Information has been published in the last few days estimating a plausible scenario concerning when we actually might get vaccinated. This comes from Bob Wachter (Twitter: @Bob_Wachter), who is Chair of the UCSF Department of Medicine, and the spokesperson for their public information project which is attempting to fill the vacuum created by a highly politicized CDC (which would normally publish such info). Full Twitter thread here.
The first chart depicts the number of US persons who would receive priority under two different vaccination prioritization schemes. The analysis takes into account that some people can be counted in multiple buckets (e.g. some front line Health Care Workers are over 65 with one of more comorbidities). So they get counted the first time they show up in the prioritization list, and aren’t double-counted when they would otherwise show up in a lower priority group (e.g. one comorbidity).
Personally, I think I would be counted in the one comorbidity bucket (high blood pressure), which means my cohort is 60 million people in the US population, and would get priority from roughly the 70th million person to the 130th million person under either of these schemes.
The next chart shows the USCF’s best estimate of US vaccination administration potential, assuming Pfizer and Moderna both scale up quickly, including the benefits of project Warp Speed.
They’re assuming administration of 25 million vaccinations per month, which suggests my personal (guesstimated) cohort would start getting vaccinated in mid- to late March, and be completed sometime in May. Note that both the Pfizer and the Moderna vaccine require two shots, spaced roughly 3-weeks apart. It’s likely that additional suppliers could join the party, but by definition, they’ll impact the back-end of this graph, not the front-end.
I’ve been quiet for the past month. In part because I was busy, and in part because I was tired of reporting on states manipulating their case counts by suppressing testing.
In the last few weeks, judging from the national news, there’s been a spike in cases nationally despite this gamesmanship. Frankly, it was kind of inevitable, though I wasn’t sure it would be obvious prior to the election.
It’s an easily knowable number, so this morning I spent a couple of hours calculating it.
All calculations are based on the Covid Tracking Project’s data. For this purpose I compared the latest 2-week period (10/24 to 10/10) to the prior 2-week period (10/09 to 09/25). My original scope for this analysis was the 50 states plus DC. However, there were some unusual adjustments that distorted the results for Hawaii and Missouri during this period, so I eliminated them.
Here’s what happened: Latest 2 weeks v Prior 2 weeks for 48 states + DC (excluding HI and MO)….
Total Tests: 12.9 million v 11.9
Positive tests (new cases): 817,309 v 597,073
Positivity (positive tests/(total tests-pending)): 6.3% v 5.0%
Period over period increase: 220,236 Increase due to Positivity increase: 165,770 Increase due to Testing increase: 54,466
Overall there are 17 states with a positivity rate >10%. Of these, only one state (Wisconsin) showed a decrease in positivity between the two periods. The state with the highest positivity in the current period is ND, at an astonishing 41.9%.
20 states experienced positivity between 5.0% and 10%. Only two (DE & OR) experienced a decrease between the two periods.
The Twitter thread I referenced above has 5 clips from the Meadows interview. It’s clear that the administration has completely surrendered any pretense of trying to control the pandemic, short of a vaccine.
Florida’s peak week for the number of tests and new cases ended on July 17. Even though Positivity on that week was a staggering 19.0%, which screams-out for additional testing, the state cut back on test counts the next week, and for the next five consecutive weeks. Between July 17 and August 28, weekly testing levels dropped by 60%.
It wasn’t until the week ending September 5, in the face of increased positivity, that Florida’s testing counts increased, but modestly, still 53% below the July 17 peak.
Trump has been widely ridiculed in the press for saying that “more testing leads to more cases”. In the common sense meaning of these words that may seem like a stupid statement, but add one word and it becomes completely true: “more testing leads to more reported cases”.
In this post we’re going to estimate the impact of Florida’s decision to cut testing counts in reducing the Confirmed Case count. Here we calculated an alternative scenario where testing remained at the July 17 levels. As you can see in the chart, Floridas actual testing peaked at 459,151, and dropped steadily to 180,465 for the week ending 28 August, and then increased slightly to 216,130.
If Florida had maintained peak testing levels, how many additional cases does this add? That depends on the Positivity Level, i.e. the percent of people tested who test positive. We calculated using the CDC recommended methodology (see this post for a deep dive on how Florida plays games with the Positivity Level it reports on its dashboard).
To estimate additional Cases, we need to estimate the positivity level on the incremental tests. Generally speaking, when the number of tests goes up, you expect the positivity level to go down somewhat, on the theory that the sickest people tend to get tested first, so that additional tests hit a slightly healthier population.
In Florida’s case, this hasn’t always been true. Florida allocates tests not by need, but by county population. This means that tests don’t flow preferentially to the counties with the highest infection rate. Indeed, in a recent county level analysis, we discovered that the counties with the lowest Positivity Rate were actually testing more than the counties with the highest rates. (see Table 2 in this post). Were Florida to increase testing and change its allocation policies so that counties with higher positivity rates received more tests, there’s a reasonable chance Florida’s average Positivity rate would actually increase even as testing counts increased.
Nevertheless, we think it’s unlikely that Florida would change its allocation methods to one that would increase reported case counts. As a result, we decided to assume a similar allocation based on county population alone, and estimated the Positivity as as shown in Figure 2.
The Scenario Estimate in Figure 2 is calculated as follow:
The original tests are carried forward at the observed Positivity rate
Incremental tests within the scenario are estimated at a lower Positivity rate that decreases 10% for each 10% increment over the number of actual tests. In other words, the first 10% of incremental tests (as a % of actual tests for the week) are carried forward at 90% of the observed Positivity rate, the next 10% at 80%, and so forth.
