COVID Update – Nov. 27, 2020

First, I would like to thank everyone who read and commented on my last update. I have to say, I was totally bowled over by the response. At my age, I’m not a social media oriented guy. I deleted my FB account years ago. I have no Twitter account. I was kicked out of NextDoor by Trumpers who said I was an advocate of “cancel culture.” And I use my private Instagram exclusively for pictures of my family and closest friends.

That leaves Reddit, and although I perfectly aware the platform has been used to host some of the vilest elements of our society, the sub-reddits I post on are filled with friendly, informed, and all around terrific people. I’m someone who’s surprised at getting 100 people to like what I’m doing, let alone over 2,000. Along with that came hundreds of great comments, and if I didn’t acknowledge yours, please forgive me. I had a hard time keeping up that day!

There were some very good issues raised and even some challenges. Here are some of the main ones:

  • What is the effect of testing on the case rate? How are we doing with testing, anyway?
  • Are viral load and severity of illness really correlated? Do masks really reduce viral load? This was not raised by an anti-masker, but by a redditor who was genuinely questioning my assertion that these were accepted facts.
  • Why is the rate of increase in cases so severe this time? While this was superficially addressed, it’s probably worth examining more.

This post will contain the usual case updates for SD, LA, and OC. It will also have some info on hospitalization rates. And finally, I’ll try to answer the above questions to the best of my ability.

A few people asked about my credentials, so once again, I’ll reiterate that I’m not a medical expert, or an epidemiologist, or a statistician (LA mod’s bestowal of that title on me to the contrary notwithstanding), or an authority on anything, really. If I have a special skill, perhaps it’s communicating the consensus of experts in a field. So let’s call me an amateur science communicator – amateur, because I certainly don’t take any money for what I do, and when people do offer me that, I direct them to the Equal Justice Initiative. I try to be accurate, but occasionally I do err. When that happens, I depend on you, my readers, to point that out, and you have. Any advocate of scientific skepticism, as I am, is glad for that; it’s part of the corrective process of science and science communication.

Now, onto the current data!

Case Rates

Here’s an interesting tool that lets you assess the risk level of attending an event. The risk level is the estimated chance (0-100%) that at least 1 COVID-19 positive individual will be present at an event in a county, given the size of the event. In the image below, I set the size of the event at 15 (a typical Thanksgiving dinner pre-COVID). The model assumes that there are 5 times as many cases as are being reported, which is a reasonable assumption.

Hospitalizations and Deaths

Unfortunately, there are still some people who think increasing case rates are an artifact of more testing. If that were so, hospitalization rates would remain flat. But they’re not, as these charts clearly indicate.

Testing and Case Rates

Ideally, a country manages a pandemic in its early stages with the following measures:

  • Very aggressive testing and case tracking, with quarantines of all people found positive
  • A unified national plan and message
  • Mask wearing and social distancing
  • Rigorous enforcement of public health measures

When a country doesn’t follow those protocols, it can find itself in the position we’re in now. There are too many cases in the general population to do any meaningful case tracking, and too many people refuse to cooperate with case trackers.

Testing all over the US has ramped up. CA has increased it’s testing by nearly 50% in just the last month.

The other major problem with testing is that there are no federal standards, as described by an article on the John Hopkins site:

Under the current conditions, inputs into the same data categories differ between states. For example, in one state, the data for the number of tests administered might include both antigen tests and PCR tests. In another state, the testing data might only include PCR tests. This means that while the data category (“number of tests”) is the same, the inputs and resulting calculation are different.

Since the beginning of the pandemic, states have changed the amount and the type of testing data they report, and have been inconsistent in how they report antigen tests.

Some states also periodically pause or fully stop sharing key data that are used in making positivity calculations, or change the cadence with which they report data. Both of these actions can create abnormal spikes in positivity rates in tracking efforts such as ours.

https://coronavirus.jhu.edu/testing/differences-in-positivity-rates

Viral Load

Redditor /u/scarifiedsloth challenged me in my last update about the strength of the correlation of viral load with severity of COVID cases. I’m glad they did. As I keep writing, if you’re not a certified expert, then your only option as a science communicator is to express the consensus of expert opinion on that topic.

In this case, a mea culpa is in order. In fact, there does not appear to be a consensus – yet.

This article pretty much sums up the situation.

The evidence suggests an association of viral dose with the severity of the disease. However, the evidence of the relationship is limited by the poor quality of many of the studies, the retrospective nature of the studies, small sample sizes and the potential problem with selection bias.

