Confirmed Cases Deceptive Practices Pandemic

Official Misinformation

Part 1:
“Slow Down the Testing”

The pandemic in mid-July, 2020, most agree, was the worst of times in the Sun Belt.  But by late August, the Trump campaign is trying desperately to convince the American public and media that, if not now quite the best of times, things are improving. 

Some states are supporting this narrative with deceptive reporting of critical COVID statistics.  Unfortunately, it’s working, providing a misleading picture of progress against this disease while endangering lives in the process.

As an example of a misleadingly optimistic report, see this extended analysis published by Will Feuer on CNBC News website on August 25.  A brief excerpt:

“Fauci’s worst fears have not come to pass as daily new cases have steadily fallen across much of the U.S….

In Florida, the daily average number of new cases has fallen from about 11,100 [per day] on July 22 to about 3,900 [per day] this week. Cindy Prins, an epidemiologist at the University of Florida, attributed much of the drop to changing behavior across the state, prompted by news coverage and effective public health messaging.” 

CNBC News, August 25, 2020

Feuer is at least somewhat aware that “Confirmed Cases” can be manipulated.  But, along with most of the MSM, he doesn’t do the work to tease apart the official truth-bending, even in a heavily reported piece.  As we’ll see, according to the numbers, changing behavior in Florida actually had very little to do with the reduction in Confirmed Cases. 

To be clear, I am not an epidemiologist.  But I am a former management consultant, who spent a fair number of years working with highly dysfunctional large corporations that in some cases institutionalized misleading reporting (Note 1).  The skills I developed then are useful here in ferreting out what’s going on with states like Florida, which is, in my opinion, publishing politically-motivated, official misinformation about the status of the pandemic.

What is a Confirmed Case?

Trump was widely ridiculed for saying the “more testing leads to more cases”.  In point of fact, it’s an accurate statement if you add one word: “more testing leads to more reported cases”.  This subtle difference seems lost on many reporters covering this story.  It’s not lost on Red governors looking to support the President’s campaign narrative.

In the situation the US finds itself today, a “Confirmed Case” is an artificial construct.  Recognize that a Confirmed Case means something far different from the common-sense meaning of the words, which would be someone sick with an “infection”.  The number of infections, estimated by the CDC and others, is likely 10x higher than the current confirmed case count.  So, of course, more testing leads to more cases

When states are acting in good faith to attack the problem, and reporting consistently, Confirmed Cases are an OK barometer for the status of the pandemic.  But, because (as we’ll see) the numbers are so easy to manipulate, it’s highly problematic if the state is acting in bad faith.

To illustrate how this works, I’m going to do a deep dive on Florida in two parts.  Part 1 will look at testing numbers.  Part 2 (which I’ll publish later this week) will take a close look at positivity (the percentage of tests confirming an infection) and how this is being manipulated.

The Undisputed Facts

In mid-July, Florida was reeling from the Pandemic.  It had assumed the mantle as COVID’s epicenter in the US from New York.  The press narrative was all about how out-of-control things were, and particularly focused on DeSantis’ mishandling of the pandemic.

By the end of August, the narrative is switching to Florida getting things under control. 

Here are the “top-line” numbers.  The week ending July 17 is arguably Florida’s worst week; while the week ending August 27 appears to show substantial, continuing improvement:

Week endingNew Cases
July 1772,730
August 2718,705

Yes, it’s true that New Cases fell by 74% between these two periods, from 10,000/day to less than 2,700 .  Most reporting goes no deeper than this.  What’s wrong with that?

A Plan to Hide the Truth?

What’s wrong is it points to a story that isn’t true.  Florida is showing slight signs of improvement, perhaps, but the pandemic is far from under control.  However, the state’s top line reporting paints a far rosier picture.  To get to the truth, you need to dig deeper and calculate some numbers yourself (something few reporters seem to do). 

In Florida’s case, you’ll want to download the daily Florida DOH County Report (Note 2).  This is the source document for the official case count, and therefore deserves close examination.  The document was originally designed so that, the number of positive tests = confirmed cases, based on the number of people tested.  Put another way, you can think of the report as driving a formula calculating Confirmed Cases as follows:

(a)  [Confirmed Cases] = [People Tested] x [% positive]           Note: “% positive” is often referred to as “Positivity”, a term we’ll adopt for the rest of this post. (a) is simply a label.

