Pollinger, Stefan (2020) Optimal Case Detection and Social Distancing Policies to Suppress COVID-19. TSE Working Paper, n. 20-1109, Toulouse

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Abstract

This paper shows that the optimal combination of social distancing and case detection allows for complete and efficient eradication of COVID-19. The first contribution is theoretical. I show that the optimal suppression-policy is a simple function of observable sufficient-statistics, making it easily implementable. I prove that optimal social distancing is the strongest when an outbreak is detected, and then gradually relaxed. If case detection is sufficiently efficient, social distancing vanishes wholly and quickly; otherwise, it needs to stay in place until a vaccine arrives. The second contribution is quantitative. I find that, if Italy adopts digital contact tracing, total suppression costs only 0.8% of annual GDP. In sharp contrast, under the current detection efficiency, the total cost of suppression amounts to at least 14% of GDP.