论文标题
估计SARS-COV-2感染的数量以及美国社会疏远的影响
Estimating the number of SARS-CoV-2 infections and the impact of social distancing in the United States
论文作者
论文摘要
了解已经感染了新型冠状病毒SARS-COV-2的人的数量，以及社会疏远政策在限制其传播方面的有效程度，对于有效的政策至关重要。在这里，我们介绍了美国确认病例降低真实感染数量的程度的估计，并分析了在减轻或抑制病毒时的有效社会疏远措施。我们的分析使用基于流行病的潜在微分方程模型的Covid-19死亡模型，其可能性具有可能性。我们为四个具有重要流行病的州提供分析：加利福尼亚，佛罗里达，纽约和华盛顿。我们的短期预测表明，这些状态可能遵循案件和死亡人数的增长的轨迹有所不同。
Understanding the number of individuals who have been infected with the novel coronavirus SARS-CoV-2, and the extent to which social distancing policies have been effective at limiting its spread, are critical for effective policy going forward. Here we present estimates of the extent to which confirmed cases in the United States undercount the true number of infections, and analyze how effective social distancing measures have been at mitigating or suppressing the virus. Our analysis uses a Bayesian model of COVID-19 fatalities with a likelihood based on an underlying differential equation model of the epidemic. We provide analysis for four states with significant epidemics: California, Florida, New York, and Washington. Our short-term forecasts suggest that these states may be following somewhat different trajectories for growth of the number of cases and fatalities.