You need to dig this deep because the State of Florida plays games with its top-line positivity reporting (and publishes alternative testing counts that we’ll discuss in detail in Part 2).

For example, for the week ending July 19, the DOH Dashboard was reporting positivity as 12.73%.  However, based on the people-based testing counts provided on the County Report, the positivity was 17.89% for the week ending July 17.  We’ve adopted these County Report variables because they are the source for the underlying DOH case count.  They were also designed consistent with the methodology for case and test reporting that was recommended by the pre-politicized CDC, and which can be compared to most other states (Note 3).

By this calculation, the County Report tells you that Total People Tested fell from 406,435 during the Week ending 7/17, to 150,259 for the week of 8/27, a 63% drop!  

Feuer, in his article, is aware that Case Count is influenced by testing counts.  As he states:

While testing has declined in recent weeks, the number of new cases is falling faster than testing rates, indicating that at least some of the drop is real….

When you dive into the numbers, new cases fell by 54,025 for the weeks ending July 17 to August 27.  But, based on the formula (a), Cases would have fallen by 45,849 simply due to reduced testing numbers, even if Positivity had stayed flat.  By this reckoning, 85% of the reduction is due directly to reduced test counts! 

Week endingPositivityTotal Tests
(per 100k)
New Cases

July 1717.89%406,435 (1,973)72,730
August 2712.45%150,259 (729)18,705

Feuer doesn’t run the Florida numbers himself, and seems to accept Cindy Prins’ explanation (quoted at top) at face value, that “much of the drop” was due to changing behavior.  However, behavior impacts positivity, explaining only 15% of the drop.  The other 85% is due to the State of Florida’s testing levels.  I note that Feuer quotes Dr. Prins, an Epidemiologist at the University of Florida, indirectly, so the quote may not be accurate.  She is, however, an employee of the State of Florida.

Is there a benign explanation for cutting testing?

A positivity rate of 17.89% is dangerously high.  To be experiencing this rate and be cutting back on testing suggests either gross incompetence or callous disregard for human life (or both). 

For example, see this graph which contrasts New York’s testing history to Florida’s.  Note these are both large states (population nearly the same); both have been hit hard by the Pandemic.  New York was hit earlier, but has been the most successful state in terms of reducing new infections and caseloads.  Florida was hit later, and has done a much worse job in controlling the infection.

Once Florida’s case rate started to climb in mid-June, Florida appeared to follow the New York model, increasing testing dramatically until July 17.  However, New York has continued to increase its testing rate even as positivity has fallen to under 1%. 

By contrast, Florida began cutting the number of tests week by week starting July 18, so that by the week ending August 27th it was testing at less than half of its peak level, falling to to 44th out of 51 states (including DC). 

Even the rate of 1,973/100k that Florida was testing at the mid-July peak isn’t particularly high.  It would have ranked 8th during the week of August 27th.  The rate of 729 seems shockingly low: CA @ 5.64% tested at 1,489. 

Most of the states you see with high positivity (>10%) and low testing rates (<1,000/100k) are other states presumably supporting the “Pandemic is Over” narrative of the Trump campaign.  Texas, struggling with a similar positivity rate to Florida’s is at 14.1% positivity and is testing at 745/100k. Others, starting with the lowest testing levels, are SC @ 28.44%/292; ID @ 12.88%/735; MO @ 14.09%/766; SD @ 17.45%/851; MS @ 16.29%/899; IA @ 16.77%/903; and KS @ 10.70%/989.  The only “blue” state meeting the same criteria (positivity> 10%, testing < 1,000/100k) is NV @ 15.55%/592.

We also took a close look at Florida’s testing rate by county.  We’ll have a LOT more to say about this in Part II of this post, but we think it’s worth introducing here.  The maps show the level of testing from the County Report, expressed in Tests-per-Person / per 100,000 population for the weeks ending 7/17 and 8/27, respectively.

Click to Enlarge

On average across the entire state, the testing level fell by 63%. However, the two counties with the highest rate in the state are:

  • Leon County, where the State Capital is located, testing at 1,980/100k. The testing rate actually rose during this interval, the only county where this happened, from 1,535 during the week of July 17.
  • Alachua County, home of the University of Florida, at a rate of 1,562/100k, a reduction of less than 20% period-to-period.

It would seem the state government, while willing to endanger its citizens in support of a narrative, is taking care of itself!

