Sports betting junkies have withdrawal pains due to Coronavirus (Covid-19) social distancing. It has shut down sports and much of the economy. There are no games to bet on. But you can still bet on sports derivatives. Who will go third in the NFL draft? Will Tampa Bay win more games this season with Tom Brady than New England without him? Professional oddsmakers say no. Their over/under for the Pats is 10 1/2 wins. It’s 7 1/2 for the Bucs.
Professional oddsmakers’ over/under is usually close to the actual result. It draws bettors on both sides so bookies can balance their book and make money on the vigorish (betting fee). Too bad there’s not an over/under for Covid-19 metrics. It would be a useful check against numbers coming from the President’s experts, the Center for Disease Control, the World Health Organization, reporters, and others in the Chicken Little business (i.e., the bad news sells business).
Prediction Markets used to provide professional oddsmakers’ handicaps of elections and other political events. They were pretty accurate. Much better than polls at predicting outcomes. Politicians didn’t like it. That may be why regulators shut it down.
On March 29th, presidential adviser Dr. Fauci predicted 100,000 – 200,000 US deaths from Covid -19. He later increased it to 240,000. That’s quite a range. He wouldn’t make it as a professional handicapper. His point spread is too big.
It’s reported that he and Dr. Birx, another presidential adviser, used the World Health Organization’s model for their early predictions. That’s the abandoned model that predicted the 3.4% death rate that started the Covid-19 pandemic panic. For what it’s worth, experts now seem to agree that the death rate will be 0.1 – 1.0% of cases. That may be close enough for government work. But the 10:1 point spread is too wide for bookies to make book.
It’s reported that many experts are now using the University of Washington’s model based on Farr’s Law of Epidemics. Computer models are known for the garbage in — garbage out phenomena. The accuracy or value of the output depends on the validity of the inputs.
Farr’s curve of cases, deaths, and other measures of epidemics is initially exponential but then declines, peaks, and decays in a bell shaped pattern. The numbers don’t reach the sky. But early trends lead to Chicken Little panics. And to over reactions like shutting down the economy.
We are told it’s better to be safe than sorry. One death is one too many. It’s therefore heartless to note that Covid-19 deaths since February are about 2% of total US deaths for the same period according to the CDC. People die, and life goes on. But not the economy if people die from Covid-19.
One key input for models is infection rates. It’s estimated based on increases in reported cases. Reported cases are confirmed based on tests. The test detects the presence of the virus that causes Covid-19 but not the quantity (viral load). If the viral load is low, you may not get sick. Many cases are a symptomatic. If you don’t have symptoms, you may not get tested. If you test positive and have pneumonia, you probably have Covid-19. Food and Drug Administration guidelines say you can then be treated — in a hospital.
If you test positive and don’t have pneumonia, you may be sent home until you get it and can then be treated under FDA guidelines. You may end up on a ventilator in a hospital where your odds of survival are probably less than 30% if you have other health issues or are old. (The viral load increases rapidly, and early treatment improves outcomes. Delay is deadly.)
Reporters and others for whom bad news is good eagerly report new cases as evidence of bad news. New cases may be increasing because the virus is spreading. They may be increasing because more tests are available and are being given. Probably both. The big questions are how many more deaths will there be? And how many deaths will social distancing prevent – or delay? And how many deaths, if any, will social distancing and shutting down the economy cause? What are the trade offs?
These are hard questions to think about. The answers are hard to quantify. They affect deaths of Covid-19 victims and lives of compliant citizens who lose their jobs. And their liberties. And maybe the deaths of some of them. They affect careers – of politicians and experts. Doomsayers have a vested interest in doom. They may exaggerate doom to frighten people into social distancing and other well-intentioned responses to mitigate damage from exaggerated doom — that never happens. They may be wrong. It may be hard – or impossible – for them to admit it.
Let’s look at deaths from Covid-19. It’s the best measure of doom. It’s not as easy to determine as you might think. People die with Covid-19 and from Covid-19. The death is not the way I want to go either way. It’s drowning in your own juices as pneumonia kills you despite ventilators — which may just prolong the agony.
Who dies? Mostly the old and the sick who are already dying and those with weak immune systems and diseases they may not know about. Those who die with Covid-19 may be coded as dying from Covid-19 as it becomes the default cause of death. Check the box. So deaths from Covid-19 are probably over-stated.
There were 7,616 deaths in the U.S. as of April 4th attributed to Covid-19 by the CDC. To put this in perspective, there were 446,778 deaths from all causes. The University of Washington model predicts 93,531 deaths from Covid-19 by August 4th. There will be 1,410,852 deaths from all causes assuming the CDC’s US average of 7,838 deaths per day in the interim. The range of Covid-19 deaths predicted by the model is 40,000-178,000 or about 3-13% of total deaths.
The experts are just guessing. With our lives and well being. And freedom.
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