I'm going to start a thread on global first reported #COVID19 cases. Things to look out for: Date, location, demographics, stage, visible vs invisible world (tourists go to the doctor, supply chain workers don't), indicators of fast spread (many reports in diff locations). 👇
SOUTH KOREA: 20 Jan, Chinese woman, Incheon, hospitalization; nice table and dynamic map, early cases NW then SW, current center Daego is in the SE. en.wikipedia.org/wiki/2020_coro…
GERMANY: 27 Jan, Starnberg, Bavaria, Webasto employee, finally a first case from the industrial world; there is a nice dynamic map, this was all over Germany in a flash. en.wikipedia.org/wiki/2020_coro…
JAPAN: 10-15 Jan, Chinese national, Kanagawa, hospitalization, direct contact with Wuhan. Many more direct contacts with Wuhan in January. en.wikipedia.org/wiki/2020_coro…
The early phase of the Covid pandemic in Lombardy, spring 2020. In most provinces (including Lodi and Bergamo) Rt peaked in February, before the onset of mass testing.
The paper reconstructs the beginning of the pandemic before the first public case in Codogno (Feb 14). It was already widespread in Lombardy by mid February, and showed no connection to population density.
The paper reports by symptom onset, so take another 5-6 days off to capture the outbreak by infection date. This confirms the many, statistical mistakes of the "Burn-Murdoch race chart" era. We were chasing ghosts that had passed thru already. researchgate.net/publication/35…
To summarize a longer private conversation: In the long reckoning, no restrictive public measure will survive any rigorous scrutiny. It was all protection theater. Measures that made a difference were all in the backend, the access-to-care part, that nobody paid any attention to.
That summarizes a claim I made a long time ago. If a country is diligently prepared for a pandemic, most public restrictions are unnecessary. If it's not, they might seem unavoidable, but ultimately pointless. Protection theater for a shell-shocked populace.
So the biggest mistakes were already made ten-plus year ago. The "rationalization" of the healthcare, eldercare, and disaster preparedness systems, euphemism for cost-saving measures that killed valuable operational expertise in favor of spreadsheet wizardry.
If you had Ames, Iowa on your bingo card for hotbeds of innovation research — Bingo. Indeed the technology adoption curve (aka the most important curve in history) was invented by rural sociologists at Iowa State College some 70 years ago.* A little history.
WW2 put pressure on US food supplies, and a variety of technological innovations in agriculture promised improved yields. The rural sociologists were mostly concerned how these improved technologies could be made attractive to farmers, a notoriously skeptical bunch.
In the 1940s two researchers at ISC, Bryce Ryan and Neal Gross, conducted field research on how Iowa famers adopted the novel hybrid seed corn. Their report already contained the key ingredients: risk preferences, social contagion, geographic spread, and the logistic curve.
A few notes on coordination, adaptation, and the role of institutions.
"Both the organization theorist Chester Barnard and the economist Friedrich Hayek took adaptation to be the main purpose of economic organization, but with differences." — Oliver Williamson Nobel Lecture
Unlike cooperation, which has taken on the meaning of "solving the Prisoner's Dilemma" and collaboration, which just generically means "working together", coordination suffers from being semi-defined, which often means one has to divine the type of coordination implied.
Based on a very useful pointer from @petergklein, it turns out the meaning of coordination has shifted over time, from longitudinal alignment (concatenation) to simultaneous alignment.
While we're killing time I can translate and summarize a podcast talk I gave in 2017 (in German) on how Donald Trump confounded the poll aggregators and won the election. Because clearly the message still hasn't gotten across, or we wouldn't still be waiting. 1/♾
The story started for me in March 2016 when a coworker predicted during lunch that Trump (still mostly a joke then) would win the election. I proposed that the only way for him to do it would be to stay on message and at the same time discourage Clinton voters from voting.
If you remember, a lot of pundits assumed that Trump was playing an outsider role to clear the field during the primaries and then would turn more "presidential" in order to appeal to the centrist establishment voters. As has been the masterplan for decades.
Very interesting thread about the relevance of Coase's Nature of the Firm for the platform age. I've written a few things about how working on a dynamic ridesharing* service in 2009 helped me connect Coase/Williamson to digital business models, so here's a few summary comments.
The current focus of the public debate is the often contentious relationship between drivers and platform, but in order to understand the structure of the industry, it's also important to look at the underlying relationship, namely that between driver and passenger.
A key problem we had to consider when conceptualizing our service was how to safeguard both drivers and passengers. Turns out when you look into the history of taxicab and limo services, it is fraught with what we like to call "contractual hazards"...