Note 1:  From 1986 to 1993, I was a consultant with the New York office of McKinsey & Company.  My first engagement was with the computer division of a major company that by the accounting of the McKinsey team was losing $2 billion/year, and by the company’s books, about $300 million.  Playing games with numbers is not restricted to states.

Note 2:  The sources for most of this analysis are the Cases by County dataset published by the Florida Department of Health. This allowed me to calculate case and test reporting at a granular level for the weeks ending 7/17 and 8/27.  Not precisely the dates quoted by Feuer, but close enough. This data is archived on the University of Florida’s Florida COVID-19 Hub, which you can find here.  For the purposes of weekly totals, I downloaded tables for 7/11, 7/17, 8/21, and 8/27, to allow me to calculate the difference in cumulative totals.

Note 3: The CDC’s original, non-political guidelines recommended reporting by people tested rather than samples, recognizing that an individual can receive multiple tests prior to testing positive. When health practitioners talk about Positivity, the percentages they quote usually assume tests reported this way.  Reporting based on samples will always show a lower percentage than reporting based on people.  We’ll explain this in more detail in Part II (Florida’s alternative approach actually mixes the two methods, making it even more confusing).


Where we are now (Aug)?

“Where are we now?” is a key question, because (as I wrote here), much of the MSM is being faked out by its emphasis on “Confirmed Cases,” an easily manipulated statistic.  Many of the worst-affected states seem to be taking the President’s advice to “Slow the testing down!”.  Fewer tests translate to fewer reported cases, lightening the pressure on state governments. And because most states still aren’t reporting probable deaths (contrary to CDC guidelines), they can also conceal the resulting deaths.

So, IMO, before analyzing the status of any state, you first need to look at how much testing they’re doing, then at the Positivity Rate (the percent of administered tests showing infections), and only then at other trends.  It’s a lot more work than simply reporting on growth of Confirmed Cases.  We use the COVID Tracking Project’s state-level statistics from 8/18/20 as the source for data here.


Among hard-hit states in the “second wave”, only Louisiana and Arizona seem to be doing significantly better, while Alabama is showing signs of progress.

Louisiana Testing/Positivity
Click or drag to change chart in this group. All pandemic-sense original analysis based on Covid Tracking Project Data (8/14/20)
Arizona Positivity/Testing
Alabama Positivity/Testing

Louisiana was an early-hit state, with infections centering on New Orleans and tourist-driven transmission around Mardis Gras.

This created a big spike in April that was brought under control during lock-down.  When the state re-opened in June, infections climbed again, now state-wide, mostly outside of New Orleans.  Louisiana tackled the problem the right way by testing aggressively.  The peak infection rate is now down to 4.9% in the week ending August 18, down from 10.7%.  Louisiana is one of 22 states reporting probable deaths.

Arizona had the highest positivity rate of any state in early July.  This combined some of the highest infection rates in the country within the Navajo Nation, plus intense growth in and around Phoenix.  The current 9.3% positivity rate remains dangerously high, but clearly a huge improvement over 26.8%.  The testing rate, at under 1,000 tests/100k, seems foolishly low.

Note that the gradual reduction in tests from a peak of 1,345 to 930/100k is exaggerating the true rate of decline, if you’re looking at Confirmed Cases.  On the other hand, AZ is one of 22 states reporting probable COVID deaths.  This limits its ability to hide the reality of what’s happening in the long term, as ultimately Case Fatality Rates will start to climb precipitously if case counts are kept artificially low.

Alabama showed only a 7.7% Positivity Rate for the week ending August 18, while increasing testing to 1,730 tests/100k.  The previous week was 16.5%, and it was 19.9% the week before that; it’s promising, but too early to assume this latest progress is anything but ephemeral.

Minimal Improvement with High Infection Rates

There are seven states that have suffered very high Positivity Rates for over a month.  Some are showing minor improvement, but it’s still too little. In rough order (worst to less worse) are: Florida, Mississippi, Nevada, Idaho, Texas, Kansas, and Georgia.

Florida is probably the worst offender.  The Positivity Rate was hovering at or near 19% for a month, and started dropping ever so slowly to 16.2% in the latest week.

Original analysis based on COVID Tracking Project data.

Note that the testing rate has nearly halved over the same period: from 1,953/100k during the week ending July 14, to 1,079 in the week ending August 18.  The combined result of the slight decline in Positivity and the dramatic reduction in testing means that 7-day average of Confirmed Cases peaked on July 16 at 13,965 and by August 18 had fallen to 3,838. 

