Better and worse outcomes

23 March 2020

Better and worse outcomes seem more likely; expected case appears more painful

I’ve spent much of the last three days thinking more about expected, better, and worse cases, and how I should update my priors in light of a constant flood of new information.

On the one hand, I’m increasingly optimistic that there is a path toward the better case, and I’ve increased from p=20% to p=25%. We now have multiple existence proofs (China, South Korea, Taiwan, Hong Kong, maybe Japan) of a playbook that works. The New York Times describes it very well: Let scientists lead; ramp medical capacity rapidly; implement extreme social distancing (total lockdown); ramp up testing; isolate the infected, including removing people from their families (the secondary attack rate seems has been estimated at 10-15% with a lot of questions); aggressive identify, track, trace, and quarantine every suspected case and every contact of that suspected case; and prevent new infections from coming across the border since the potential for reintroduction is very high even after successful controls. At the same time, we need to continue the rapid push for therapeutics (promising) and a vaccine (likely far away); and to help poorer countries both for humanitarian reasons, as well as on the selfish grounds that otherwise the virus could find human reservoirs.

On the other hand, even in the expected case, the current and potential economic impact is almost unimaginable (see yesterday’s post to get a sense of it), with nothing to compare it to in any living human’s memory. With aggressive economic support from governments and actions by central banks, it’s possible to imagine how we bridge six weeks or even three months that lets the world return to its current productive capacity within a few years, avoiding mass long-term unemployment, bankruptcies, and worse. But if a total lockdown needs to go on for many months; or if governments implement half-measures or are unable/unwilling to maintain strict control measures and then have to re-implement them again several months later; the economic damage could be severe. And that’s still leaving aside many known unknown risks like a severe second wave; the virus mutating in a more dangerous direction; failing to build health care capacity; zero-sum behavior by countries; rising geopolitical tensions; and so on. I fear that there’s a real risk of an own goal here, and have raised my risk of a worse outcome to 25%; and at the same time have understood that the economic impact under the expected case is worse than I previous thought.


What should our base rate be on the time to economic recovery?

I love this white paper from JP Morgan, which looks back in history to ask how quickly countries rebound from crisis and economic hardship. I highly recommend reading the full paper. Some key points:

  • Looking across 12 major dislocations since 1870, “With the exception of the Great Depression and certainly in the post-war era, it generally took less than four years to regain the peak, and sometimes less than three.”
  • The market currently (17 March; we’re further down since then) implies more than a decade to regain the prior earnings peak:
  • German and Japan after WWII, and China after Mao’s Great Leap Forward, did take a decade or more to recover; but COVID-19 should be much less destructive of the world’s economic capacity under almost any scenario.
  • “Sometimes, even when wars do result in damage and ruin, the speed with which economies rebound is faster than the speed with which they decline. The US Civil War was the deadliest conflict in US history, with 6x the number of war dead as a percentage of the US population than World War II. The Civil War left the southern US in complete shambles […]” but farm income recovered within a few years of the end of the war:
  • Finally, asset prices often reach their bottom well before things start to improve, and even when the news is relentlessly bad (see many charts in the paper).


Reasons for optimism from an immunologist

I’ve started actively follow Dr James R. Baker’s blog (yes, we seem to use the same WordPress template) and recommend it for balanced, expert discussion in plain English. I particularly liked his recent post, Seven reasons to be optimistic. Read the whole thing, but the headlines are:

  1. Social distancing does work
  2. Underreporting is probably very high, so the actual Infection Fatality Rate (IFR) is likely to be much lower than the Case Fatality Rates we see reported. Plus we might be building herd immunity faster than we think. (Reminder, IFR is based on the actual number of infections, whether we know about them or not; CFR on the confirmed cases. We only know CFR, but we should care about IFR.)
  3. We’re building medical capacity quickly
  4. Coronavirus could mutate to become less pathogenetic. (CCN: I’m sceptical.)
  5. Summer weather could help. (CCN: Still sceptical, but more evidence is pointing this way; I need to do a post just on this topic.)
  6. Existing anti-virals could help as therapeutics.
  7. While we’re working on vaccines, we’re not counting on them. (CCN: I also need to do a post on why an effective, safe, widely distributed vaccine is likely very far away.)

What’s happening in Iran?

A close friend whose family left during the revolution, and who now lives in the West, reports:

“Iranian doctors are very liberally using the hydroxycloroquine combined with citromycin combo and reporting very good results on patients that have respiratory distress. I have been speaking to a few doctors in the family every couple of days to get the pulse. [Apparently] the country is practicing zero social distancing (in the middle of a big national holiday when everyone is visiting everyone) and has a weak medical system.”

A useful resource comparing the pressure on health care systems across Europe

“European countries have been facing enormous pressure on their healthcare systems […] We calculate the relative pressure on healthcare systems by analyzing the proportion of COVID-19 related deaths (intensity approach) and COVID-19 active cases (magnitude approach) in real-time relative to the number of hospital beds, number of medical doctors, and healthcare expenditure, in European countries.”

Unsurprisingly, the charts show that Italy and Spain are under unique pressure today; do they give a hint of the next countries to feel the crunch?

The one chart I look at every day

Is the Our World in Data chart showing cases by country, on a log scale, normalized to t=0 on the day they first reported 100 cases. This tries to answer the question of how the different trajectories compare by country, adjusting for the fact that the disease took hold / took off on different dates. Here’s the chart as it currently stands (this is embedded so should be up to date):

The key question, of course, is whether countries like Italy, Spain, the US, the UK, etc are beginning to bend the curve since implementing increasingly strict control measures, as China, South Korea, and other Asian countries did.

As a reminder, this chart plots confirmed cases. That means we should expect a lag, perhaps even a significant lag, between the date a country imposes strict control measures, and the date we see the curve bend, for two reasons. First, there’s probably a 6-8 day lag (maybe more) between a decline in the actual rate at which infections are increasing, and a decline in the rate at which confirmed cases are increasing, given the lag from infection to symptoms, from symptoms to a test, from testing to confirmation, and from confirmation to reporting. Second, most or all countries implementing strict control measures are also increasing the rate at which they test, so the gap between actual cases and confirmed cases should be closing over that period (since we’re detecting a higher proportion of the actual cases through more testing), which could have the effect of making the rate at which confirmed cases are increasing appear to accelerate even if the rate at which actual cases are increasing is declining.

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