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Interesting analysis. I was wondering - how is weather built into your model? I'm thinking that even if people take relatively few precautions in Ontario in the summer, most of the things that people tend to do in the summer are very low risk activities - it's just really hard to catch COVID on the beach because the UV zaps the virus and the wind blows it away. Plus school's out. So I'm just puzzled by the blue line that shows a big rise in cases in July - that seems implausible regardless of the vaccine roll-out or lockdown regime.

The second uptick could be the result of restaurants who never previously used reservations having to pivot to systems like OpenTable to adapt to sudden policy requirements. Furthermore, customers who never previously bothered to make reservations suddenly learned how to, and quickly got in the habit of doing so.

Disclaimer, I'm not an economist, but I do help manage a restaurant whose revenues dropped by 80%. Nothing spurs innovation like the need to survive, and using OpenTable was one of the many (often technology driven) adaptations we made.

I just took a quick look at the paper. I would like to run the simulation - I assume was done Stata or R?

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