Centre for Evidence-Based Medicine

Bottom line: more study is needed. This makes sense. Severity of COVID is related to a multiplicity of factors: strength of the immune system, preconditions, age, sex, quality and availability of healthcare, treatment during the disease, etc. Even if this were not a deadly virus, it would be quite difficult to isolate any one of the causes. On top of that, we have the increasing number of COVID “long haulers” — mostly younger people who had milder cases, but who now are experiencing severe post-illness symptoms.

It’s difficult under the best of circumstances to establish cause from correlation. Look how long it took with cigarettes! So it’s not surprising that there are multiple correlations at this point, but it will take some time to evaluate them all.

There does seem to be general agreement that viral load has an effect on contagion, and that makes perfect sense. That said, the reason why some people have a higher viral load than others is not fully known yet. With COVID, this is an especially important area of study, since there is quite a bit of evidence that superspreaders in the population are primarily responsible for large outbreaks. The problem is, many of those superspreaders can’t be easily identified.

Reasons for the current surge

As I pointed out before, I don’t know of a publicly available database offering historical data on sources of community outbreaks. In SD, a community outbreak is defined as 3 cases originating from a single location. In a recent 3 day period, the Public Health Dept. identified 35 community outbreaks (the goal for SD is <7 community outbreaks in a week). Here’s where they occurred:

  • 8 in retail settings
  • 4 in restaurant settings
  • 4 in bar/restaurants
  • 13 in business/warehouse/retail
  • 1 in government
  • 2 in healthcare
  • 3 in other

Before you jump to any conclusions, let’s examine how representative this is. Let’s say each one of those community outbreaks was responsible for not just 3, but 6 cases. That would mean this sample identified the source of 6 x 35, or 210 cases. During that same period, there were about 700 cases per day, or 2,100 cases.

That means that we don’t really know where 90% of the cases originated. There are dozens of articles in the media proposing that “family get-togethers” are the source. In fact, we don’t know that for sure. That doesn’t mean that they’re safe, though. As a great article in fivethirtyeight.com pointed out, even a small Thanksgiving can be dangerous.

So, is there an expert consensus on why the spread now is so rapid? No, partly because there are probably lots of reasons:

  • Superspreader events from relatively small, like a wedding in Long Island that resulted in 34 cases to the Sturgis motorcycle rally, which resulted in an unknown number of cases.
  • Delay in implementing restrictions. An article in the NY Times shows a strong correlation between the growth in cases and hospitalizations and the measures taken by governments to curb the epidemic (see chart below).
  • Public attitude and misinformation. The number of careless people, anti-maskers, COVID-deniers, or whatever you want to call them, influences how seriously everyone takes the pandemic, from neighbors to retail managers.
  • The Bully Pulpit. The position of a president governor, Congress person, or political official has a major effect on how people perceive the danger and thus the precautions they take.
  • Weather. Here in California, it’s still possible to have almost every event outside. Not so in the Dakotas. Moving inside means much less air circulation, giving virus-laden aerosols more time to do their dirty work.
  • Pandemic Fatigue. People want to go back to their “normal” lives. They’re tired of restrictions, so their tolerance for risk goes up.
  • The absence of a national strategy. Even if you’re a Republican, you can’t reasonably argue that the White House has a unified national plan. When the G20 started to discuss the pandemic, Trump left to go play golf. This has affected everything, from data collection to public understanding of effective measures.
  • Last, but certainly not least, lack of economic help. The CARES act was last March. Since then, unemployment benefits have run out. Small businesses and “essential workers” are facing economic ruin. Restauranteur Tom Colicchio predicts that COVID could lead to ruin for the 11 million people employed by the restaurant industry, and 40% of the establishments could go out of business. This forces millions of people to choose between health and economic well being.

Bottom line: we’ll be studying this for a long time to come. It doesn’t matter if we don’t know exactly why cases increased so quickly. The point is, we either take many more precautions than we initially thought we’d have to, or we’ll have an even bigger surge by the end of December.


This is a fairly grim picture, I know. Unfortunately, 5 million people flew for Thanksgiving, despite CDC warnings. So the situation, according to virtually all serious epidemiologists, is going to get even worse.

We won’t have even a semblance of a national plan until January 20. That means almost two months of national chaos. How the next two months play out, then, is basically up to you, your friends, and your family. This is not the way it should be, but it’s the way it is.

All we can hope is that enough people realize that effective vaccines are on the horizon, and that it is a tragedy to see anyone end up in the hospital or die when the solution is so close at hand.


Last week, I tried to respond to everyone who posted. I was so gratified to see the comments after my long absence that I felt compelled to do that. I’m not sure I’ll have time to do that today. Just know that I read every comment, even the ones that castigate me, and I appreciate them all.

2 comments on “COVID Update – Nov. 27, 2020

  1. Thanks for resuming covid data posts. You are the only person I’ve found who can present accurate raw data analysis without dumbing down too much. Thank you so much!

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