OVER the last few days I have been listening with increasing incredulity to the BBC’s interrogations, if such a word can be used, of Professor Neil Ferguson of Imperial College London. I hold him responsible for ramping up the incidences of ‘What’s the Time, Mr Wolf?’ in the Harper household from a manageable pre-coronavirus level to one which is threatening to overwhelm the system, so have a keen interest in the validity of his predictions.
Credulity, however, is not something that BBC interviewers could ever be accused of lacking. The science is settled, after all. All that is required of high-handed interviewers such as Mishal Husain is unquestioningly to dispense the government’s advice. I find the lack of curiosity quite astounding, particularly in journalists. They have accepted that it is in the public’s interest to stay at home so feel no need to examine the logic. They seem to think that to do so would give implicit consent to disobey. I think they’re wrong: I think the population’s compliance depends on rigorous probing of the advice.
Andrew Marr did little better on Sunday, feinting to quiz the expert but pulling his punches each time, ultimately taking his projections as immutable fact. I understand the BBC have to pick out the middle path but it’s the facts they deem unchallengeable that betray their bias.
This is a rapidly evolving situation with the experts fairly admitting to having an imperfect understanding of the key inputs to their modelling. This is not a criticism of expertise, this is a criticism of inquiry. Here are some questions that would improve my own limited understanding:
Predictions for the infection fatality rate of swine flu were considerably worse in the early stages of the pandemic than borne out in reality. What did you learn from this when modelling Covid-19?
How reliant are the models on the first date of transmission within the studied country? If that date is moved back a fortnight what does it do to your IFR?
What is the sensitivity of thepolymerase chain reaction (PCR) test used to diagnose Covid-19?
If the false negative rate is as high as you say, would you confidently tell a self-isolating doctor who tested negative to return to work?
If the advice following both a positive and negative result is the same why run the test?
Is there any cross-immunity from other strains of coronavirus? Are some people ‘resistant’ to this infection? What proportion?
What proportion of people who share a house with somebody who is infected go on to become infected themselves?
What proportion of ventilated patients could expect to survive to discharge?
If a person is willing to accept the risk to be with a dying relative what business does a hospital have in denying that?
Are one thousand nights of dancing and thrill and laughter worth a year in the care home?
These questions are not all of an epidemiological nature, they may not even have answers, but I would like somebody to be asking them.