death rate (deaths/cases) by state not a more effective measure of performance?

---

Depends what you are measuring; what you suggest would heavily weight the performance of the state's medical system v. Prevention.

---

Both are taken into account because both are part of the equation, and at the end of the day the survival outcome is really all that matters at far as performance.

---

I must be missing something in your question.

I assume you feel that the lower the death rate the better? If so, assume two identical states each with a population of 100.

State A has one case and that patient dies for a death rate of 100%.

State B has 50 cases and 25 die for a death rate of 50%.

Would you rather live in the state with the better death rate of 50%.

---

No one would draw any conclusions with such a small subset of data, so your example is moot. You start with an assumption about how much land area a state has matters relative to virus performance, when populations within states always have concentrated densities. Sort of a random evaluation factor. To put it in perspective, if Rhode Island would have lost the same number of people to Covid as NY, they would have finished ahead of NY on your rankings despite those deaths equaling 3% of their entire state population.

EDIT: if you asked me, not that you are, a performance factor could be cases per capita plus the death rate (cases/deaths). That would evaluate infection spread/prevention and treatment/outcome.

---

The example isn't moot. If it was you would not have suggested an alternate to measure the prevention of spread, which is what the example illustrated. I could change the example by adding 5 zeros to the end of each number and 10 more states with different fractions. It would no longer be a small data set and it would show exactly the same thing.

Your suggestion is a good one but it also has two flaws. First, I was looking for one number as a metric no multiple. To get a ranking out of it, one would have to decide the relevant importance of the two factors.

Second, and to the point of my OP, there is a degree of difficulty factor. People argued against a nationwide lockdowncorrectly in my viewthat "Montana is not like New York." What did they mean by that? They meant that because Montana was not as densely populated as New York, the risk of community spread was much lower. In judging the relative performances of Steve Bullock and Andrew Cuomo it is disingenuous to ignore that difference.

Just using cases per capita ignores that degree of difficulty factor on the prevention of spread component.

I understand that the method I used is imperfect. If my 100 person states are set up so that one has two towns of 10 and 90 people and one has 50 towns of 2 people but each has the same land mass, they have the same density but the risk of spread across all 100 people is much greater in the first.

But my computation at least attempts to account for all three factors: deaths per capita inherently includes spread and the efficacy of treatment, then adjusted for density.

---

It wasn't "Montana is different from New York" because of land size or density, it's because they didn't have a raging outbreak. They could just as easily have an outbreak in Bozeman or Missoula or Helena and it would require action. The same was for Texas. They weren't having an outbreak at the time, so that is the motivation for the different treatment. It would have been reflected had an outbreak started, and the smaller numbers would have had an exponential impact compared to other population bases. It almost sounds if you're trying to build an excuse for populated metropolitans, but ratio stats are intended to cut through that.

Regarding your example, if you added multiple zeroes to your sample set, that makes a huge difference because even if you kept the same outcomes you would have a location where 100% of the patients are dying and 50% in the other, so of course you'd say the latter is doing better. 100% of a thousand is much worse than 100% of 1.

Your model tells us nothing other than an attempt to try to affirm your thoughts on population density as some prime factor. While it may have more people to get infected, it's also easier to consolidate resources as well as enforce and role out prevention measures to a maximum amount of people. Population density is measured by people per kilometer or square mile. So you could have the most densely populated city in a large state and it wouldn't be reflected the same as you appear to be arguing. That's why I said land, not people, are the driving factor. I used the RI example as a counter, but there are several others that look very odd, and don't really seem to reflect any logical measure of comparative performance.

My example is to COMBINE both the cases per capita and the death rate for a score you could rank by state. That would address both spread and effective treatment. I still think death rate is the most effective and objective, but by adding the case per capita you increase the understanding of infection management. Since both factors have equal value across the comparison and for each state as a score component you don't really need a value equalizer, unless you're saying deaths matter more than cases, which would bring us back to just using the death rate.

If you wanted to go even more technical you could take the testing ratio and deduct it from the score as a viral "visibility" factor. Those who exceeded national averages would have their score reduced, and those who didn't would have their score increased. The main reason against this factor is testing numbers aren't that reliable for a number of factors.

---

I wasn't trying to prove or affirm that population density is a major driver in Covid spread, I was trying to measure performance assuming that it was. Sorry if that wasn't clear.

Here is a study that supports that assumption: https://www.medrxiv.org/content/10.1101/2020.06.12.20130021v1.full.pdf

Actually not a lot of literature on the subject and some of it distinguishes between the actual density and the amount of "connectiveness.," the latter being the concept of how much the hub interacts with the surrounding areas. Both factors seem to increase the chances of exponential growth, but as you say they also increase the chance that the area has adequate resources and systems to deal with a pandemic.

Given that, my hypothesis would be that cases per capita would advantage less densely populated states because they had an easier time limiting spread while death rate should favor more densely populated states based on better/more available medical. But even the best medical in a city experiencing rapid growth early int he pandemic and with an older population might rate worse than a poor medical confronting a slower rise later in the pandemic with a younger population.

This is what I really know: I wish I was putting this much effort into a statistical analysis of why BU should have one of the 4 CFB Playoff spots. But I think Covid is going to take that away too.

whiterock said:

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quash said:

---

whiterock said:

---

quash said:

---

RD2WINAGNBEAR86 said:

---

The only thing gonna kill this Coronavirus Armageddon is the election on November 3rd. If Americans can feed their families and survive til then, we will be fine. God Bless America. My heart goes out to all Americans that have had their lives and careers destroyed by the coronavirus response. Just hang on! Better times ahead.

---

Delusional in the extreme.

I keep seeing this stated as though it means something. The only possible explanation is that Covid19 is a hoax.

That's TDS. And wrong.

---

CV is not a hoax.
The histrionic reaction to it is.

---

And you think the reaction stops cold on election day?

---

Won't stop cold, just fade to the back page.

---

Only if some larger story presents itself. You'll notice that "Black people tryna kill us!!" couldn't knock Covid off the front page. It would take something like "Trump voids electoral college results, refuses to leave office" for Rona to get relegated

So you may be right. He's already gaslighting vote by mail for cover in his campaign lit.