So the MSM narrative for Florida, based on “improving” Confirmed Case counts,  is seriously overstated: most of the “improvement” has been manipulated by holding down the number of tests.  With such low testing rates and high Positivity, the risk of undetected expansion of the pandemic remains extremely high.

Moreover, Florida is NOT reporting probable COVID deaths, hiding a significant number of deaths (see Is FL 5x better than NJ?).  Frankly, it’s a shit-show.  Instead of manipulating the numbers by under-testing and under-reporting, DeSantis should be trying to save lives.

While Florida is the poster-child for how to fake-out the MSM, there are another six states in similar condition. All have suffered obscenely high Positivity Rates for at least a month, and are testing too little. Of the six, Georgia is “stuck in the middle” with moderately high testing rates, and Positivity rates still above 10%. Click or slide the image below do view different states.

Mississippi Testing/Positivity
Click or drag to change chart in this group. All pandemic-sense original analysis based on Covid Tracking Project Data (8/14/20)
Nevada Testing/Positivity
Idaho Testing/Positivity
Kansas Testing/Positivity
Texas Testing/Positivity
Georgia Testing/Positivity

Getting Worse

Unfortunately, three other states are clearly worsening, and not doing enough to contain the spread.  States with similar patterns are as follows:

  • Iowa: positivity increased from 6.7% to 10.9
  • North Dakota: positivity from 3.0% to 9.9
  • Missouri: positivity from 6.1% to 10.6%
Iowa Positivity/Testing
Click or drag to change chart in this group. All pandemic-sense original analysis based on Covid Tracking Project Data (8/14/20)
North Dakota Positivity/Testing
Missouri Positivity/Testing
Click or drag to change chart in this group. All pandemic-sense original analysis based on Covid Tracking Project Data (8/14/20)

Confirmed Cases Deceptive Practices

Is FL 5x better than NJ?

President Trump loves to cite the statistic Case Fatality Rate (“CFR”) as proof the US response to the pandemic is the “best in the world”. His choice is not accidental. If you look carefully, he’s cherry-picked just about the only statistic where the US doesn’t look awful relative to most other advanced countries. He suggests this difference is because US hospitals are more effective than other countries. It’s a lie.

CFR is actually a terrible “top-line” measure for pandemic response effectiveness. The ultimate goal is to keep people from dying or becoming disabled. If you can keep people from getting sick in the first place, it’s much better than curing them, as they don’t suffer, don’t risk permanent health impairment or death, and society avoids spending resources for treatments that are no longer necessary.

If you want a single statistic to measure response-effectiveness (as Jonathan Swan pointed out in his famous HBO/Axios interview), Deaths/100,000 population is much better than CFR. But on this measure the US looks mediocre in comparison to many other countries. And you still have to take into account likely future deaths (not just those which have already occurred). Recognizing the infections are spreading in the US faster than any other advanced country, the US’ death rate is likely to end up among the worst. So, of course, Trump ignores it.

But, even setting all of that aside, the US “lead” in CFR is largely illusory. To illustrate why, we’ll contrast Florida’s CFR to New Jersey’s, a state whose battle with the pandemic resembles the pattern in many of the early-hit European countries, much more than Florida.

What is CFR?

CFR is a simple ratio: [Deaths] / [Cases]. A “naive” CFR calculation looks like this:

New Jersey15,893186,5948.5%
Source: COVID Tracking Project 08/12/2020

Calculated this way, it turns out that New Jersey has the second highest CFR in the US (after Connecticut). No wonder Trump loves to talk about Florida when he promotes his views on CFR.

Do you believe that Florida’s hospitals are 5x better than New Jersey’s in curing COVID? Or is something else going on here?

The short answer

The short answer is, “Yes! A lot of things are going on.” We’ll expand on each of these points, but here are the key explanations for the differences:

  1. Florida cases are made up of significantly younger people than New Jersey’s. This translates directly to a lower death rate.
  2. Florida’s cases are newer than New Jersey’s, so a higher percentage have yet to die.
  3. Florida is currently generating new cases at a much higher rate, temporarily lowering CFR even more.
  4. New Jersey reports both confirmed and probable COVID deaths, while Florida reports only confirmed deaths. This significantly lowers the apparent CFR for Florida.
  5. New Jersey was unlucky. Or, you could say, badly located, or made serious mistakes (really, all of the above). Given the once-in-100 year nature of this pandemic, imo, they amount to nearly the same thing.

