Social Distancing, Quarantine, Contact Tracing, and Testing: Implications of an Augmented SEIR Model
Abstract: This paper modifies the basic SEIR model to incorporate demand for health care. The model is used to study the relative effectiveness of policy interventions that include social distancing, quarantine, contact tracing, and random testing. A version of the model that is calibrated to the Ferguson et al. (2020) model suggests that permanent, high-intensity social distancing reduces mortality rates and peak ICU demand substantially, but that a policy that relaxes high-intensity social distancing over time in the context of a permanent efficient quarantine regime is even more effective and also likely to be less disruptive for the economy. Adding contact tracing and random testing to this policy further improves outcomes. However, given the uncertainty surrounding the disease parameters, especially the transmission rate of the disease and the effectiveness of policies, the uncertainty for health outcomes is very large.
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Provider: Federal Reserve Bank of Richmond
Part of Series: Working Paper
Publication Date: 2020-05-08
Note: * Due to the highly fluid nature of COVID-19 data, this working paper will be updated as a work in progress on the author's website.