Working Paper: CEPR ID: DP14791
Authors: Dirk Niepelt; Martin Gonzalezeiras
Abstract: We contrast the canonical epidemiological SIR model due to Kermack and McKendrick (1927) with more tractable alternatives that off er similar degrees of "realism" and flexibility. We provide results connecting the diff erent models which can be exploited for calibration purposes. We use the expected spread of COVID-19 in the United States to exemplify our results.
Keywords: epidemiology; SIR model; logistic model; COVID-19
JEL Codes: I18
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| number of susceptible (x) (C29) | infection rate (b) (I14) |
| number of infected (y) (I12) | infection rate (b) (I14) |
| number of susceptible (x) (C29) | infection dynamics (C69) |
| number of infected (y) (I12) | infection dynamics (C69) |
| modified SIR model (C59) | infection dynamics (C69) |
| hybrid model (C59) | infection dynamics and economic consequences (F44) |
| logistic model (C25) | economic modeling tractability (C51) |