Working Paper: CEPR ID: DP16429
Authors: Nenad Kos; Satoshi Fukuda; Christoph Carnehl
Abstract: We study social distancing in an epidemiological model. Distancing reduces the individual’s probability of getting infected but comes at a cost. Equilibrium distancing flattens the curve and decreases the final size of the epidemic. We examine the effects of distancing on the outset, the peak, and the final size of the epidemic. Our results suggest that public policies that decrease the transmission rate can lead to unintended negative consequences in the short run but not in the long run. Therefore, it is important to distinguish between the interventions that affect the transmission rate and the interventions that affect contact rates.
Keywords: epidemics; equilibrium distancing; transmission rate; interventions; SIR
JEL Codes: I12; I18; C73
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| social distancing (I14) | probability of infection (C67) |
| social distancing (I14) | epidemic curve (Y10) |
| social distancing (I14) | final size of the epidemic (E17) |
| increase in cost of distancing (R48) | distancing (Y40) |
| reduced distancing (R11) | peak prevalence of the disease (I12) |
| transmission rate (F42) | peak prevalence (C41) |
| high transmission rate (F42) | prevent spread of disease (I14) |
| short-term policies aimed at decreasing transmission (F42) | higher peak prevalence (I12) |
| short-term policies aimed at decreasing transmission (F42) | smaller final size of the epidemic (E17) |
| interventions affecting distancing incentives (H31) | outcomes for short-run and long-run epidemic dynamics (C41) |