论文标题
COVID-19的预测模型应用于美国八个州
A predictive model for Covid-19 spread applied to eight US states
论文作者
论文摘要
提出了一个隔室流行模型来预测Covid-19病毒扩散。它考虑了:被发现和未被发现的感染人群,医疗隔离和社交隔离,隔离释放以及可能的再感染。模型中的系数是通过适合美国八个州的经验数据来评估的:亚利桑那州,加利福尼亚,佛罗里达,伊利诺伊州,路易斯安那州,新泽西州,纽约州和德克萨斯州。这些州共同占美国人口的43%;其中一些州似乎很好地处理了最初的暴发,而另一些州似乎是新兴的热点。在各州之间,COVID-19的演变相当相似:接触和恢复率的变化仍低于5%;然而,毫不奇怪,死亡率,再感染率,居住效应以及隔离中的释放速率的变化较大。结果表明,在第一次检测到的几个州可能已经进行了爆发,并且加利福尼亚可能已经看到多数以上的大流行。我们基于当前情况的预测表明,Covid-19将成为地方性,并传播了两年多。如果各州完全放松全家订单,大多数州可能会在2021年遇到次要峰值。如果锁定已被锁定,那么在大多数开放的州,到目前为止,到目前为止的Covid-19死亡人数可能会大大降低。此外,我们的模型预测,将接触率降低了10%,或者将测试降低约15%,或者将锁定稳定性增加一倍(从当前的$ \ sim $ \ sim $ 15%到$ \ sim $ 30%)将在一年内消除在德克萨斯州的感染。我们预测,我们预计到2020年11月1日,我们预测约有1100万次感染(包括未发现),800万例确认病例和630,000例累积死亡。
A compartmental epidemic model is proposed to predict the Covid-19 virus spread. It considers: both detected and undetected infected populations, medical quarantine and social sequestration, release from sequestration, plus possible reinfection. The coefficients in the model are evaluated by fitting to empirical data for eight US states: Arizona, California, Florida, Illinois, Louisiana, New Jersey, New York State, and Texas. Together these states make up 43% of the US population; some of these states appear to have handled their initial outbreaks well, while others appear to be emerging hotspots. The evolution of Covid-19 is fairly similar among the states: variations in contact and recovery rates remain below 5%; however, not surprisingly, variations are larger in death rate, reinfection rate, stay-at-home effect, and release rate from sequestration. The results reveal that outbreaks may have been well underway in several states before first detected and that California might have seen more than one influx of the pandemic. Our projections based on the current situation indicate that Covid-19 will become endemic, spreading for more than two years. Should states fully relax stay-at-home orders, most states may experience a secondary peak in 2021. If lockdowns had been kept in place, the number of Covid-19 deaths so far could have been significantly lower in most states that opened up. Additionally, our model predicts that decreasing contact rate by 10%, or increasing testing by approximately 15%, or doubling lockdown compliance (from the current $\sim$ 15% to $\sim$ 30%) will eradicate infections in the state of Texas within a year. Extending our fits for all of the US states, we predict about 11 million total infections (including undetected), 8 million cumulative confirmed cases, and 630,000 cumulative deaths by November 1, 2020.