Working Paper: NBER ID: w26917
Authors: Jeffrey E. Harris
Abstract: New York City has been rightly characterized as the epicenter of the coronavirus pandemic in the United States. Just one month after the first cases of coronavirus infection were reported in the city, the burden of infected individuals with serious complications of COVID-19 has already outstripped the capacity of many of the city’s hospitals. As in the case of most pandemics, scientists and public officials don’t have complete, accurate, real-time data on the path of new infections. Despite these data inadequacies, there already appears to be sufficient evidence to conclude that the curve in New York City is indeed flattening. The purpose of this report is to set forth the evidence for – and against – this preliminary but potentially important conclusion. Having examined the evidence, we then inquire: if the curve is indeed flattening, do we know what caused to it to level off?
Keywords: No keywords provided
JEL Codes: I1; I12; I18; I28
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| decline in reported new infections (F44) | flattening of the COVID-19 curve (E32) |
| social distancing measures (I14) | flattening of new infection rates (J11) |
| social distancing measures (I14) | decline in reported new infections (F44) |
| social distancing measures (I14) | reduction in transmission rates (C22) |