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On Using SIR Models to Model Disease Scenarios for COVID-19

Quarterly Review 4111 | Published June 4, 2020

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On Using SIR Models to Model Disease Scenarios for COVID-19

Abstract

_From introduction:_ This paper is intended to introduce economists to a simple SIR model of the progression of COVID-19 to aid understanding of how such a model might be incorporated into more standard macroeconomic models. An SIR model is a Markov model of the spread of an epidemic in which the total population is divided into categories of being susceptible to the disease (S); actively infected with the disease (I); and resistant (R), meaning those that have recovered, died from the disease, or have been vaccinated. The initial distribution of the population across these states and the transition rates at which agents move between these three states determine how an epidemic plays out over time. These transition rates are determined by characteristics of the underlying disease and by the extent of mitigation and social distancing measures. This model allows for quantitative statements regarding the tradeoff between the severity and timing of suppression of the disease through social distancing and the progression of the disease in the population.


This paper is a substantially revised version of Staff Report 595, https://doi.org/10.21034/sr.595.