Timing social distancing to avert unmanageable COVID-19 hospital surges

被引:38
作者
Duque, Daniel [1 ]
Morton, David P. [1 ]
Singh, Bismark [2 ]
Du, Zhanwei [3 ]
Pasco, Remy [4 ]
Meyers, Lauren Ancel [3 ,5 ]
机构
[1] Northwestern Univ, Ind Engn & Management Sci, Evanston, IL 60208 USA
[2] Friedrich Alexander Univ Erlangen Nurnberg, Discrete Math, D-91058 Erlangen, Germany
[3] Univ Texas Austin, Dept Integrat Biol, Austin, TX 78712 USA
[4] Univ Texas Austin, Operat Res & Ind Engn, Austin, TX 78712 USA
[5] Santa Fe Inst, Santa Fe, NM 87501 USA
关键词
COVID-19; optimization; cocooning; social distancing; public health response;
D O I
10.1073/pnas.2009033117
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Following the April 16, 2020 release of the Opening Up America Again guidelines for relaxing coronavirus disease 2019 (COVID-19) social distancing policies, local leaders are concerned about future pandemic waves and lack robust strategies for tracking and suppressing transmission. Here, we present a strategy for triggering short-term shelter-in-place orders when hospital admissions surpass a threshold. We use stochastic optimization to derive triggers that ensure hospital surges will not exceed local capacity and lockdowns are as short as possible. For example, Austin, Texas- the fastest-growing large city in the United States-has adopted a COVID-19 response strategy based on this method. Assuming that the relaxation of social distancing increases the risk of infection sixfold, the optimal strategy will trigger a total of 135 d (90% prediction interval: 126 d to 141 d) of sheltering, allow schools to open in the fall, and result in an expected 2,929 deaths (90% prediction interval: 2,837 to 3,026) by September 2021, which is 29% of the annual mortality rate. In the months ahead, policy makers are likely to face difficult choices, and the extent of public restraint and cocooning of vulnerable populations may save or cost thousands of lives.
引用
收藏
页码:19873 / 19878
页数:6
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