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As we reach the apex of the COVID-19 pandemic, the most pressing questionfacing us is: can we even partially reopen the economy without risking a secondwave? We first need to understand if shutting down the economy helped. And ifit did, is it possible to achieve similar gains in the war against the pandemicwhile partially opening up the economy? To do so, it is critical to understandthe effects of the various interventions that can be put into place and theircorresponding health and economic implications. Since many interventions exist,the key challenge facing policy makers is understanding the potentialtrade-offs between them, and choosing the particular set of interventions thatworks best for their circumstance. In this memo, we provide an overview ofSynthetic Interventions (a natural generalization of Synthetic Control), adata-driven and statistically principled method to perform what-if scenarioplanning, i.e., for policy makers to understand the trade-offs betweendifferent interventions before having to actually enact them. In essence, themethod leverages information from different interventions that have alreadybeen enacted across the world and fits it to a policy maker's setting ofinterest, e.g., to estimate the effect of mobility-restricting interventions onthe U.S., we use daily death data from countries that enforced severe mobilityrestrictions to create a "synthetic low mobility U.S." and predict thecounterfactual trajectory of the U.S. if it had indeed applied a similarintervention. Using Synthetic Interventions, we find that lifting severemobility restrictions and only retaining moderate mobility restrictions (atretail and transit locations), seems to effectively flatten the curve. We hopethis provides guidance on weighing the trade-offs between the safety of thepopulation, strain on the healthcare system, and impact on the economy.

Two Burning Questions on COVID-19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave?