I asked Brian Sullivan and Kevin Roche if they might be willing to respond to what I wrote in the adjacent post this morning in connection with one particularly vehement comment on it. Understanding that there is reasonable ground for disagreement, I thought that readers might find these responses of interest. I certainly hope that they can foster informed discussion illuminating the serious issues before us.
Brian Sullivan writes:
Using a scenario that has no possibility of occurring to justify future actions is wrong. Minnesota is not “doing nothing,” so holding that out as our baseline case is simply a way of using data to manipulate and scare people. The data that exist now from other countries enable development of much more informed projections of future scenarios.
One of the leading UK epidemiologists informing the government of its policy options, Neil Ferguson, just reduced his projections of total UK deaths from 400,000 to 20,000 (or lower) – a 95% reduction – because he had more data to develop a better model. Other epidemiologists suggest that there is evidence using current data that the fatality rate will be closer to 0.1% than the the original WHO estimate of 3%. Pretty big change.
So should we be basing public policy off obsolete models or use models based on current data? No one is arguing that we do nothing. Folks like us are arguing that we use current data to make policy decisions that seek to minimize economic harm while protecting vulnerable populations. Why is that controversial?
I don’t have the energy to go through other points [the commenter makes] other than to say that “leaving it to the experts” (e.g. “just lie back and enjoy it”) without skeptical questioning is a hallmark of totalitarian countries, not the US.
Kevin Roche writes:
Nobody knows R0; nobody has done the necessary research to actually determine it. People infer it and, frankly, it is an irrelevant number. What matters is what we know about actual infection rates. It is so important to be sure people think simply and logically about this.
1) There is percent exposure to the virus. We don’t know what that is, but I assume a high percent of the population has been or is going to be exposed. But it clearly isn’t 100%. Testing for antibodies is the only way to determine that, and some studies are beginning.
2) Then there is infection, which means you were exposed and the virus actually got a toehold in your body. As best we can tell, and this is Dr. Birx’s point [in yesterday’s White House task force briefing], that is actually low, only 20% on the Diamond Princess, apparently much lower in Wuhan, where you have to remember the virus ran unchecked for weeks in a densely populated metropolitan area of over ten million people, likely exposing a very large fraction of the population. Why it is low is an interesting question….To ascertain infection rates, you would need large scale, randomized testing of the population. Unfortunately most tests currently have somewhat high false positive rates, and somewhat lower false negatives. And because people are out there in the real world, you are only getting a snapshot it time. Ideally you would take your study population and retest them regularly to see how the infection rate rises over time.
3) Then there is illness, which means you actually develop some symptom due to infection by the virus. Again, as best we can tell from testing rates and other factors, a very large percent of those infected are asymptomatic, at least half and potentially as many as three-quarters of all who are infected. Hence the concern about social distancing, good hygiene, etc. because if you are infected, you can be spreading the virus even if you are asymptomatic. To ascertain the true rate of asymptomatic persons, you would need that large scale randomized testing study, and you would need to find out how many people had a symptom. Since for most people, the illness is pretty mild, you would be relying on self-reporting and of course anyone who has tested positive and seeks medical care would also be included in that percent of symptomatic people. And as with infection rates, you would want to follow people for some period of time.
4) Then there is serious illness, which you can define as someone who needs hospitalization. This also gets a little tricky, because the people who are most likely to get infected and become seriously ill generally have multiple serious co-morbidities. So is it the virus or the co-morbidities that are causing the need for medical attention. But at least if you got your denominators and numerators right in steps 1, 2, and 3, the calculation of the percent of people who get seriously ill should be more straightforward.
5) Death, again not as straightforward as it seems. Italy’s experience is illustrative. Did these very sick patients who also got coronavirus die from coronavirus or the other diseases? But if your definition of cause of death is good, percent of deaths is a straightforward calculation.
One final note is the denominator issue. Best in my judgment to use population, which we do know. But no matter what is used, you have to be clear about it. Walz and others are using denominators that are not population and not being clear about it. Obviously any denominator other than total population makes the percent or rate look higher and scarier. And any denominator other than population is useless at this point because of the issues mentioned in 1, 2 and 3.
Clear thinking is important. The commenter seems to prefer attacks on lawyers.
JOHN adds: During my legal career, I cross-examined hundreds of experts. Probably thousands. Some knew what they were talking about, others didn’t. Many committed obvious logical errors. I would summarize my experience with the mild observation that experts–including the most highly qualified and highly paid experts–are far from infallible. And they often disagree, so it is necessary to analyze their arguments and data to determine, as best we can, where the truth lies. No one who has had that sort of hands-on experience with experts, often of the most distinguished kind, would argue that we should blindly turn important public policy decisions over to them. And the idea that debate should be stifled because “experts” know best is ridiculous.