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One of the difficult questions is: assuming there really is a “cost of democracy” holding tech-level constant, should you be personally willing to pay it? Can’t honestly answer that without normalizing for your relative safety as a function of class/wealth.
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I’m totally willing to accept a 10x-100x higher fatality rate (on a low base like 0.1- 1%) for higher civil liberties but then I’m not most at risk from poverty, crowding etc. Healthcare workers at least knowingly sign up for a risky profession.
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Hmm. Would you, in the wake of this, vote for a measure making forced group quarantine an emergency power, weakening habeas corpus in situations well short of martial law? I honestly don’t know.
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If you could be administered a medical test against your will, by people who have entered your house without a specific warrant, and taken away to quarantine, would you be okay with that? I think it’s technically feasible in the US right now only under martial law right? 🤔
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So... the case that per capita is meaningless because outbreaks are scale free. I’m not sure I buy this. You can’t just assume scale-free based on lack of correlation. A country is a logistics/travel connectivity cluster, not a meaningless fiction.
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A quick chart for those who keep asking for per-capita adjustment: Here’s population vs total death toll one week after 10th death. No relationship. As I’ve been saying, population does not affect pace of spread. All per-capita figures do is make smaller countries look worse.
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I think the way to combine cluster analysis and country analysis is some notion like mean-free-path. The right unit of analysis is neither the “country” nor the “outbreak cluster” but something else. Populations are not structureless Petri dishes. They gave a mobility topology.
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I’d buy the scale free argument if cities were large open spaces within walls where people all just stood still 3 feet apart and virus was jumping like a wildfire through a forest. No. We move, at varying speeds, through striations. The connectivity matters.
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Per capita is likely a terrible way to control for country effects, but country effects must exist and show up if modeled right. Wuhan and New York are both important economic hubs with a lot of travel for example.
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Maybe the right way to adjust is to Ignore country boundaries but segment graph of air travel and road travel connectivity bandwidth by a min-cut/max-flow logic, to define de facto “logistics countries”. This would make Seattle part of an Asian hub, NY part of an EU hub.
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Add an MLM attribution logic. Wuhan gets a fraction of the case count of all 1-degree removed air linked cities, regardless of country they’re in. Recursively back from newest hubs. Many big cities are better connected to international trading partners than national hinterland.
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Idea for a graph theory project: use the flight connectivity data and dates of travel restrictions to construct city-clusters that should be treated as “Covid19 nations”
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I'm not sure what you are after, but what you describe is essentially getting at WHEN "seeds" get distributed across cities. But the real action is after that, as each seed then spreads out. That's more about local customs and degree of mixing (eg lots of public transit vs cars).
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