As shown in Figure 3, for the week ending 8/28, the state actually tested only 180,645 people (with a reported Positivity Rate of 12.5%). In our scenario, we “tested” an additional 276,626 and calculated an incremental Positivity rate of 8.0% using our formula. This converted to a total of 459,151 tests at an average positivity rate of 9.8%.
Overall, in the 7 weeks since the peak week of July 17, the State of Florida reported 318,626 cases, instead of the 463,454 we estimated would have been generated had testing levels remained constant. This means that Florida under-reported new cases by more than 46%.
Based on this analysis, there remains some improvement in Florida’s situation. But it’s not nearly as large as normally reported. Note that the lower case count will ripple into other parts of the reporting. In particular, deaths resulting from cases that are not confirmed will NOT be reported in Florida’s official COVID counts, as Florida (contrary to CDC recommendations) does not report probable COVID deaths.
My dad, who’s a holocaust survivor, and 97 years old, curates a blog for his independent living community about current politics. Yesterday he sent me this note. This is my reply to him.
Sections in italics are direct quotes from Scot Atlas’ op-ed piece in the Hill. Given Atlas’ position, this has to be taken as something pretty close to the “official” policy of the Trump Administration and why it’s safe now to reopen the schools (this post will make a lot more sense if you read it first).
My response follows:
We know who is at risk. Only 0.2 percent of U.S. deaths have been people younger than 25, and 80 percent have been in people over 65; the average fatality age is 78. A JAMA Pediatrics study of North American pediatric hospitals flatly stated that “our data indicate that children are at far greater risk of critical illness from influenza than from COVID-19.”
Death is not the only metric. There clearly are pediatric complications of COVID at an unknown incidence. See, for example this article: https://undark.org/2020/09/02/kids-covid-19-long-haulers/ . This is like suggesting to parents “Don’t worry about preventing your kids from catching Lime Disease. No one dies of Limes”.
Kids are contagious to adults, and are frequently low- or non-symptomatic. Kids catching COVID at school are a perfect vector to bring COVID home and getting adults in the household sick.
While we saw more cases in July and August, we are not seeing the explosion of deaths we saw early on. An analysis of CDC data shows that the case fatality rate has declined by approximately 85 percent from its peak.
Again, a focus on death. See above.
CFR is a truly stupid way to judge the effectiveness of the Administration’s response. It’s much better to keep people from getting sick in the first place. The administration focuses on it because it’s the only measure where the US doesn’t look awful.
CFR is substantially understated in the US compared to other countries because, among other issues, our cases are newer and people haven’t had time to die yet. For example, last month the average case in Florida was 37 days old.
“Peak” CFR is presumably referring to the “bad old days” of April and May when NJ and NY were experiencing so many deaths. Those states did a terrible job keeping COVID out of nursing homes. Lower CFR today is significantly because of a younger population in hospitals. Treatments are better, but not 85% better.
Note also that many red states are skimping on testing (to reduce case counts), and not reporting probable deaths. For many states, particularly Florida and other Sun Belt states, the reality is currently worse than it seems. See my piece: Official Misinformation.
We are doing much better with treating hospitalized patients. Lengths-of-stay are one-third the rate in April; the fatality rate in hospitals is one-half of that in April. Fewer patients need ICUs if hospitalized, and fewer need ventilators when in ICUs.
I suspect a lot of this ties to the fact that a much higher % of cases are now younger (including share of hospitalized patients)
Again the emphasis only on acute illness and death. Most “long haulers” never see a hospital. Again, should we ignore Lime Disease because fewer folks end up in the ICU? The administration’s policies are infecting millions of people. I suspect we’ll be paying the cost in disabilities and increased health care costs for decades. Similar to Opioid Addiction, Diabetes, and Obesity, add COVID to the list of devastating morbidities.
We are progressing at record speed with vaccine development. This is due to eliminating bureaucracy and working in partnership with America’s world-leading innovators in the private sector.
True-ish. However, to be useful in re-opening schools now, we’d need a vaccine now, not next year, which is the earliest it could be delivered in quantity, even if the “end of October” date is real. Frankly, the idea that you can reopen schools now, with limited testing, and high community infection rates is delusional. Especially when many students don’t even think COVID is real. It would be much better to wait for the vaccine to become available before reopening the schools for in-school instruction, especially without adequate testing. Otherwise you risk killing off your most experienced teachers and sickening a generation of parents.
Third, we are leveraging our resources to guide businesses and schools toward safely reopening with commonsense mitigation measures. We must safely reopen schools as quickly as possible, and keep them open. The harms to children from school closures are too great to accept any other outcome.
Same problem as just noted. In many states, positivity rates (when calculated properly) remain above 10%. Florida, for example, is claiming a Positivity rate of 5.83% for the week of 8/23, when the real rate (calculated according to CDC guidelines) was in fact 13.9%. Many of the states most anxious to reopen have positivity rates above 10%. See: https://pandemic-sense.com/2020/09/03/official-misinformation-2/
With this level of infections, I don’t believe any schools will be able to stay open long.
For in-school to work, you need, at minimum, vaccinated teachers and staff, mask mandates, and instant testing available as needed. None of that is required in the current CDC guidelines. Until those elements are available, I believe Atlas is playing politics with the lives of students, teachers, and school staff.
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:
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!
Total Tests (per 100k)
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.
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 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 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.
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.
Unfortunately, three other states are clearly worsening, and not doing enough to contain the spread. States with similar patterns are as follows: