How Risky is COVID-19?
How Risky is COVID-19?
It is difficult not to think in circles about Covid-19. There is a welter of research out there, very little of it yet subject to intensive peer review. Whatever your initial bias, someone somewhere has research to confirm it. To organize thinking, I would like to highlight just one piece of research — from Andrew Brigden, chief economist of Fathom Financial Consulting in London — that brought together the various strands better than anything I have read so far, or at least organized the problem for asset managers in a very useful way.
After crunching through some statistical analysis, Brigden found that the crucial reproduction number, or “R” rate — the number of people infected by each person who has Covid — tends to diminish in line with reduced mobility. In other words, the more people stay at home, the less they infect others. But crucially, R also decreases in line with the number of people who have already been infected. This second variable is plainly very good news. The more any individual country has had the disease already, the slower it is likely to spread. To show the effect, Brigden offered this chart of how much reduced mobility can explain infection rates in the UK on its own, compared with the actual change in R that has happened:
The UK’s drastic lockdown in March and April plainly had everything to do with bringing spread under control. But we would have expected infection rates to drift upwards as the country began slowly to return to normal in the late spring; instead, the R rate has continued to fall and remains below 1.
Naturally, one of the greatest concerns at present centers on the US, and the way that Covid is now taking hold across the states of the “Sun Belt” that had largely been spared during the beginning of the outbreak in March. The failure of these states to clamp down on mobility doubtless has much to do with this. But when Brigden mapped R in each state (for these purposes, simply looking at the multiple of new cases this week compared to last), against the death rate that it had already suffered, there was a clear and strong relationship. States with minimal death rates so far are suffering serious levels of R well above 2.
What is going on? Brigden very usefully breaks down the possibilities into five broad answers, which are not mutually exclusive. The first three, I would say, are unambiguously positive, both for us all as humans, and less importantly in terms of the prospects for risk assets. The fourth is somewhat negative, but still suggests that there is a clear if costly way to keep the damage wrought by the virus under control. The fifth would be a total nightmare:
Fear of dying from the disease provokes other changes in behavior, such as more frequent hand washing and the wearing of face masks, that prevent the spread of the disease but are not captured by measures of mobility.
Heterogeneity across the population means that we all have a different ‘R’ number, with some people, including those with a large network of contacts, more likely both to acquire the disease and to pass it on. Once those people have been exposed, and are no longer susceptible, the average R will fall.
The virus has spread far more rapidly than antibody testing suggests, which means the virus is running out of people to infect.
Potential ‘super spreader’ events — such as nightclubs, and music concerts that involve a lot of people being close together indoors — are no longer happening.
It is a seasonal phenomenon in the northern hemisphere, and it will return later this year in a ‘second wave.’
Living in New York, I see a lot of truth in the first. It is unusual to see people walking down the street unmasked, and more or less every building requires you to wear a mask to enter. I have never yet seen anyone complain about this. As the disease takes hold in the Sun Belt, I suspect strong and understandable resistance to minor inconveniences like mask-wearing will begin to disappear.
I can believe that there is a fair amount of truth to the second hypothesis, and the authorities are busily testing the third. In New York in the early days, plenty of people with nasty cases of Covid-19 who did not need to be hospitalized were never tested, and so do not appear in the figures.
The fourth makes much sense, and bodes ill for cinemas, theaters, professional conference businesses and sports played indoors as well as nightclubs. It must be miserable news for single people in their twenties. Going without such “super spreading” events would inevitably have a negative ongoing impact on GDP, but it would be well short of a disaster.
A true second wave (what is happening in the Sun Belt is a continuation of the first wave that hit the Acela Corridor) would be a disaster. The second wave of the Spanish flu in the fall of 1918 proved far worse than the first wave that spring. As a second wave of Covid-19 would overlap with seasonal flu, and would hit a population very reluctant to return to lockdown, it would be terrible for the world’s advanced economies, and quite possibly inflict even more economic damage than the first wave has done.