Yesterday, I posted the graph below on Instagram. To briefly explain methodology and assumptions employed in creating it, I’ll first suggest that interested readers go check out this predecessor post, Going Viral: Why New York City Will Soon Be Shut Down in Five Graphs, that explains how I came up with the original (exponential) growth curve for projected total COVID-19 cases in NYC.
As is my new practice, I’m going to explain all the math in the caption, so anyone not interested in the math can simply ignore the caption and enjoy the picture.
An explanation for how I created the exponential growth curve above can be found in this post. If you have a look there at the graph derived from the JAMA Wuhan data, you’ll see that for the eight days following the introduction of “drastic measures,” the number of new daily cases (total, rather than confirmed) basically levels off. The graph shows a gradual downslope and an inexplicable spike, but my understanding is that that had more to do with the timing of the reporting and the Chinese government’s preferred optics than the actual trend. Thereafter, there is a roughly linear decline in the number of new cases for ~10 days (I use 11 here to err on the side of caution), followed by a long, shallow tail; here, I have the number of new cases decrease by 10% per day for 10 more days to carry us to April 15th. Of course, there’s no reason that the spread of the disease should progress exactly in NYC as it did in Wuhan (and, in fact, the progression, at least from the time of institution of some drastic measures, will likely be much worse here, given the laxity of the steps we’ve taken to date), but given the lack of available data and models, I’m doing what I can.
Climate / Change 
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