Yesterday I made a post about the S-curves of coronavirus cases in three highly infected countries (China, South Korea and Italy), and argued that looking at the data and based on the experience in China and South Korea we should be able to contain the virus in other countries too.
However, this also meant that countries like Italy and UK are probably only in the first quarter of their journey to containing the virus, and self-quarantine and social isolation will become the new buzzwords of the year.
I live in the UK, and in spite of heavy testing, NHS has not found many cases (460 as of Thursday, 1.5% of all tests made) – except surprisingly the health minister Nadine Norris. But still, everyone has become afraid of everyone else.
This will have a big impact on both the supply and demand side of the economies. With Christina Lagarde of ECB warning of a 2008-style crisis, it’s good to go back to over ten years ago and think what was the root cause for it. And it was exactly FEAR.
After the crisis, we did a lot of work mapping bank exposures and building models of contagion and could not replicate the cascading defaults that we should have been seeing without central bank and government intervention. The logical conclusion to me was that the root cause of the crisis was not the actual exposures or risks, but the fear caused by the lack of measurement and valid information on them. We envisioned it to be much worse than the reality actually was. When the lights were off we imagined monsters under the bed.
And this is what we are doing now.
So what can we do differently this time? We have much more data available, better models, better software, and better visualizations and channels to communicate them. Let’s make use of it all!