Beth Israel Deaconess Medical Center, Emergency Medicine, Boston, MA.
Servizio Emergenza Territoriale 118, Torino, Italy.
Disaster Med Public Health Prep. 2020 Oct;14(5):e11-e15. doi: 10.1017/dmp.2020.218. Epub 2020 Jun 24.
The 2019 coronavirus disease (COVID-19) pandemic has led to physical distancing measures in numerous countries in an attempt to control the spread. However, these measures are not without cost to the health and economies of the nations in which they are enacted. Nations are now looking for methods to remove physical distancing measures and return to full functioning. To prevent a massive second wave of infections, this must be done with a data-driven methodology. The purpose of this article is to propose an algorithm for COVID-19 testing that would allow for physical distancing to be scaled back in a stepwise manner, which limits ensuing infections and protects the capacity of the health care system.
2019 冠状病毒病（COVID-19）大流行导致许多国家采取了保持身体距离的措施，试图控制其传播。然而，这些措施对实施这些措施的国家的健康和经济并非没有代价。各国现在正在寻找取消保持身体距离措施并恢复全面运作的方法。为了防止大规模的第二波感染，这必须采用数据驱动的方法。本文的目的是提出一种 COVID-19 检测算法，该算法可以逐步放宽保持身体距离的措施，从而限制后续感染并保护医疗系统的能力。
