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Yang H, Sürer Ö, Duque D, et al. Design of COVID-19 Staged Alert Systems to Ensure Healthcare Capacity with Minimal Closures. medRxiv. 2020;doi: 10.1101/2020.11.26.20152520.
Yang, H., Sürer, �. �., Duque, D., Morton, D. P., Singh, B., Fox, S. J., Pasco, R., Pierce, K., Rathouz, P., Du, Z., Pignone, M., Escott, M. E., Adler, S. I., Johnston, S. C., & Meyers, L. A. (2020). Design of COVID-19 Staged Alert Systems to Ensure Healthcare Capacity with Minimal Closures. medRxiv : the preprint server for health sciences, . https://doi.org/10.1101/2020.11.26.20152520
Yang, Haoxiang, et al. "Design of COVID-19 Staged Alert Systems to Ensure Healthcare Capacity with Minimal Closures." medRxiv : the preprint server for health sciences vol. (2020). doi: https://doi.org/10.1101/2020.11.26.20152520
Yang H, Sürer Ö, Duque D, Morton DP, Singh B, Fox SJ, Pasco R, Pierce K, Rathouz P, Du Z, Pignone M, Escott ME, Adler SI, Johnston SC, Meyers LA. Design of COVID-19 Staged Alert Systems to Ensure Healthcare Capacity with Minimal Closures. medRxiv. 2020 Dec 24; doi: 10.1101/2020.11.26.20152520. PMID: 33269372; PMCID: PMC7709193.
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medRxiv. 2020 Dec 24; doi: 10.1101/2020.11.26.20152520.

Design of COVID-19 Staged Alert Systems to Ensure Healthcare Capacity with Minimal Closures.

medRxiv : the preprint server for health sciences

Haoxiang Yang, Özge Sürer, Daniel Duque, David P Morton, Bismark Singh, Spencer J Fox, Remy Pasco, Kelly Pierce, Paul Rathouz, Zhanwei Du, Michael Pignone, Mark E Escott, Stephen I Adler, S Claiborne Johnston, Lauren Ancel Meyers

Affiliations

  1. Los Alamos National Laboratory, Los Alamos, NM 87544, USA.
  2. Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL 60208, USA.
  3. Department of Mathematics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, 91058, Germany.
  4. Integrative Biology, The University of Texas at Austin, Austin, TX 78712, USA.
  5. Operations Research and Industrial Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
  6. Texas Advanced Computing Center (TACC), The University of Texas at Austin, Austin, TX 78712, USA.
  7. Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.
  8. The City of Austin, Austin, TX 78701, USA.
  9. Santa Fe Institute, Santa Fe, NM 87501, USA.

PMID: 33269372 PMCID: PMC7709193 DOI: 10.1101/2020.11.26.20152520

Abstract

Community mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including France's ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.

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