It is a bright new day, so here are some thoughts on various subjects, most of which have the same theme: deciding how bad things are depends on your frame of reference.
I had said that excess deaths was the key variable in understanding the coronavirus epidemic, and the policies being deployed against it. Once deaths are plotted out over several years then we have a base-rate against which any upward trend can be detected. Emil Kirkegaard directs me to European data, which shows deaths week by week at national level. Given the nature of the epidemic, it is the over 65 years of age group which is of particular interest.
No evidence of excess mortality, so far, in the reporting countries, apart from Italy. Data is delayed in coming through, so we should be cautious about that for another few months. Nonetheless, so far, we are not at the excess death levels of the winter of 2016/2017.
In Europe at least, it is not killing many of us, yet, compared with previous seasonal variation in death rates. However, since most countries are isolating the population as much as possible (no stepping stone) this paucity of excess deaths may indicate that the policy of isolation is working.
All simulations have assumptions, each with their error terms, and most have projected estimates of death rates under different policy conditions. Basically, if a government gets its act together, then a mixture of test and isolate; test, isolate and trace contacts and isolate those; different degrees of lockdown; different degrees of mask wearing; different degrees of hand and home washing will result in a lower number of deaths. So, when looking at any simulation you need to look not just at their worst case, but at the predictions they make for each condition.
The Imperial predictions have, in my view, been unjustly criticised because their high estimates of death rates under the “Do Nothing” condition. That prediction led the UK Government to Do Something, and under this new condition it is appropriate to look at the predictions they made about those mitigating scenarios, which were much lower. Not a change in the model, nor an admission of error, but a confirmation that when circumstances of social interaction change, the death rate will probably go down. Note also that their model suggest that the increased demand for hospital care will be evident in late April/early May, and we are not there yet.
By the way, unless commentators are publishing their own models, they should merely state their own assumptions and make their own predictions in sufficient detail that they can be evaluated later. The best guy on this is Prof Philip Tetlock, who has doggedly tested expert prediction, and has scathing things to say about most public experts, but much better things to say about less well known, tested and validated winners of prediction competitions.
Here are super-forecaster’s predictions for the situation a year from now: more than 800,000 deaths but less than 8,000,000 worldwide, they estimate. Talk about error bands.
Here is a brief summary of Tetlock’s work:
Another approach, (previously posted by Steve Sailer) is due to Aatish Bhatia with Minute Physics is to plot for all countries the log of their infection rate versus the log of their death rate, to create an interactive display in which most countries progress up the same path, but China and South Korea seem to have fallen off the routine death march into apparent safety. Unfortunately, I cannot find an actual interactive link, only a video of the simulation at work a week ago.
As a final individual point of view, here is University of Cambridge virologist Dr Jane Greatorex, who worked in Sierra Leone on the Ebola outbreak and for Public Health England during the swine flu epidemic being interviewed about various issues, particularly how long self-isolation should last for infected persons.
The Covid-19 virus has not been in the UK for very long, so is not widespread.
Recovered people probably have immunity now, though it will take 12 before extent of immunity is clear.
I take great umbrage at the lengths of time you are meant to be infectious for because it is just not true. Nine days is nonsense. You don’t excrete a live virus that long.
Those studies are not checking for live virus, they are checking for genome. They do something called a PCR test (polymerase chain reaction), which is the test we are using to diagnose patients. It doesn’t tell you that you have live virus in your nose, it tells you have had it. For about 72 hours of a viral infection you have a live virus. In children it can last for longer – four or five days have been observed in flu.
So, there’s a big difference between how long we can detect the virus and how long they can infect someone else. With this coronavirus the only way you can say, yes, they are still shedding live virus – which is the only thing that will infect someone else, is if you take that sample from the patient and extract it and put it on tissue culture cells and then see it growing. That is done very rarely.
How long are people contagious before symptoms appear?
The likelihood is up to 48 hours before.
Is the data from China trustworthy?
Yes, there is very good data. The studies that have been done are excellent and so rapidly produced, but it is all about the context in infectious diseases. There will be some genetic differences in the way that we respond to diseases. That’s not unheard of. So I have a bit of wariness. The data that is coming out of here matters the most and Public Health England is looking at that.
Although we have to wait for more data, it is already possible to run simulations to roughly guess the impact of lockdown policies, so these predictions can be tested against the death rates reported over the next three weeks. It is possible that, far from excess deaths, all infectious diseases will be reduced.
We may become a world in which we wash our hands more frequently, wear masks in public places whenever we feel a cold coming on; nod or bow rather than shake hands, and accept that no-one flies anywhere without good cause, and a clean bill of health.
Or, that by next October, it will be business as usual again.