Evaluating Policies Early in a Pandemic: Bounding Policy Effects with Nonrandomly Missing Data
提出一种新方法，在检测有限且分布不均的情况下，界定早期大流行政策对病例数的影响，并应用于田纳西州扩大检测政策，发现其减少了病例。
Abstract During the early part of the COVID-19 pandemic, national and local governments introduced a number of policies to combat the spread of COVID-19. In this paper, we propose a new approach to bound the effects of such early-pandemic policies on COVID-19 cases and other outcomes while dealing with complications arising from (i) limited availability of COVID-19 tests, (ii) differential availability of COVID-19 tests across locations, and (iii) eligibility requirements for individuals to be tested. We use our approach study the effects of Tennessee’s expansion of COVID-19 testing early in the pandemic and find that the policy decreased COVID-19 cases.