Florida Cases are Younger

Younger people die from COVID at a much lower rate than older people. In New Jersey, 30-year-old’s died at a rate of 0.22%. Folks aged 80+ have died at a rate of 37%! (Note 1)

A major reason for Florida’s lower CFR is its median age for Confirmed Cases is about 10 years younger than New Jersey’s. As shown in the table, if we apply the New Jersey CFR for each age segment to Florida’s distribution, New Jersey’s overall CFR would decline from 7.7% (as it stood on July 30) to 4.8%.

AgeNJ CFR% NJ Cases% FL Cases
Median Age5040
Overall CFR7.7%4.8%
NJ Age Distribution of Cases and Deaths per NJ Department of Health updated 7/30/20
Florida Case Distributions from Florida Covid Action Master File 8/14/2020. FL age categories converted to NJ categories using a straight-line annual distribution within each FL age-segment.

Note that many European countries have significantly older populations than the US. It’s clear that comparing aggregate CFR from one jurisdiction to another without understanding the underlying age distribution can be very misleading.

More Florida cases haven’t yet died

As of 8/12, the average New Jersey case was 104 days old, while the average Florida case was 37 days.

Once a case shows up in the statistics, it takes a surprisingly long time for the corresponding deaths to occur and be reported. Half of case fatalities take place within 15 days from the date they’re first recorded. Add 7 days delay for the death to show up in the reports, and you’re up to 22 days for half of the deaths to be reported. The next 25% take another week, but then the final 25% trickle in over about another month. For our analysis, we assumed 100% of deaths would be counted after 57 days. (Note 2)

Based on this distribution, of the 557,000 Confirmed Florida Cases on 8/12, 201,000 (36.1%) had yet to resolve into either a death or a recovery. Contrast that to NJ where only only 9,213 (4.9%) are unresolved. Source: original analysis based on Covid Tracking Project Data from 8/12/20.

Most European countries are in a similar situation to New Jersey, with a much older set of cases, which are mostly resolved, in comparison to the US.

Florida is currently generating new cases at a high rate

While related to the previous point, a high rate of new cases also inflates the denominator of the ratio, reducing the CFR even more, albeit only temporarily. Florida added over 48,000 cases in the 7 days from 8/6-8/12: 8.6% of its total cases to date. By contrast, New Jersey added only 2,611 during the same period, 1.4% of its total.

Unlike deaths, which take a while, Florida’s 48,000 cases hit the denominator immediately, reducing apparent CFR. As long as Florida continues to add cases at a high rate, its CFR will always appear lower than its true rate.

New Jersey is experiencing the opposite phenomenon. On July 31, CFR was 7.7%. Over the next two weeks, deaths from old cases continued to trickle in, while relatively very few new cases were added. As a result, CFR increased to 8.5%.

Does that mean NJ is doing a worse job treating its COVID patients? Of course not. Anyone successfully dealing with the virus is eventually going to experience an end-phase when CFR will increase. It’s another reason why it’s stupid to rely on CFR as a sole measure of success.

Florida Doesn’t Report Probable Deaths

The CDC recommends that states report both probable and confirmed deaths in their COVID statistics. New Jersey does so, Florida does not.

What’s the difference? A “Confirmed Death” means a positive COVID test result was received. A “Probable Death” means the deceased was diagnosed by a medical professional as dying from COVID, but not confirmed by a test.

New Jersey added 1,854 probable deaths to its tally on June 25, and continues to report probables, now no differently from other deaths.

Florida does NOT follow the CDC guidelines and reports only confirmed deaths. Realize that this is part of a consistent pattern by Florida’s government to obfuscate what’s actually going on in the state. It gives them the flexibility to cut back on testing (thereby managing the apparent case growth) without CFR exploding. See our post, Faked Out, Not Fake News

To try to estimate the impact, we took a careful look at the CDC’s published “Excess Death” rates, shown in the chart below.

Excess Deaths

In the chart, each green bar represents total deaths from all non-COVID diseases for a single week, starting 1/1/2017 through 8/1/2020. The orange line shows the 95% confidence level for each date: if total deaths exceed this line, there’s less than a 5% chance that this occurred by chance. A red + on the chart means this confidence level was exceeded. The blue bars show reported COVID deaths separately, which get added to deaths from all other diseases.

Both New Jersey and Florida reported their first COVID deaths within a week of each other. Florida’s deaths stayed at a low level for a couple of months, and didn’t “take off” until after Memorial Day. Even then, the take-off appears relatively modest, a fraction of baseline.

New Jersey’s COVID deaths exploded almost immediately after the first death was recorded (so that combined deaths peaked at nearly 3x baseline).

In both states, after “take off,” you can see weeks where non-COVID deaths by themselves exceeded the 95% interval. Given the location on the timeline, these should be considered “probable COVID deaths” which weren’t included in the original COVID death counts. For Florida, we estimated 3,973 Probable Covid Deaths during 2020 through August 1 (Note 3).

However, New Jersey, following CDC guidelines, began reporting probable deaths as part of its regular reporting, adding 1,854 probable deaths on 6/25.

The different practices are obvious when you compare the CDC reported COVID deaths to those reported by the COVID Tracking Projects reports for the same date, 8/1.

CDC COVID Deaths 8/1/207,15914,140
CTP COVID Deaths 8/1/207,02215,830
Difference CDC-CTP159-1,690
Estimated Probable Deaths
not included in CTP count
Estimated Total COVID Deaths 8/110,34715,830
Ratio of CTP deaths
CTP COVID Deaths 8/128,91315,893
Adjusted [Confirmed + Probable]
Deaths 8/12
Sources: CDC Excess Deaths Associated with COVID-19
COVID Tracking Project (“CTP”)

Taken by itself, adding this estimate of Florida’s probable cases increases the CFR from 1.6% to 2.4%. Of course, it doesn’t stand alone.

NJ was Unlucky

Overall, our comparison of Florida’s vs. New Jersey’s CFR, and normalizing for age differences, is as follows:

Source of AdjustmentFloridaNew
“Naive” CFR Calculation1.6%8.5%
Adjustment for Florida age distribution-2.9%
Adjustment for newer cases0.9%0.4%
Adding in Probable Deaths0.8%
Estimated, normalized CFR3.3%6.0% original analysis

So far, therefore, we’ve brought the difference between NJ and FL from 5x to 1.8x, which is much less than before but still a big differential. Why do differences remain?

In my opinion, there are a number of factors. As we’ve seen, only some of it relates to the quality of hospital care. That said, most of Florida’s cases are hitting 70 days later than New Jersey’s. That’s an eternity in Pandemic-time, and means — all other things being equal — that survival rates probably are higher right now in Florida compared to New Jersey last April or May. New Jersey hospitals are probably doing equally well or even better, but there aren’t enough new cases to improve the CFR very much.

In addition, when you assess New Jersey, you can’t ignore that it has the highest population density of any state in the US, and is located next to New York City which started as the epicenter of the initial outbreak. Clearly, if you look at the excess death plot, there was initially much earlier community spread in NJ compared to Florida, and a much greater number of un-diagnosed cases.

Particularly bad for its impact on death rate, there was a much more extensive, early spread of the disease into NJ long term care (“LTC”) facilities.

LTC Residents (2019)71,16242,413
Licensed LTC Facilities (2019)688361
LTC Facilities with Clusters > 50 (7/12/2020)47281
Confirmed Cases in LTC Clusters (7/12/2020)4,01029,510
2019 LTC data from Kaiser Family Foundation analysis of Certification and Survey Provider Enhanced Reports (CASPER) data.
Cluster data from NY Times, 7/12/2020 as classified and geo-located by (Note 4)

In the wake of COVID-19, there’s been a good deal of finger pointing in New Jersey between state regulators and the LTC industry, suggesting poor judgements (e.g. hospitals given priority for PPE), to little oversight, and insufficient/incompetent infection management. Be that as it may, given this once-in-a-century event, it’s not unreasonable to suggest that problems were at least partly due to bad luck. How bad NJ’s situation is compared to Florida is emphasized in the map below (both states plotted to the same scale) which shows the NY Times LTC Clusters.

Overall, our hospitals and front line medical staff are doing amazing work to preserve the health of the US population. They deserve better support than they’re getting.

(Note 1) These low fatality rates should NOT suggest that it’s safe for young people to catch COVID. Long term health effects are unknown for all ages, but there is significant evidence that young people may suffer debilitating morbidities at a much higher rate than fatalities. Young people who get infected can also expand the pandemic by infecting others who are more vulnerable.

