There are several articles containing recommended reading for the period of confinement during the present epidemic. But perhaps the most thoughtful is that in (odd as it may seem) the Daily Mail. This is by Roger Alton and relates to the Mail’s “Book of the Week”: The Rules of Contagion by Adam Kucharski, an epidemiologist who teaches at the University of London’s School of Tropical Medicine. This was obviously written and probably went to print before the present epidemic got started. The reviewer congratulates the author for avoiding the temptation to add last minute references in an effort to increase timeliness. These were not needed to make the book relevant. (The book will not be released in the USA until September. Here’s a link to the UK edition currently on offer.)
After summarizing the book’s description of the history of epidemics and the evolving means to contain them, the review provides Kucharski’s summary conclusion:
‘There’s a saying in my field: “If you’ve seen one pandemic, you’ve seen . . . one pandemic.” ’ And like all good mathematicians, [Kucharski] knows that numbers are the key. Not hysteria. Not fear.
Here’s the reviewer’s summary of what the math teaches, according to Kucharski:
The shape of all outbreaks is roughly the same: first spark, then growth, peak and decline. It is a pattern known as the SIR model, dividing populations into three types: susceptible, infected and recovered. Once the number of recovered people is large enough, the disease will die out as there is no one left to infect. And at the heart of that is a mathematical big beast, the reproduction number, known as R, representing the number of people an infected person will go on to infect. If R is less than one, then sooner or later the disease will die out. But above that, if R is greater than one, the contagion will spread. The R for coronavirus appears to be between two and three, comparable to the Sars outbreak of 2002. Ebola and pandemic flu have an R between one and two. Measles, though, which is staggeringly infectious, has a very big R, about 20.
Toward the conclusion of the review, the writing of Evelyn Waugh is drawn into the discussion:
As we live through the throes of a disease pandemic and a stock market panic, never has it been more important to hold the line between real and bogus information. It’s not a new phenomenon. In Evelyn Waugh’s 1938 satirical novel Scoop, legendary American foreign correspondent Wenlock Jakes is sent to cover a revolution in the Balkans. Unfortunately he oversleeps on his train and wakes up in the wrong — but wholly peaceful — country. Not realising his error, he makes up a story about ‘barricades in the streets, a dead child like a broken doll spreadeagled in the deserted roadway, machine guns answering the rattle of his typewriter’. Other journalists swiftly arrive and make up similar stories, stocks plummet, the country has an economic crash, there’s a state of emergency, and then a revolution. And Jakes is there to cover it.
Fiction of course, but now the speed at which bogus information can be transmitted — like a virus — is incomparably quicker than in Waugh’s day. Whether it is disease epidemics or crime and terrorism, mathematical models can help countries plot outcomes and allocate resources.But models are just that, writes Kucharski: reality is messy and complex. If you build a model train set — no matter how skilful and full of add-ons such as delays, leaves on the line, faulty signals — it will always differ from reality in some way.
A survey of other recommended reading will follow in a later post.