R < 1 as an economic constraint
Eric Budish
What the paper says
Abstract This paper proposes a novel pandemic response paradigm, and shows that it would have been the right middle ground between lockdown and ignore-the-virus for Covid-19: maximize social welfare subject to $$R\,{\le }\,1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>R</mml:mi> <mml:mspace/> <mml:mo>≤</mml:mo> <mml:mspace/> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> as a constraint . A simple graphical argument shows that this formulation is an approximately optimal way to balance socioeconomic and health objectives, because of a sharp kink in the benefits-of-risk-reduction curve at $$R\,{=}\,1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>R</mml:mi> <mml:mspace/> <mml:mo>=</mml:mo> <mml:mspace/> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> (both the curve and its kink are novel to this paper). Two critical insights emerge from this approach to the pandemic. First, the $$R\,{\le }\,1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>R</mml:mi> <mml:mspace/> <mml:mo>≤</mml:mo> <mml:mspace/> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> constraint imposes a “risk budget” on society. Society should optimally spend this budget on the social and economic activities with the highest ratio of socioeconomic value to disease-transmission risk, with targeted activity bans for activities with too low a ratio of value-to-risk. For example, schools have a much higher ratio of value-to-risk than bars, so society should optimally spend its risk budget on schools over bars. Second, what I call “low-cost risk reducers” (LCRRs) can significantly improve activities’ value-to-risk ratios and hence significantly reduce the cost of satisfying the $$R\,{\le }\,1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>R</mml:mi> <mml:mspace/> <mml:mo>≤</mml:mo> <mml:mspace/> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> constraint. Examples of LCRRs for Covid-19 include rapid testing, high-quality facemasks, stay-home-if-sick rules and improved air circulation. A simple numerical example, based on estimates from the medical literature for $$R_{0}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>R</mml:mi> <mml:mn>0</mml:mn> </mml:msub> </mml:math> and the efficacy of LCRRs for Covid-19, suggests the potential gains from this paper’s approach to the pandemic would have been enormous—plausibly trillions of dollars and hundreds of thousands of lives in the United States alone.
4 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.37 × 0.4 = 0.15 |
| M · momentum | 0.60 × 0.15 = 0.09 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.