(Note 2) There is a tiny, very long tail for COVID fatalities. For analysis purposes we’ve ignored it, but anecdotal reports of people dying from COVID after illnesses lasting 90+ days are not uncommon.

(Note 3) original analysis based on CDC Florida Excess Deaths with and without COVID-19. We examined weeks where non-COVID deaths exceeded the 95% confidence interval by themselves, and estimated probable COVID deaths by calculating the difference between non-COVID deaths and the CDC’s expected deaths from all causes.

(Note 4) Pandemic Sense classified the NY Times cluster data based simply on the name of the institution. The Kaiser LTC data is undoubtedly a somewhat different universe and is not directly comparable (which is why we didn’t calculate percentages combining the two datasets).


How Hard is it to Steal a National Election by Mail?

The nationally recognized Princeton Election Consortium just published my analysis of this issue. Spoiler: it’s harder than you might think (fortunately). Click on the above links to view it on PEC’s site, or click here to download a PDF.


About Pandemic Sense

To be clear, I am not an epidemiologist or an expert in infectious disease. However, for most of my life I’ve applied numerical analysis to gaining insight and solving problems. I trust you will find my contributions here useful.

Deceptive Practices

Faked Out, Not Fake News

Why the Current Narrative that
“Florida is Improving” is a Lie

If you browsed the New York Times Coronavirus tracker on August 9 (data through 8/8/2020), you’d likely conclude that Florida is “getting better”.  After all, on the front page of the Latest Map and Case Count for the US, Florida shows up in a section called “Where new cases are decreasing”.  Click deeper to the Florida details, and you see a nice graph which indeed appears to show that cases are dropping significantly.  The obvious conclusion is the pandemic is coming under control.

Source: New York Times Website, 8/9/2020

This obvious conclusion would be wrong.  It fails to take into account that “Confirmed Cases” is an easily manipulated statistic.  Unfortunately, virtually the entire mainstream press bases its reporting on confirmed cases and is being fooled.

In Florida, as you can see in the Time’s graph, the 7-day average of Confirmed Cases peaked on July 17 @ 11,870 and dropped to 6,550 on August 8, an apparent decrease of 44.0% (See: Note 1).

Between these same dates, the 7-day average number of tests dropped 42%!  Note: [Positive Tests] = [Confirmed Cases] by definition in this Florida data.  So, if the total number of tests administered drops, and the Positive Test Rate stays the same, cases must drop.

In Florida’s case, Positive Test Rate was 17.5% on August 8 and 18.1% on July 17.  As a result, 95% of the apparent reduction in Florida cases is due simply to the reduced number of tests.  It’s why The Covid Tracking Project’s graphs for both New tests and New cases cases depict virtually identical trends during July and August (except for slightly different scaling).

Source: The Covid Tracking Project Website 8/9/2020

Thus, by any reasonable standard, the Florida pandemic remains uncontrolled and extremely dangerous.  The best you can say for it is that the Positive Test Rate is no longer climbing (albeit stabilized at a shockingly dangerous level).  

Think Florida is alone in doing this?  Think again.  We looked at every state plus the District of Columbia over the most recent 5-week period (Weeks ending July 7 through August 4).  All of the 10 states with the highest positive test-rate cut back testing during the most recent week.  This means they all reported fewer new cases than if they’d held testing levels constant. 

Contrast these states to the 10 with the lowest Positive Test Rate:  6 of these best-performing states tested the most during the latest week.  Tests/100K averaged much higher as well:  for example, NY, with a Positive Test Rate of 1.0%, tested at a rate of 2,401 tests/100K population.  This means it tested at a rate more than 100% higher than 5 of the 10 worst-performing states, and 43% higher even than GA (the most aggressive-testing state in this group).  

The fact is that every state in the worst-performing 10 cut back on testing, despite long-standing WHO protocols to increase testing when positive rates are this high.  Nine out of these worst-performing states have Republican governors.  It’s hard to credit that this behavior is an accident.  Could they be heeding the President’s advice to “Slow the testing down”?

Note 1: This calculation (and those that follow) are based on the author’s original analysis using data released by the Covid Tracking Project.  The author’s calculation of seven-day average case counts for Florida based on the Tracking Project data were identical to the NY Time’s number for August 8, and differed by a count of 5 cases (11,870 vs. 11,865) for July 17.